World Resources Institute
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WRI is a global research organization that works with governments, businesses, multilateral institutions and civil society groups to develop practical solutions that improve people’s lives and ensure nature can thrive. Their work is organised around seven global challenges: Food, Forests, Water, Energy, Climate, the Ocean, and Cities. They analyse these issues through the lenses of their four Centers of Excellence: Business, Economics, Finance, and Equity.
Available DatasetsShowing 310 of 310 results
- This layer shows the soil drainage, based on result of a classification established from Kalimantan RePPProT dataon 'SL_drain1' field (1990, 1:250,000 scale) . This data was provided and processed by Daemeter Consulting and was prepared by the World Resources Institute for use in the Suitability Mapper (2012). Data separated into categories: stagnant; very poor; poor; moderately good; good; excessive; very excessive.1Licence not specifiedover 1 year ago
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- Publication des résultstats du processus de conversion des anciens titres forestiers en contrat de concession forestière. Carte élaboré en 2009 par le Ministère de l'Environnement avec l'appui technique et financier de World Ressources Institute1Licence not specifiedover 1 year ago
- over 1 year ago
- Publication des résultstats du processus de conversion des anciens titres forestiers en contrat de concession forestière. Carte élaboré en 2009 par le Ministère de l'Environnement avec l'appui technique et financier de World Ressources Institute1Licence not specifiedover 1 year ago
- Carte produite par le Ministère de l'Environnement, Conservation de la Nature et Tourisme avec l'appui de World Resources Institute (WRI), grâce au financement du Programme Régional pour l'Environnement en Afrique Centrale (CARPE), de l'Agence Américaine pour le Développement (USAID).1Licence not specifiedover 1 year ago
- Global Forest Watch, en étroite collaboration avec le Ministère de l'Environement et des Forêts, a élaboré cette carte à partir des données existantes sur l'aménagement forestier au Cameroun. Certaines données – encore indisponsibles ou incomplètes – n'ont pu figurer sur cette carte, telles qu'une partie des forêts communautaires attribuées et Ventes de coupe. Les limites des UFA pourront eventuellement être modifier dans le cadre du processus de classement en cours.1Licence not specifiedover 1 year ago
- This archive contains all spatial data from the 2014 Interactive Forest Atlas of Cameroon.1Licence not specifiedover 1 year ago
- This archive contains all spatial data from the 2008 Interactive Forest Atlas of the Congo.1Licence not specifiedover 1 year ago
- Publication des résultstats du processus de conversion des anciens titres forestiers en contrat de concession forestière. Carte élaboré en 2009 par le Ministère de l'Environnement avec l'appui technique et financier de World Ressources Institute1Licence not specifiedover 1 year ago
- Carte produite par le Ministère de l'Environnement, Conservation de la Nature et Tourisme avec l'appui de WorldResources Institute (WRI), grâce au financement du Programme Régional pour l'Environnement en AfriqueCentrale (CARPE), de l'Agence Américaine pour le Développement (USAID).1Licence not specifiedover 1 year ago
- Cette couche représente un réseau de transport de haute tension des barrages hydroélectriques vers les centres de distribution au Cameroun. Le manque d’accès au sein des présentations étatiques des données spatiales et des informations documentaires officielles sur les lignes électriques rende la cartographie ces réseaux difficiles. Néanmoins, les données suivantes proviennent de la numérisation sur imagerie satellitaire Landsat et de la collecte de données auprès des compagnies d'électricité. La précision des données est dépendent de la résolution spatiale des images satellites utilisées et ne sont pas exhaustives sur l'étendue du pays. La dernière mise à jour ce réseau au niveau national a été effectué en 2013.1Licence not specifiedover 1 year ago
- El Instituto de Recursos Mundiales (WRI) y el Ministerio de Agricultura y Bosques (MAB) trabajan en estrecha colaboración desde el 2010 para mejorar las capacidades nacionales en monitoreo y manejo de bosques, enfocándoseen técnicas modernas para recopilar y gestionar datos. Los dos objetivos principales de esta colaboración son: (1) Desarrollar un sistema de información para el manejo de bosques completo y fácil de acceso, y (2) Entrenar al MABy al sector ONG que trabaja en bosques sobre sistemas de información geográfica (SIG), ánalisis de información, para mejorar el monitoreo, manejo y toma de decisiones acerca del uso de recursos forestales.Conjunta, esta información se integra al Atlas Forestal Interactivo de la República de Guinea Ecuatorial, una base de datos geográficos con información sobre la ordenación del territorio, uso desuelos y títutlos de bosques en Guina Ecuatorial. Este poster muestra el estado de bosques con información del Atlas de Diciembre 2016. La información más reciente puede ser descargada enel sitio web gnq.forest-atlas.org1Licence not specifiedover 1 year ago
- This layer represents a network of classified roads, rural roads and forest tracks in Cameroon. The road layer is updated using recently acquired medium-resolution satellite images for the period 2005 to 2010. The new forest roads have been digitized and organized according to the data source (type of imagery), The date (acquisition date of the image), as well as the state of the road and its main use. The status of the old roads has been updated based on more recent observations using satellite imagery. The refining of data on existing public, departmental, regional and national roads was carried out on the basis of information provided by topographical maps and ground tracking for areas where cloud cover over the images made identification difficult. Given the different sources of this layer, the accuracy of the data is a function of the spatial resolution of the satellite images used. The last update was in 2013.1Licence not specifiedover 1 year ago
- over 1 year ago
- The data for this layer correspond to the subdivisions of the concessions to be managed for a period of five years included in the management plans validated by MINFOF. The data for this layer are continually updated according to the availability of the new management plans, the descriptions of which are based on topographic maps (INC ) at a scale of 1: 200,000 and 1: 50,000.1Licence not specifiedover 1 year ago
- The boundaries of the geographical areas represent the non-industrial average plantations or areas planted in the agro-industrial plantations. Therefore, two databases have been combined to produce this layer (planted areas and agro-industrial plantation boundaries). The information presented was detected from the Landsat 8, Landsat 7 Aster, Alos satellite images and the missing information was replaced by the contents of the planted areas. This layer is treated with great caution, given its approximate nature. The accuracy of the information can thus vary from one polygon to another. This layer is continually updated.1Licence not specifiedover 1 year ago
- This archive contains all spatial data from the 2007 Interactive Forest Atlas of Cameroon.1Licence not specifiedover 1 year ago
- A standalone visualization application that can be used without an internet connection.1Licence not specifiedover 1 year ago
- Cette carte a été établie à partir des informations brutes issues des extraits de cartes et des descriptifs des limites des titres contenus dans les dossiersde requête de conversion. Elle ne préjuge pas de leur convertibilité ni d'éventuels problèmes administratifs quant aux limites au moment de leur obtention.Source des données cartographiques: limites administratives (IGC, UN-OCHA), titres forestiers (SPIAF), aires protégées (ICCN, WWF, SYGIAP, OSFAC). Date: Avril, 20071Licence not specifiedover 1 year ago
- Les données utilisées pour l'élaboration de cette carte ont été rassemblées conjointement par une équipe composée du personnel du World Resources Institute (WRI), du Ministère des Forêts et de la Faune (MINFOF) et d'autres partenaires à l'instar du Centre Technique de la Forêt Communale (CTFC) et GIZ-ProPSFE. En outre, Rainforest Alliance (RA) a activement participé au processus de validation des données. Cette carte est produite par le WRI et le MINFOF avec le soutien de l'Agence Américaine pour le Développement International (USAID), du Ministère de l'Environnement de Norvège et du Département pour le Développement International de le Grande Bretagne (DFID). Cette initiatve bénéficie également du support matériel (logiciels) de ESRI et Erdas.1Licence not specifiedover 1 year ago
- En 2004, l’intérêt de GFW pour le Cameroun et saprésence continue dans ce pays a été démontréd’une façon bien plus significative à travers laproduction de cet « Atlas forestier interactif duCameroun ». Cette première version de l’atlasinteractif est le fruit d’une étroite collaborationentre GFW, les autorités chargées de la gestion desforêts et toutes les parties prenantes recherchantune gestion forestière durable dans le pays.L’initiative actuelle est unique parce qu’ellerecueille des données et des informations forestières,les présente d’une façon visuelle et combinedes données et des informations qui, jusqu’ici,n’étaient ni reliées, ni facilement accessibles.L’amélioration de la qualité et l’accessibilité accrueaux informations sur le secteur forestier à traversl’utilisation d’outils modernes, tels que la télédétectionet les SIG, peut contribuer de manière significativeà l’amélioration de la gestion et à l’utilisationrationnelle, durable et responsable des forêts.1Licence not specifiedover 1 year ago
- Espaces territoriaux habités et dirigés au moins par un chef de troisième degré. Ce tableau regroupe les villages, Chef-lieu de Arrondissements , Chef-lieu de Départements , Villes et capitale. La liste des localité n'est pas exhaustive et les données ont été numérisées à partir des cartes topographiques et d'un fond provenant de l'Institue Nationale de Cartographie, à l'échelle de 1:200 000. Ces informations sont des approximations et ne presentent pas l'etat exacte des lieux habitees. En effet, la qualite et precision depend fortement de la source des donnees.1Licence not specifiedover 1 year ago
- El Instituto de Recursos Mundiales (WRI) y el Ministerio de Agricultura y Bosques (MAB) trabajan en estrecha colaboración para mejorar las capacidades nacionales de monitoreo de la tala forestal, en base a la utilización de datos y técnicas modernas de gestión de la información. En el marco de esta colaboración, y con el apoyo del Programa Regional de África Central para el Medio Ambiente (CARPE) de la Agencia de Estados Unidos para el Desarrollo Internacional (USAID), se realizó una cartografía completa y actualizada de títulos forestales y áreas protegidas diferentes de la República de Guinea Ecuatorial a partir de datos existentes. La representación de los títulos forestales está basada en información disponibles hasta el 31 de julio de 2013. Todas la información se encuentran en el Atlas Forestal Interactivo de la República de Guinea Ecuatorial. Al poner a disposición una cantidad considerable de información sobre la ordenación del territorio y la utilización de suelos, el Atlas convierte en una herramienta importante de ayuda a la toma de decisiones.1Licence not specifiedover 1 year ago
- Table regroupant toutes les filiales internationales auxquelles appartiennent une ou plusieurs sociétés d'exploitation forestière exerçant au Cameroun. Ces données fournissent des informations sur le nom et origine de la société; le type d'exploitation; et le volume exploitée annuellement. Sa mise à jour est effectuée de façon continue par les cadres du service de la cartographie du MINFOF avec l'appui de WRI.1Licence not specifiedover 1 year ago
- Cette base de données inclut les informations relatives à la localisation, l’opérateur et la capacité de chaque usine recensée. Les usines sont également présentées en fonction de leur capacité. Cette collecte d’information, provenants des documents officiels du MINFOF et des points de relevés GPS, est toujours en cours, ce qui rend la mise à jour continuelle. Les differentes catégories d'unités de transforamation du bois definies par le MINFOF sont en core moins précises et les données ne sont pas exhaustives. La derniere mise a jours a ete conduite en 2012.1Licence not specifiedover 1 year ago
- Cette couche représente les limites des forêts domaniales gérées par l'Etat (Unités forestières d'Aménagement) ou par les communes (Forêts communales). Les données de cette couche sont mises à jour continuellement suivant la disponibilité des nouveaux documents officiels à savoir les avis au public et les décrets de classement et les décrets d'attribution dont les descriptifs sont faits à base des cartes topographiques ( fond INC) à l'échelle de 1:200 000. La qualité de ces données peut varier en fonction des polygones.1Licence not specifiedover 1 year ago
- This report and associated material is the third in a series of interactive forest atlases of Cameroon. Readers and users of version 3.0 are encouraged to consult versions 1.0 (2005) and 2.0 (2007) for additional and more detailed information regarding Cameroon’s forest estate. Particular issues covered more extensively in these previous versions include discussions of forest legislation, forest land use classification categories, and the recent history of the forest estate. Versions 1.0 and 2.0 also offer more extensive cartographic representation. Online versions of these reports, interactive maps, and atlas data are available at http://www.wri.org/forests. For more information on areas in which the Atlas has had an impact since version 1.0 was released, please refer to Appendix 7 at the end of this document.1Licence not specifiedover 1 year ago
- Limites des subdivisions prévues pour l'exploitation annuelle au sein des concessions forestières. Elles font parties des series de production dans les UFE. Les concessionaires font la demande d'ouverture des concession chaque année au MINFOF, une année supplementaire peut être accordée pour le recollement à la demande du concessionnaire si tout le bois n' a pas été exploité.Les données de cette couche sont mises à jour continuellement suivant la disponibilité des nouveaux plans d'aménagement dont les descriptifs sont faits à base des cartes topographiques ( fond INC) à l'échelle de 1:200 000 et au 1: 50 000. Les données sont incomplètes, les concessionnaires ne publient pas régulièment ces données. Cette couche représente les documents et decisions prises relatif a la vente de coupe depuis 2002 et la derniere mise a jour a ete effectuer en 2016.1Licence not specifiedover 1 year ago
- Limits of the subdivisions foreseen for the annual exploitation within the forest concessions. They are part of the production series in the LEU. The concessionaires apply for the opening of the concessions each year to MINFOF, an additional year may be granted for replanting at the request of the concessionaire if all the timber has not been exploited. The data of this layer are updated continuously According to the availability of the new management plans, the descriptions of which are based on topographic maps (INC ) on the scale of 1: 200 000 and 1: 50 000. Data are incomplete, dealers do not publish regularly those data. This layer represents the documents and decisions taken on the sale of the cut since 2002 and the last update was made in 2016.1Licence not specifiedover 1 year ago
- This data set displays the boundaries of areas designated as comarcas in Panama. Comarcas are legally recognized semi-autonomous areas where indigenous peoples own the land and resources with rights of access, use, withdrawal, management, and exclusion. Although the Government retains ownership of subsoil resources, the indigenous community must be consulted by government and private organizations for proposed developments on their lands. The government and mining concessionaire are required to guarantee benefits to the community and compliance with sustainable development practices.1Licence not specifiedover 1 year ago
- This data set displays the boundaries of areas registered as community forests in Namibia. Community forests are recognized by the Minister of Environment and Tourism as communal lands subject to a management plan agreed upon by the Minister and a representative body of communal land members. In accordance with the agreement, the management plan grants communal land members the rights to manage and use natural resources, including the removal of forest produce for fuel, personal shelter, or livestock shelter; allows for agricultural activity; allows communal land members to authorize others to use the community forest's natural resources; and allows communal land members to collect a fee and set conditions for the use of natural resources.1Licence not specifiedover 1 year ago
- This map shows the rate at which forests could capture carbon from the atmosphere and store it in aboveground live biomass over the first 30 years of natural forest regrowth. It was created by combining ground-based measurements at thousands of locations around the world with 66 co-located environmental covariate layers in a machine learning model to produce a wall-to-wall map. Forest plot data used to train the model are sourced from published literature, which can be found in the Forest Carbon database (ForC, maintained by the Smithsonian Institute (https://github.com/forc-db)), as well as georeferenced data from publicly available national forest inventories. Although rates were estimated over all forest and savanna biomes globally, they are filtered here by “reforestable” area, as defined in Griscom et al. 2017 (PNAS). Reforestable areas exclude areas of native grasslands and croplands to safeguard the production of food and fiber and habitat for biological diversity.Extent: Global, within reforestation extent of Griscom et al. 2017 (which excludes the boreal, grassy biomes, and croplands) Resolution: 1 km x 1 kmCitation: Cook-Patton, S.C., Leavitt, S.M., Gibbs, D. et al. Mapping carbon accumulation potential from global natural forest regrowth. Nature 585, 545–550 (2020).Credits: Cook-Patton, S.C., S.M. Leavitt, D. Gibbs, N.L. Harris, K. Lister, K.J. Anderson-Teixeira, R.D. Briggs, R.L. Chazdon, T.W. Crowther, P.W. Ellis, H.P. Griscom, V. Herrmann, K.D. Holl, R.A. Houghton, C. Larrosa, G. Lomax, R. Lucas, P. Madsen, Y. Malhi, A. Paquette, J.D. Parker, K. Paul, D. Routh, S. Roxburgh, S. Saatchi, J.van den Hoogen, W.S. Walker, C.E. Wheeler, S.A. Wood, L. Xu, B.W. Griscom. 2020. Mapping carbon accumulation potential from natural forest regrowth. Nature, in press. https://www.nature.com/articles/s41586-020-2686-x. This work resulted from a collaboration between The Nature Conservancy, World Resources Institute, and 18 other institutions.Date: Applicable to the first 30 years of natural forest regrowth. Related layers: Carbon accumulation potential from natural forest regrowth in forest and savanna biomes, Uncertainty in carbon accumulation potential from natural forest regrowth1Licence not specifiedover 1 year ago
- The Round Table on Responsible Soy (RTRS) is a civil society organization that promotes the production, processing and marketing of responsible soy globally. It aims to promote sustainable production to reduce the social and environmental impacts of soybeans. The RTRS Responsible Soy Production Map is created based on [RTRS Standards](http://www.responsiblesoy.org/wpdm-package/rtrs-standard-for-responsible-soy-production/?lang=en), and is intended to guide responsible expansion of soybean production for RTRS certification. The RTRS committed to create macro-scale maps for Argentina, Brazil, Bolivia, and Paraguay to identify and preserve critical ecosystems and High Conservation Value Areas (HCVAs), as well as identify opportunities for responsible expansion of soy with low levels of environmental impact. The process began in Brazil in 2012, followed by Paraguay in 2013. Additional national level maps (e.g. Argentina) are in development. These national maps are created by RTRS National Technical Groups in each country, with experts representing all levels of the supply chain to interpret the global methodology at the national level. Each group was led by local coordinators and supported by GIS companies and consultative groups, as well as [BACP (IFC)](http://www.ifc.org/wps/wcm/connect/RegProjects_Ext_Content/IFC_External_Corporate_Site/BACP/), [IDH](https://www.idhsustainabletrade.com/), 3Fi, [WWF](http://www.worldwildlife.org/?utm_campaign=301-redirects&utm_source=wwf.org&utm_medium=referral&utm_content=wwf.org) and [The Gordon and Betty Moore Foundation](https://www.moore.org/), the principal funders of this project. The guides were developed according to Annex 4: RTRS approach to responsible conversion, page 20, of the [RTRS Production Standard](http://www.responsiblesoy.org/wpdm-package/rtrs-standard-for-responsible-soy-production/?lang=en). The macro-scale maps show the four different categories described in Guide 4 of the Standard, and the High Conservation Value Areas assessment guides for determination and management of HCVAs. *The categories are as follows:* 1. Areas which are critical for biodiversity (hotspots), where stakeholders agree there should not be any conversion of native to responsible soy production. 2. Areas with high importance for biodiversity where expansion of soy is only carried out after an HCVA assessment which identifies areas for conservation and areas where expansion can occur. 3. Areas where existing legislation is adequate to control responsible expansion (usually areas with importance for agriculture and lower conservation). 4. Areas which are already used for agriculture and where there is no remaining native vegetation except legal reserves and so no further expansion is occurring. 5. Areas deforested after 2009.1Licence not specifiedover 1 year ago
- This data set provides the boundaries of mining titles (títulos mineros concedidos) for Colombia. The shapefiles are compiled by Tierra Minada, a Colombian civil society group, utilizing information from the Colombian Mining Registry, which is maintained by the National Mining Agency. For more information about the data sets, visit the Tierra Minada website or Colombia’s Mining Cadaster Portal.1Licence not specifiedover 1 year ago
- RAdar for Detecting Deforestation (RADD) is a deforestation alert product that uses data from the European Space Agency’s Sentinel-1 satellites to detect forest disturbances in near-real-time . The RADD alerts use a detection methodology produced by Wageningen University and Research (WUR), Laboratory of Geo-information Science and Remote Sensing. These alerts are particularly advantageous in monitoring tropical forests, as Sentinel-1’s cloud-penetrating radar and frequent revisit times (6-12 days) allow for more consistent monitoring than alert products based on optical satellite images. Alerts are available for the primary humid tropical forest areas of South America, sub-Saharan Africa and insular Southeast Asia at a 10m spatial resolution, with coverage from January 2019 to the present for Africa and January 2020 to the present for South America and Southeast Asia. Pre-processed Sentinel-1 images are collected from Google Earth Engine, then quality controlled and normalized using historical time-series metrics. Forest disturbance alerts are then detected using a probabilistic algorithm. Each disturbance alert is detected from a single observation in the latest image if the forest disturbance probability is above 85%. If the forest disturbance probability reaches 97.5% in subsequent imagery within a maximum 90-day period, alerts are then marked as "high confidence". The product has a minimum mapping unit of 0.1 ha (equivalent to 10 Sentinel-1 pixels) to minimize false detections. Alerts are detected within areas of primary humid tropical forest, defined by Turubanova et al. (2018) and with 2001-2018 forest loss (Hansen et al. 2013) and mangroves (Bunting et al. 2018) removed. For more information on methodology and validation, please refer to Reiche et. al. (2021). The version presented here (v1) has been updated from that described in the paper (v0), with changes to the forest mask and a reduction of the minimum mapping unit. The RADD alerts were made possible thanks to the support of a coalition of ten major palm oil producers and buyers. Under the project, Wageningen University and Research (WUR) developed the detection method and Satelligence first scaled the system in Indonesia and Malaysia and provided additional prioritization of alerts for on-the-ground follow up. Additional support was provided by the US Forest Service and Norway’s International Climate and Forest Initiative. The alerts are currently generated by WUR using Google Earth Engine.*This data product utilizes a special encoding*Each pixel (alert) encodes the date of disturbance and confidence level in one integer value. The leading integer of the decimal representation is 2 for a low-confidence alert and 3 for a high-confidence alert, followed by the number of days since December 31, 2014. 0 is the no-data value. For example:20001 is a low confidence alert on January 1st, 201530055 is a high confidence alert on February 24, 201521847 is a low confidence alert on January 21, 20200 represents no alert1Licence not specifiedover 1 year ago
- OverviewThis data set delineates peatlands and other organic soils globally using five layers. Miettinen et al. 2016 was used for Indonesia and Malaysia, Hastie et al. 2022 was used in lowland Peru, Crezee et al. 2022 was used in the Congo basin, and Gumbricht et al. 2017 was used for all land between 40 degrees north and 60 degrees south (including areas covered by the aforementioned data sets). Xu et al. 2018 was used for all land above 40 degrees north. Miettinen et al. 2016, Xu et al. 2018 were rasterized to ~30x30 m resolution while Gumbricht et al. 2017, Crezee et al. 2022, and Hastie et al. 2022 were resampled from their native resolutions to ~30x30 m resolution in order to align with the Global Forest Change maps from Hansen et al. 2013. All layers were combined, i.e. Gumbricht et al. 2017 was also used in Indonesia/Malaysia, the Peruvian Amazon, and the Congo basin. All data sources have different methods for peatland delineation, which are described in their original publications. Crezee, B. et al. Mapping peat thickness and carbon stocks of the central Congo Basin using field data. Nature Geoscience 15: 639-644 (2022). https://www.nature.com/articles/s41561-022-00966-7. Data downloaded from https://congopeat.net/maps/, using classes 4 and 5 only (peat classes). Gumbricht, T. et al. An expert system model for mapping tropical wetlands and peatlands reveals South America as the largest contributor. Global Change Biology 23, 3581–3599 (2017). https://onlinelibrary.wiley.com/doi/full/10.1111/gcb.13689 Hastie, A. et al. Risks to carbon storage from land-use change revealed by peat thickness maps of Peru. Nature Geoscience 15: 369-374 (2022). https://www.nature.com/articles/s41561-022-00923-4 Miettinen, J., Shi, C. & Liew, S. C. Land cover distribution in the peatlands of Peninsular Malaysia, Sumatra and Borneo in 2015 with changes since 1990. Global Ecological Conservation. 6, 67– 78 (2016). https://www.sciencedirect.com/science/article/pii/S2351989415300470 Xu et al. PEATMAP: Refining estimates of global peatland distribution based on a meta-analysis. CATENA 160: 134-140 (2018). https://www.sciencedirect.com/science/article/pii/S0341816217303004 Resolution: 30 x 30mGeographic Coverage: GlobalFrequency of Updates: SporadicDate of Content: Range of yearsSources (by region):Crezee et al. 2022 (Congo basin) Gumbricht et al. 2017 (between 40 deg N and rest of southern hemisphere) Hastie et al. 2022 (Amazonian lowland Peru) Miettinen et al. 2016 (Indonesia and Malaysia) Xu et al. 2018 (temperate/boreal, north of 40 deg N)CautionsThis is a composite layer comprised of five data sets, each with their own methods and strengths and weaknesses. Refer to the original publications for each data set to learn more about specific cautions for each. All input layers have been converted from vector data or resampled from coarser raster dataLicenseCC-by-4.01Licence not specifiedover 1 year ago
- These three data sets, produced by WWF and RESOLVE, show the location of current tiger habitat and priority areas for habitat conservation.*Tiger Conservation Landscapes: *Tiger Conservation Landscapes (TCLs) are large blocks of contiguous or connected area of suitable tiger habitat that that can support at least five adult tigers and where tiger presence has been confirmed in the past 10 years. The data set was created by mapping tiger distribution, determined by land cover type, forest extent, and prey base, against a human influence index. Areas of high human influence that overlapped with suitable habitat were not considered tiger habitat.*Tx2 Tiger Conservation Landscapes: *This data set displays 29 Tx2 Tiger Conservation Landscapes (Tx2 TCLs), defined areas that could double the wild tiger population through proper conservation and management by 2020.*Terai Arc Landscape corridors: *This data set displays 9 forest corridors on the Nepalese side of the Terai Arc Landscape (TAL). Corridors are defined as existing forests connecting current Royal Bengal tiger meta-populations in Nepal and India.1Licence not specifiedover 1 year ago
- This map was created from two State Forestry Department (SFD) 2010 maps, supplemented by information from Environmental Impact Assessments (EIAs) for re-entry logging by specific licensees. Where not already identified in available SFD maps, names of licensees associated with individual numbered licenses have (where possible) been obtained from company documents and regional perspective maps from EIAs.Permit issuance dates and official areas in hectares are from various sources, including EIAs. Identities of corporate groupings to which individual licensee companies belong are based on various sources, including EIAs and official company documents.This map does not include Timber Licenses in Sarikei, Betong, Sri Aman, Samarahan and Kuching Divisions in the west of Sarawak, though there are known to be few such licenses in those Divisions. It is possible that some licenses shown on this map may have expired or been amended since 2010; other new licenses not shown here may also have been created. Individual licensees may also have joined or split from the named corporate groups. This map also does not include 'Belian Timber' Licenses.A number of the Timber Licenses are split into non-contiguous parts. In some cases separate boundary entries are given for each part; these are annotated 'Part 1' etc in the title. These 'Part' are not official names, but rather naming conventions used in the GIS cleaning of the data.1Licence not specifiedover 1 year ago
- A conservation easement, according to the Land Trust Alliance, is “a legal agreement between a landowner and a land trust or government agency that permanently limits uses of the land in order to protect its conservation values.” The National Conservation Easement Database (NCED) is the first national database of conservation easements in the United States. Voluntary and secure, the NCED respects landowner privacy and will not collect landowner names or sensitive information. This public-private partnership brings together national conservation groups, local and regional land trusts, and state and federal agencies around a common objective. The NCED provides a comprehensive picture of the estimated 40 million acres of privately owned conservation easement lands, recognizing their contribution to America’s natural heritage, a vibrant economy, and healthy communities.Before the NCED was created no single, nationwide system existed for sharing and managing information about conservation easements. By building the first national database and web site to access this information, the NCED helps agencies, land trusts, and other organizations plan more strategically, identify opportunities for collaboration, advance public accountability, and raise the profile of what's happening on-the-ground in the name of conservation.With the initial support of the U.S. Endowment for Forestry and Communities, NCED is the result of a collaboration between five environmental non-profits: The Trust for Public Land, Ducks Unlimited, Defenders of Wildlife, Conservation Biology Institute, and NatureServe.1Licence not specifiedover 1 year ago
- This data set, a collaboration between the GLAD (Global Land Analysis & Discovery) lab at the University of Maryland, Google, USGS, and NASA, measures areas of tree cover gain across all global land (except Antarctica and other Arctic islands) at 30 × 30 meter resolution, displayed as a 12-year cumulative layer. The data were generated using multispectral satellite imagery from the Landsat 7 thematic mapper plus (ETM+) sensor. Over 600,000 Landsat 7 images were compiled and analyzed using Google Earth Engine, a cloud platform for earth observation and data analysis. The clear land surface observations (30 × 30 meter pixels) in the satellite images were assembled and a supervised learning algorithm was then applied to identify per pixel tree cover gain.Tree cover gain was defined as the establishment of tree canopy at the Landsat pixel scale in an area that previously had no tree cover. Tree cover gain may indicate a number of potential activities, including natural forest growth or the crop rotation cycle of tree plantations.When zoomed out (< zoom level 13), pixels of gain are shaded according to the density of gain at the 30 x 30 meter scale. Pixels with darker shading represent areas with a higher concentration of tree cover gain, whereas pixels with lighter shading indicate a lower concentration of tree cover gain. There is no variation in pixel shading when the data is at full resolution (≥ zoom level 13).The tree cover canopy density of the displayed data is >50%.1Licence not specifiedover 1 year ago
- This data set provides the boundaries of known Licenses for Planted Forests (LPFs) within Sarawak, Malaysia. LPFs have a maximum tenure of 60 years, and must be over 1,000 hectares in size. Though they are designed for the purpose of planting of timber trees (mostly acacia), licensees are permitted to plant a portion of their licensed area with oil palm trees for a single rotation.The data set combines the boundaries of LPFs issued up to and included on the Sarawak Forestry Department (SFD) LPF map published 11th Jan 2011. Precise boundaries were sourced from regional SFD maps from 2010 and from Environmental Impact Assessment (EIA) reports for individual concessions.Licenses (and licensee subsidiaries) have been attributed to major corporate groups based on published company records and secondary sources. Where information on the areas within LPFs allotted for oil palm is available, the boundaries of these areas have been plotted and included in the separate dataset on oil palm concessions in Sarawak. Information on the permit issuance date, official total area in hectares, and plantable area in hectares for LPF licenses has been obtained directly from EIA reports or from secondary sources which have drawn on such reports. Information on area of each LPF license planted up to 2012 (where provided) has been obtained from official published reports or websites of relevant companies.It should be noted that it is common for LPF licenses to overlap with current Timber Licenses (see separate logging concession dataset for Sarawak). In such instances, LPF clearance and planting only proceeds in individual zones within the LPF when the Timber License holder has completed its own activities.1Licence not specifiedover 1 year ago
- This data set comes from the National Institute of Forests (INAB) in Guatemala. Through various joint efforts and in coordination with the Inter-institutional Group for Forest Monitoring and the GIZ, INAB obtained 308 high resolution RapidEye (RE) images to cover the entire country. These images, with a spatial resolution of 5 meters multispectral, were used to detail 16 classes of forest, 21 subtypes of forest, and 16 subtypes of forest by density. For broadleaf, coniferous, and mixed forest, detailed densities (sparse and dense) were differentiated for the first time in Guatemala.Mangroves were identified at the species level thanks to the database of Project Mangrove, 2012 MARN-CATHALAC, which has registers of four species. For the purposes of this map, un-forested zones were simply designated “No Forest”."1Licence not specifiedover 1 year ago
- There are three classes of Totally Protected Areas (TPAs) in Sarawak: National Parks, Wildlife Sanctuaries and Nature Reserves. Some of the TPAs are gazetted, while others remain ungazetted and are classified as 'proposed'.All boundaries are from Sarawak Forestry Department (SFD) maps. Three principal map sources were used: a high-resolution SFD map of northern Sarawak from February 2010; a high-resolution SFD map of central Sarawak from 2010; and low-resolution SFD maps of National Parks, Wildlife Sanctuaries and Nature Reserves available on the SFD website and accessed in April 2014. TPAs which are entirely over water are not included.The status of each protected area given in this data set is based on the list of gazetted TPAs as of 31st December 2014 given on the website of the Sarawak Forestry Corporation (accessed November 2015), and the Sarawak Forestry Department Annual Report of 2012.1Licence not specifiedover 1 year ago
- This data set displays 29 Tx2 Tiger Conservation Landscapes (Tx2 TCLs), defined areas that could double the wild tiger population through proper conservation and management by 2020.The number of wild tigers has declined from an estimated 100,000 in the early 1900s to a current estimate of around 3,500 adult animals. In response to this rapid decline, government officials convened in November 2010 to endorse the St. Petersburg Declaration, pledging to double the wild tiger population by 2020. To aid in this effort, Wikramanayake and his team conducted a landscape analysis of tiger habitat to determine if a recovery of such magnitude is possible. They identified 29 Tiger Conservation Landscapes with potential for doubling wild tiger population with proper conservation and management.1Licence not specifiedover 1 year ago
- This data set provides the boundaries of known oil palm concessions for the state of Sarawak, Malaysia, and was compiled from available public documents. Where available, associated information provided with this data set includes licensee name, permit number (Operational Ticket), corporate grouping, permit date, and official license area. This data set also includes areas under License for Planted Forest (LPF) agreements where oil palm has been planted for one rotation, where availableThe data set combines the boundaries of oil palm licenses obtained from Environmental Impact Assessment (EIA) reports for individual oil palm and LPF concessions (spanning various dates) and a regional State Forestry Department map from 2010 for northern Sarawak. The information drawn from oil palm EIA reports was compiled by Aidenvironment and SADIA, and combined with the other information by Earthsight Investigations. Licenses (and licensee subsidiaries) have been attributed to major corporate groups based on published company records and secondary sources.A number of the oil palm concession licenses are split into non-contiguous parts. In some cases separate boundary entries are given for each part; these are annotated 'Part 1' etc in the title. These 'Parts' are not official names, but rather naming conventions used in the GIS cleaning of the data.1Licence not specifiedover 1 year ago
- Terra-i is a near real-time monitoring system developed by that detects land cover changes in the tropics. It uses satellite data from MODIS vegetation indices (MOD13Q1 and NDVI) and products related to presence of water bodies (MOD35) as well as Tropical Rainfall Measuring Mission (TRMM) precipitation data to detect anthropogenic changes in vegetation cover every 16 days. Terra-i is a collaboration between the International Center for Tropical Agriculture (CIAT - DAPA), CGIAR’s Research Program on Forestry, Trees and Agroforestry (FTA), The Nature Conservancy (TNC), the University of Applied Sciences Western Switzerland (HEIG-VD), and King’s College London (KCL).The system is based on the premise that natural vegetation follows a predictable pattern of change in greenness from one date to the next, brought about by site-specific land and climatic conditions over the same period. The model is trained to understand the normal pattern of changes in vegetation greenness in relation to terrain and rainfall for a site, which allows for prediction of what the next vegetation response should be based on the historical data. If the prediction is significantly different from the historical responses in relation to pattern of rainfall and lasts for two 16-day periods in a row, the pixel is marked as potentially having changed by anthropogenic means.1Licence not specifiedover 1 year ago
- This data set displays the boundaries of areas designated as Māori Lands. These areas include both Māori freehold lands and Māori customary lands. Māori customary lands belong to the Crown but are communally held by Māori in accordance with customary values and practices, generally referred to as tikanga Māori. Māori freehold lands are Māori customary lands that have been converted, through application to the Māori Land Court, to the titled, private possession of Māori individuals or small groups (fewer than five owners). Most Māori land falls under the category of Māori freehold land. The Native Lands Act of 1862 created the Māori Land Court, which oversees the administration of freehold land titles.1Licence not specifiedover 1 year ago
- Estimates the uncertainty in carbon accumulation potential from natural forest regrowth. Specifically, the uncertainty metric is calculated as the modeled sequestration rate (mean of 100 random forest models) divided by the standard error of the 100 random forest models. Uncertainty is presented as a ratio because areas with higher sequestration rates tend to have high standard errors for their sequestration rates; presenting error as a ratio standardizes the model error by the sequestration rate. Higher numbers represent greater uncertainty in the model. For reference, an error ratio of 0.5 means that the standard error of the random forest models is half as large as the mean output of the models for that pixel. The rate uncertainties were estimated over all forest and savanna biomes.Extent: Global, within forest and savanna biomesCitation: Cook-Patton, S.C., Leavitt, S.M., Gibbs, D. et al. Mapping carbon accumulation potential from global natural forest regrowth. Nature 585, 545–550 (2020).Credits: Cook-Patton, S.C., S.M. Leavitt, D. Gibbs, N.L. Harris, K. Lister, K.J. Anderson-Teixeira, R.D. Briggs, R.L. Chazdon, T.W. Crowther, P.W. Ellis, H.P. Griscom, V. Herrmann, K.D. Holl, R.A. Houghton, C. Larrosa, G. Lomax, R. Lucas, P. Madsen, Y. Malhi, A. Paquette, J.D. Parker, K. Paul, D. Routh, S. Roxburgh, S. Saatchi, J.van den Hoogen, W.S. Walker, C.E. Wheeler, S.A. Wood, L. Xu, B.W. Griscom. 2020. Mapping carbon accumulation potential from natural forest regrowth. Nature, in press. https://www.nature.com/articles/s41586-020-2686-x. This work resulted from a collaboration between The Nature Conservancy, World Resources Institute, and 18 other institutions.Resolution: 1 x 1 kmDate: Applicable to the first 30 years of natural forest regrowth. Related layers: Carbon accumulation potential from natural forest regrowth in reforestable areas, Carbon accumulation potential from natural forest regrowth in forest and savanna biomes1Licence not specifiedover 1 year ago
- This data set displays the boundaries of the 24 legally-recognized and titled indigenous territories in Costa Rica as of 2008. It was created by the Observatorio del Desarrollo within the Universidad de Costa Rica, and is made available through the online Digital Atlas of Indigenous Peoples. Data sources include the Universidad de Costa Rica, la Universidad Nacional, and el Instituto Tecnológico. To view the interactive Atlas, please visit pueblosindigenas.odd.ucr.ac.cr/1Licence not specifiedover 1 year ago
- The tropical dry forests of the Gran Chaco region in Paraguay, Argentina, and Bolivia have become a hotspot of deforestation as cattle ranching and soy expand into the area. Deforestation monitoring in the Gran Chaco has been carried out by the non-profit Guyra Paraguay since 2011, using 30-meter resolution Landsat images for the 55 scenes that cover the Gran Chaco. The interpretation of forest change areas is done through multi-temporal analysis, which uses a base image from the last two years and a current image from the study month. Analysts use visual interpretation techniques to identify deforestation, including elements of tone, shape, size, texture, pattern, shadow, and context.GFW is no longer updating this data set on the platform. For more information on the Gran Chaco data set, as well as news and updates from the Gran Chaco team, please follow this link.1Licence not specifiedover 1 year ago
- This data set shows Roundtable on Sustainable Palm Oil (RSPO)-certified grower supply bases in Indonesia, though supply bases digitized by the RSPO are not available for download. A supply base consists of all lands that produce or support the production of palm oil processed at an RSPO-certified mill, and may include planted palm, nurseries, riparian buffers, HCV set-asides, palm oil mills and supporting infrastructure, certified smallholder oil palm lands, and roads. The data providers first compiled a list of all grower and group certifications conferred by the RSPO. As of March 30, 2017, about 400 palm oil mills and 20 smallholders’ groups had been certified by the RSPO globally. Polygons were digitized from maps available from audit reports hosted on the RSPO website, supplemented by spatial data on plantation boundaries provided by companies as part of the 2014 RSPO Annual Communication of Parties (ACOP), as well as plantations identified from Greenpeace and Sawit Watch concession data sets. Ancillary information was collected from audit reports including the dates of RSPO certification and letters of intent notifying stakeholders of the intent to pursue RSPO certification. The data were subset to plantations within Indonesia.1Licence not specifiedover 1 year ago
- This data set displays 9 forest corridors on the Nepalese side of the Terai Arc Landscape (TAL). Corridors are defined as existing forests connecting current Royal Bengal tiger meta-populations in Nepal and India.The TAL is spread over 4.95 million hectares, linking 14 transboundary protected areas across Nepal and India. This landscape has the second largest population of rhinos, one of the highest densities of tiger populations, and is home to the Asiatic elephant. In Nepal, TAL encompasses 2.31 million hectares extending over 14 districts and includes 75 percent of the remaining forests of lowland Nepal. In addition, TAL was recognized as a WWF Global 200 ecoregion and spans three Ramsar sites and two World Heritage Sites.1Licence not specifiedover 1 year ago
- Clark Labs, in partnership with the Gordon and Betty Moore Foundation and in support of the Foundation’s Oceans and Seafood Markets Initiative, has mapped an inventory of pond aquaculture and coastal habitats for selected countries. The goal has been to monitor the impact of shrimp farming on coastal wetlands. Ten countries thus far have been mapped for landcover for the years 1999, 2014, and 2018. Land cover categories include pond aquaculture, mangroves, other coastal wetlands, open water and “other”. In addition to land cover, changes are mapped between key categories for 1999-2014, 2014-2018 and 1999-2018.The maps for 2014 and 2018 are based on upscaled and pan-sharpened Landsat 8 imagery while the maps for 1999 data are based on upscaled Landsat 5 imagery. All maps are based on Landsat Collection 1 imagery. However, a new mapping based on Collection 2, as well as additional locations and years, is in progress and will be added in a future release.The study area of the coastal zone for mapping landcover is defined as a zone 10 km on either side of the coastline. Where necessary, the zone is extended to include land areas <= 5 m in elevation to a maximum extension of 60 km inland from the coast. The primary concern is to limit the inland extent to areas where it is likely that pond aquaculture is dominated by brackish water aquaculture and thereby has a stronger likelihood of being used for shrimp farming. When feasible, a distinction between freshwater and brackish pond aquaculture is made.Details of the methodologies used can be found in the reports at https://clarklabs.org/aquaculture/coastal-habitats-reports/Resolution: 15 x 15 metersDate of Content: 1999, 2014, 2018Geographic Coverage: Vietnam, Cambodia, Thailand, Myanmar, Malaysia, Indonesia, India, Bangladesh, Sri Lanka, EcuadorSource: © 2014-2022 Clark Labs, Clark University1Licence not specifiedover 1 year ago
- How to download this data:Click on "View Map" button at the top (the Download button allows you to download the footprint of tiles but not the actual alerts)Click on the tile where your area of interest is locatedCopy the whole URL from the pop-up and paste it into your internet browser. Download will begin automaticallyAdditional DetailsThis data set, assembled by Global Forest Watch, aggregates deforestation alerts from three alert systems (GLAD-L, GLAD-S2, RADD) into a single, integrated deforestation alert layer. This integration allows users to detect deforestation events faster than any single system alone, as the integrated layer is updated when any of the source alert systems are updated. The source alert systems are derived from satellites of varying spectral and spatial resolutions. 30m GLAD Landsat-based alerts are up-sampled to match the 10m spatial resolution of Sentinel-based alerts (GLAD-S2, RADD). This avoids the double counting of overlapping alerts, which are instead classified at a higher confidence level, indicated by darker pixels. Alerts are classified as high confidence when detected twice by a single alert system. Alerts detected by multiple alert systems are classified as highest confidence. With multiple sensors picking up change in the same location, we can be more confident that it was not a false positive and may not need to wait for additional satellite imagery to increase confidence in detected loss. *This data product utilizes a special encoding*Each pixel (alert) encodes the date of disturbance and confidence level in one integer value. The leading integer of the decimal representation is 2 for a low-confidence alert, 3 for a high-confidence alert, and 4 for an alert detected by multiple alert systems, followed by the number of days since December 31, 2014. 0 is the no-data value. For example:20001 is a low confidence alert on January 1st, 201530055 is a high confidence alert on February 24, 201521847 is a low confidence alert on January 21, 202041847 is a highest confidence alert (detected by multiple alert systems) on January 21, 2020. Alert date represents the earliest detection0 represents no alertResolution: 10 x 10mGeographic Coverage: 30°N to 30°SFrequency of Updates: DailyDate of Content: January 1st, 2015 – presentCautionsConfidence level may change retroactively as source data is updated GLAD-L: Available for entire tropics (30°N to 30°S) from January 1, 2018 to the present, and from 2015 to the present for select countries in the Amazon, Congo Basin, and insular Southeast Asia GLAD-S2: Available for the primary humid tropical forest areas of South America from January 2019 to the present RADD: Available for the primary humid tropical forest areas of South America, sub-Saharan Africa and insular Southeast Asia at a 10m spatial resolution, with coverage from January 2019 to the present for Africa and January 2020 to the present for South America and Southeast Asia In order to integrate the three alerting systems on a common grid, GLAD-L is resampled from 30m resolution to 10m resolution to match GLAD-S2 and RADD. As a result, pixels in the integrated layer may not exactly align with pixels in the individual GLAD-L layer. Each pixel in the integrated layer preserves the earliest date of detection from any alerting system, even if multiple systems have reported an alert in that pixel. In some situations, this may lead to inconsistent visualizations when switching from the integrated layer to individual alerting system layers. It is advisable to use in the integrated layer when you are interested in the earliest date of detection by any alerting system. However, it is better to use the individual alerting system layers if you are interested in a specific alert type. Although called ‘deforestation alerts’ these alerts detect forest or tree cover disturbances. This product does not distinguish between human-caused and other disturbance types. Where alerts are detected within plantation forests (more likely to happen in the GLAD-L system), alerts may indicate timber harvesting operations, without a conversion to a non-forest land use. The term deforestation is used because these are potential deforestation events, and alerts could be further investigated to determine this. LicenseCC by 4.0SourcesGLAD Alerts:Hansen, M.C., A. Krylov, A. Tyukavina, P.V. Potapov, S. Turubanova, B. Zutta, S. Ifo, B. Margono, F. Stolle, and R. Moore. 2016. Humid tropical forest disturbance alerts using Landsat data. Environmental Research Letters, 11 (3). GLAD-S2 Alerts:Pickens, A.H., Hansen, M.C., Adusei, B., and Potapov P. 2020. Sentinel-2 Forest Loss Alert. Global Land Analysis and Discovery (GLAD), University of Maryland. RADD Alerts:Reiche, J., Mullissa, A., Slagter, B., Gou, Y., Tsendbazar, N.E., Braun, C., Vollrath, A., Weisse, M.J., Stolle, F., Pickens, A., Donchyts, G., Clinton, N., Gorelick, N., Herold, M. 2021. Forest disturbance alerts for the Congo Basin using Sentinel-1. Environmental Research Letters. https://doi.org/10.1088/1748-9326/abd0a81Licence not specifiedover 1 year ago
- OverviewThis net flux layer is part of the forest carbon flux model described in Harris et al. (2021). This paper introduces a geospatial monitoring framework for estimating global forest carbon fluxes which can assist a variety of actors and organizations with tracking greenhouse gas fluxes from forests and in decreasing emissions or increasing removals by forests. Net forest carbon flux represents the net loss of forest ecosystem carbon, calculated as the between carbon emitted by forests and removed by (or sequestered by) forests during the model period. Net carbon flux is calculated by subtracting average gross removals from annual gross emissions in each forested pixel; negative values are where forests were net sinks of carbon and positive values are where forests were net sources of carbon between 2001 and 2023. Net fluxes are calculated following IPCC Guidelines for national greenhouse gas inventories in each pixel where forests existed in 2000 or were established between 2000 and 2020 according to Potapov et al. 2022. This layer reflects the cumulative net flux during the model period (2001-2023) and must be divided by 23 to obtain average annual net flux; net flux values cannot be assigned to individual years of the model. All input layers were resampled to a common resolution of 0.00025 x 0.00025 degrees each to match Hansen et al. (2013). Each year, the tree cover loss, drivers of tree cover loss, and burned area are updated. In 2023 and 2024, a few model input data sets and constants were changed as well, as described below. Please refer to this blog post for more information. The source of the ratio between belowground carbon and aboveground carbon. Previously used one global constant; now uses map from Huang et al. 2021 The years of tree cover gain. Previously used 2000-2012; now uses 2000-2020 from Potapov et al. 2022. The source of fire data. Previously used MODIS burned area; now uses tree cover loss from fires from Tyukavina et al. 2022. The source of peat maps. New tropical data sets have been included and the data set above 40 degrees north has been changed. Global warming potential (GWP) constants for CH4 and N2O. Previously used GWPs from IPCC Fifth Assessment Report; now uses GWPs from IPCC Sixth Assessment Report. Removal factors for older (>20 years) secondary temperate forests and their associated uncertainties. Previously used removal factors published in Table 4.9 of the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories; now uses corrected removal factors and uncertainties from the 4th Corrigenda to the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Planted tree extent and removal factors. Previously used Spatial Database of Planted Trees (SDPT) Version 1.0; now uses SDPT Version 2.0 and associated removal factors. Net flux is available for download in two different area units over the model duration: 1) megagrams of CO2 emissions/ha, and 2) megagrams of CO2 emissions/pixel. The first is appropriate for visualizing (mapping) net flux because it represent the density of carbon fluxes per hectare. The second is appropriate for calculating the net flux in an area of interest (AOI) because the values of the pixels in the AOI can be summed to obtain the total carbon flux for that area. The values in the latter were calculated by adjusting the net flux per hectare by the size of each pixel, which varies by latitude. When estimating net flux occurring over a defined number of years between 2001 and 2023, divide the values by the model duration and then multiply by the number of years in the period of interest. Both datasets only include pixels within forests, as defined in the methods of Harris et al. (2021) and updated with tree cover gain through 2020. Related Open Data Portal layers: Forest Carbon Emissions, Forest Carbon RemovalsGoogle Earth Engine asset and visualization scriptResolution: 30 x 30mGeographic Coverage: GlobalFrequency of Updates: AnnualDate of Content: 2001-2023CautionsData are the product of modeling and thus have an inherent degree of error and uncertainty. Users are strongly encouraged to read and fully comprehend the metadata and other available documentation prior to data use. Net flux reflects the total over the model period of 2001-2023, not an annual time series from which a trend can be derived. Thus, values must be divided by 23 to calculate average annual net flux. Uncertainty is higher in gross removals than emissions, particularly driven by uncertainty in removal factors. These uncertainties are propagated to the uncertainty in net flux. Values are applicable to forest areas (canopy cover >30 percent and >5 m height). See Harris et al. (2021) for further information on the forest definition used in the analysis. Emissions reflect stand-replacing disturbances as observed in Landsat satellite imagery and do not include emissions from unobserved forest degradation. Activity data used as the basis of the estimates contain temporal inconsistencies: Removals data contain temporal inconsistencies because tree cover gain represents a cumulative total from 2000-2020, rather than annual gains as estimated through 2023. Improvements in the detection of tree cover loss due to the incorporation of new satellite data and methodology changes between 2011 and 2015 may result in higher estimates of emissions in recent years compared to earlier years. Refer here for additional information. Large jumps in net flux along some boundary are due to the use of ecozone-specific removal factors. The changes in net flux occur at ecozone boundaries, where different removal factors are applied on each side. This dataset has been updated since its original publication. See Overview for more information.1Licence not specifiedover 1 year ago
- OverviewThis emissions layer is part of the forest carbon flux model described in Harris et al. (2021). This paper introduces a geospatial monitoring framework for estimating global forest carbon fluxes which can assist a variety of actors and organizations with tracking greenhouse gas fluxes from forests and in decreasing emissions or increasing removals by forests. Forest carbon emissions represent the greenhouse gas emissions arising from stand-replacing forest disturbances that occurred in each modeled year (megagrams CO2 emissions/ha, between 2001 and 2023). Emissions include all relevant ecosystem carbon pools (aboveground biomass, belowground biomass, dead wood, litter, soil organic carbon) and greenhouse gases (CO2, CH4, N2O). Emissions estimates for each pixel are calculated following IPCC Guidelines for national greenhouse gas inventories where stand-replacing disturbance occurred, as mapped in the Global Forest Change annual tree cover loss data of Hansen et al. (2013). The carbon emitted from each pixel is based on carbon densities in 2000, with adjustment for carbon accumulated between 2000 and the year of disturbance. Emissions reflect a gross estimate, i.e., carbon removals from subsequent regrowth are not included. Instead, gross carbon removals resulting from subsequent regrowth after clearing are accounted for in the companion forest carbon removals layer. The fraction of carbon emitted from each pixel upon disturbance (emission factor) is affected by several factors, including the direct driver of disturbance, whether fire was observed in the year of or preceding the observed disturbance event, whether the disturbance occurred on peat, and more. All emissions are assumed to occur in the year of disturbance. Emissions can be assigned to a specific year using the Hansen tree cover loss data; separate rasters for emissions for each year are not available from GFW. All input layers were resampled to a common resolution of 0.00025 x 0.00025 degrees each to match Hansen et al. (2013). Each year, the tree cover loss, drivers of tree cover loss, and burned area are updated. In 2023 and 2024, a few model input data sets and constants were changed as well, as described below. Please refer to this blog post for more information. The source of the ratio between belowground carbon and aboveground carbon. Previously used one global constant; now uses map from Huang et al. 2021 The years of tree cover gain. Previously used 2000-2012; now uses 2000-2020 from Potapov et al. 2022. The source of fire data. Previously used MODIS burned area; now uses tree cover loss from fires from Tyukavina et al. 2022. The source of peat maps. New tropical data sets have been included and the data set above 40 degrees north has been changed. Global warming potential (GWP) constants for CH4 and N2O. Previously used GWPs from IPCC Fifth Assessment Report; now uses GWPs from IPCC Sixth Assessment Report. Removal factors for older (>20 years) secondary temperate forests and their associated uncertainties. Previously used removal factors published in Table 4.9 of the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories; now uses corrected removal factors and uncertainties from the 4th Corrigenda to the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Planted tree extent and removal factors. Previously used Spatial Database of Planted Trees (SDPT) Version 1.0; now uses SDPT Version 2.0 and associated removal factors. Emissions are available for download in two different area units: 1) megagrams of CO2 emissions/ha, and 2) megagrams of CO2 emissions/pixel. The first is appropriate for visualizing (mapping) emissions because it represents the density of emissions per hectare. The second is appropriate for calculating the emissions in an area of interest (AOI) because the values of the pixels in the AOI can be summed to obtain the total emissions for that area. The values in the latter were calculated by adjusting the emissions per hectare by the size of each pixel, which varies by latitude. Both datasets only include pixels within forests, as defined in the methods of Harris et al. (2021) and updated with tree cover gain through 2020. Related Open Data Portal layers: Forest Carbon Removals, Net Forest Carbon FluxGoogle Earth Engine asset and visualization scriptResolution: 30 x 30mGeographic Coverage: GlobalFrequency of Updates: AnnualDate of Content: 2001-2023CautionsData are the product of modeling and thus have an inherent degree of error and uncertainty. Users are strongly encouraged to read and fully comprehend the metadata and other available documentation prior to data use. Values are applicable to forest areas only (canopy cover >30 percent and >5 m height or areas with tree cover gain). See Harris et al. (2021) for further information on the forest definition used in the analysis. Although emissions in each pixel are associated with a specific year of disturbance, emissions over an area of interest reflect the total over the model period of 2001-2023. Thus, values must be divided by 23 to calculate average annual removals. Emissions reflect stand-replacing disturbances as observed in Landsat satellite imagery and do not include emissions from unobserved forest degradation. Emissions reflect a gross estimate, i.e., carbon removals from any regrowth that occurs after disturbance are not included. Instead, gross carbon removals are accounted for in the companion forest carbon removals layer. Emissions data contain temporal inconsistencies. Improvements in the detection of tree cover loss due to the incorporation of new satellite data and methodology changes between 2011 and 2015 may result in higher estimates of emissions in recent years compared to earlier years. Refer here for additional information. Forest carbon emissions do not reflect carbon transfers from ecosystem carbon pools to the harvested wood products (HWP) pool. This dataset has been updated since its original publication. See Overview for more information. 1Licence not specifiedover 1 year ago
- OverviewThis carbon removals layer is part of the forest carbon flux model described in Harris et al. (2021). This paper introduces a geospatial monitoring framework for estimating global forest carbon fluxes which can assist a variety of actors and organizations with tracking greenhouse gas fluxes from forests and in decreasing emissions or increasing removals by forests. Forest carbon removals from the atmosphere (sequestration) by forest sinks represent the cumulative carbon captured (megagrams CO2/ha) by the growth of established and newly regrowing forests during the model period between 2001-2023. Removals include accumulation of carbon in both aboveground and belowground live tree biomass. Following IPCC Tier 1 assumptions for forests remaining forests, removals by dead wood, litter, and soil carbon pools are assumed to be zero. In each pixel, carbon removals are calculated following IPCC Guidelines for national greenhouse gas inventories where forests existed in 2000 or were established between 2000 and 2020 according to Potapov et al. 2022. Atmospheric carbon removed in each pixel is based on maps of forest type (e.g., mangrove, plantation), ecozone (e.g., humid Neotropics), forest age (e.g., primary, old secondary), and number of years of carbon removal. This layer reflects the cumulative removals during the model period (2001-2023) and must be divided by 23 to obtain an annual average during the model duration; removal rates cannot be assigned to individual years of the model. All input layers were resampled to a common resolution of 0.00025 x 0.00025 degrees each to match Hansen et al. (2013). Each year, the tree cover loss, drivers of tree cover loss, and burned area are updated. In 2023 and 2024, a few model input data sets and constants were changed as well, as described below. Please refer to this blog post for more information. The source of the ratio between belowground biomass carbon and aboveground biomass carbon. Previously used one global constant; now uses map from Huang et al. 2021 The years of tree cover gain. Previously used 2000-2012; now uses 2000-2020 from Potapov et al. 2022. The source of fire data. Previously used MODIS burned area; now uses tree cover loss from fires from Tyukavina et al. 2022. The source of peat maps. New tropical data sets have been included and the data set above 40 degrees north has been changed. Global warming potential (GWP) constants for CH4 and N2O. Previously used GWPs from IPCC Fifth Assessment Report; now uses GWPs from IPCC Sixth Assessment Report. Removal factors for older (>20 years) secondary temperate forests and their associated uncertainties. Previously used removal factors published in Table 4.9 of the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories; now uses corrected removal factors and uncertainties from the 4th Corrigenda to the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Planted tree extent and removal factors. Previously used Spatial Database of Planted Trees (SDPT) Version 1.0; now uses SDPT Version 2.0 and associated removal factors. Removals are available for download in two different area units over the model duration: 1) megagrams of CO2 removed/ha, and 2) megagrams of CO2 removed/pixel. The first is appropriate for visualizing (mapping) removals because it represents the density of removals per hectare. The second is appropriate for calculating the removals in an area of interest (AOI) because the values of the pixels in the AOI can be summed to obtain the total removals for that area. The values in the latter were calculated by adjusting the removals per hectare by the size of each pixel, which varies by latitude. When estimating removals occurring over a defined number of years between 2001 and 2023 to compare to emissions, divide total carbon removals by the model duration and then multiply by the number of years in the period of interest. Both datasets only include pixels within forests, as defined in the methods of Harris et al. (2021) and updated with tree cover gain through 2020. Related Open Data Portal layers: Forest Carbon Emissions, Net Forest Carbon FluxGoogle Earth Engine asset and visualization scriptResolution: 30 x 30mGeographic Coverage: GlobalFrequency of Updates: AnnualDate of Content: 2001-2023CautionsData are the product of modeling and thus have an inherent degree of error and uncertainty. Users are strongly encouraged to read and fully comprehend the metadata and other available documentation prior to data use. Values are applicable to forest areas (canopy cover >30 percent and >5 m height or areas with tree cover gain). See Harris et al. (2021) for further information on the forest definition used in the analysis. Carbon removals reflect the total removals over the model period of 2001-2023, not an annual time series from which a trend can be derived. Thus, values must be divided by 23 to calculate average annual removals. Uncertainty is higher in gross removals than emissions, particularly driven by uncertainty in removal factors. Carbon removals reflect a gross estimate, i.e., carbon emissions from previous or subsequent loss of tree cover are not included. Instead, gross carbon emissions are accounted for in the companion forest carbon emissions layer. Removals data contain temporal inconsistencies because tree cover gain represents a cumulative total from 2000-2020, rather than annual gains as estimated through 2023. Forest carbon removals reflect those occurring only within forest ecosystems and do not reflect carbon stock increases in the harvested wood products (HWP) pool. Large jumps in removals along some boundaries are due to the use of ecozone-specific removal factors. The changes in removals occur at ecozone boundaries, where different removal factors are applied on each side. This dataset has been updated since its original publication. See Overview for more information.1Licence not specifiedover 1 year ago
- This layer shows 2006 Land Cover, classified by type. The data is sourced from 2009 Ministry of Forestry data (1:250,000 scale). The World Resources Institute reclassified the original land cover categories from the Ministry of Forestry dataset for use in the Suitability Mapper (2012), into the following categories:Primary dry land forest, primary mangrove forest, primary swamp forest --> "primary forest"Secondary dry land forest, secondary mangrove forest, secondary swamp forest --> "secondary forest"Swamp, swamp scrubland --> "wetland"Bare land, savannah, scrubland --> "grassland/shrub"HTI, plantation --> "plantations"Dry rice land, dry rice land mixed with scrub, rice land, fish pond --> "agriculture"Mining, airport/harbor, settlement, transmigration area -->"settlements/other land use"Bodies of water, cloud --> excludedExact definitions and descriptions of the methodologies used to produce this data are not available.Original data available at http://appgis.dephut.go.id/appgis/kml.aspx under “Penutupan Lahan 2009."Exact definitions and descriptions of the methodologies used to produce this data are not available. Original data available at http://appgis.dephut.go.id/appgis/kml.aspx under “Penutupan Lahan 2009."1Licence not specifiedover 1 year ago
- OverviewThe tropical tree cover data maps tree extent at the ten-meter scale and tree cover at the half hectare scale to enable accurate monitoring of trees in urban areas, agricultural lands, and in open canopy and dry forest ecosystems. The data extends over 4.3 billion hectares of the global tropics. The data is derived from multi-temporal convolutional neural network models applied to Sentinel optical and radar imagery. The 10-meter dataset is a binary tree extent layer that is similar to a land cover map, while the tree cover data represents fractional cover at a half-hectare scale. More details on the methodology and analyses can be found on the GitHub page.Resolution: 0.5 haGeographic Coverage: 4.3 billion hectares of the tropics (-23.44 to 23.44 latitude)Frequency of Updates: Annual change detection maps starting in 2017 are planned for 2024 releaseDate of Content: 2020CautionsThis dataset uses a different definition of a tree and a different definition of tree cover than does Hansen et al. (2013). This dataset defines a tree according to both the height and crown diameter. Woody vegetation higher than 5 meters regardless of crown diameter, or between 3 and 5 meters with a minimum crown diameter of 5 meters is considered a tree. This definition is different from Hansen et al. (2013) which defines a tree as any vegetation at least 5 meters in height. The tropical tree cover dataset does not disambiguate plantation trees from non-plantation trees.Analyses or statistics derived for shapefiles smaller than 0.5ha may not be accurate1Licence not specifiedover 1 year ago
- This data set, created by the GLAD (Global Land Analysis & Discovery) lab at the University of Maryland and supported by Global Forest Watch, is the first Landsat-based alert system for tree cover loss. While most existing loss alert products use 250-meter resolution MODIS imagery, these alerts have a 30-meter resolution and thus can detect loss at a much finer spatial scale. The alerts are currently operational for select countries in the Amazon, Congo Basin, and Southeast Asia, and will eventually be expanded to the rest of the humid tropics.New Landsat 7 and 8 images are downloaded as they are posted online at USGS EROS, assessed for cloud cover or poor data quality, and compared to the three previous years of Landsat-derived metrics (including ranks, means, and regressions of red, infrared and shortwave bands, and ranks of NDVI, NBR, and NDWI). The metrics and the latest Landsat image are run through seven decision trees to calculate a median probability of forest disturbance. Pixels with probability >50% are reported as tree cover loss alerts. For more information on methodology, see the paper in Environmental Research Letters.Alerts remain unconfirmed until two or more out of four consecutive observations are labelled as tree cover loss. Alerts that remain unconfirmed for four consecutive observations or more than 180 days are removed from the data set. You can choose to view only confirmed alerts in the menu, though keep in mind that using only confirmed alerts misses the newest detections of tree cover loss.1Licence not specifiedover 1 year ago
- This data set, created by the GLAD (Global Land Analysis & Discovery) lab at the University of Maryland and supported by Global Forest Watch, is the first Landsat-based alert system for tree cover loss. While most existing loss alert products use 250-meter resolution MODIS imagery, these alerts have a 30-meter resolution and thus can detect loss at a much finer spatial scale. The alerts are currently operational for select countries in the Amazon, Congo Basin, and Southeast Asia, and will eventually be expanded to the rest of the humid tropics.New Landsat 7 and 8 images are downloaded as they are posted online at USGS EROS, assessed for cloud cover or poor data quality, and compared to the three previous years of Landsat-derived metrics (including ranks, means, and regressions of red, infrared and shortwave bands, and ranks of NDVI, NBR, and NDWI). The metrics and the latest Landsat image are run through seven decision trees to calculate a median probability of forest disturbance. Pixels with probability >50% are reported as tree cover loss alerts. For more information on methodology, see the paper in Environmental Research Letters.Alerts remain unconfirmed until two or more out of four consecutive observations are labelled as tree cover loss. Alerts that remain unconfirmed for four consecutive observations or more than 180 days are removed from the data set. You can choose to view only confirmed alerts in the menu, though keep in mind that using only confirmed alerts misses the newest detections of tree cover loss.1Licence not specifiedover 1 year ago
- The Round Table on Responsible Soy (RTRS) is a civil society organization that promotes the production, processing and marketing of responsible soy globally. It aims to promote sustainable production to reduce the social and environmental impacts of soybeans. The RTRS Responsible Soy Production Map is created based on [RTRS Standards](http://www.responsiblesoy.org/wpdm-package/rtrs-standard-for-responsible-soy-production/?lang=en), and is intended to guide responsible expansion of soybean production for RTRS certification. The RTRS committed to create macro-scale maps for Argentina, Brazil, Bolivia, and Paraguay to identify and preserve critical ecosystems and High Conservation Value Areas (HCVAs), as well as identify opportunities for responsible expansion of soy with low levels of environmental impact. The process began in Brazil in 2012, followed by Paraguay in 2013. Additional national level maps (e.g. Argentina) are in development. These national maps are created by RTRS National Technical Groups in each country, with experts representing all levels of the supply chain to interpret the global methodology at the national level. Each group was led by local coordinators and supported by GIS companies and consultative groups, as well as [BACP (IFC)](http://www.ifc.org/wps/wcm/connect/RegProjects_Ext_Content/IFC_External_Corporate_Site/BACP/), [IDH](https://www.idhsustainabletrade.com/), 3Fi, [WWF](http://www.worldwildlife.org/?utm_campaign=301-redirects&utm_source=wwf.org&utm_medium=referral&utm_content=wwf.org) and [The Gordon and Betty Moore Foundation](https://www.moore.org/), the principal funders of this project. The guides were developed according to Annex 4: RTRS approach to responsible conversion, page 20, of the [RTRS Production Standard](http://www.responsiblesoy.org/wpdm-package/rtrs-standard-for-responsible-soy-production/?lang=en). The macro-scale maps show the four different categories described in Guide 4 of the Standard, and the High Conservation Value Areas assessment guides for determination and management of HCVAs. *The categories are as follows:* 1. Areas which are critical for biodiversity (hotspots), where stakeholders agree there should not be any conversion of native to responsible soy production. 2. Areas with high importance for biodiversity where expansion of soy is only carried out after an HCVA assessment which identifies areas for conservation and areas where expansion can occur. 3. Areas where existing legislation is adequate to control responsible expansion (usually areas with importance for agriculture and lower conservation). 4. Areas which are already used for agriculture and where there is no remaining native vegetation except legal reserves and so no further expansion is occurring. 5. Areas deforested after 2009.1Licence not specifiedover 1 year ago
- Logging roads are often a first step to deforestation and forest degradation, but they are generally remote and sporadically used, making them difficult to monitor. The Logging Roads initiative, launched by Moabi and Global Forest Watch, uses crowdsourcing and tools developed by OpenStreetMap and the Humanitarian OpenStreetMap Team (HOT) to identify and monitor the spread of logging roads in the Congo Basin. Volunteers use satellite imagery to trace roads and identify the date the road appears.1Licence not specifiedover 1 year ago
- Publication des résultstats du processus de conversion des anciens titres forestiers en contrat de concession forestière. Carte élaboré en 2009 par le Ministère de l'Environnement avec l'appui technique et financier de World Ressources Institute1Licence not specifiedover 1 year ago
- This layer shows the elevation (in meters) for Kalimantan. 90 meter resolution. Data was prepared by the World Resources Institute for use in the Suitability Mapper (2012).1Licence not specifiedover 1 year ago
- Ce document regroupe les limites des permis de recherche (qui ne sont pas en exploitation) et permis d’exploitation minière au Cameroun. Selon la loi n 001-2001 d’Avril 2001, les permis de recherche sont délivrés par l’arrêté du Ministère chargé des mines, délivrées pour une durée de 3 ans, et ne doivent pas dépasser une superficie de plus de 1000 km carrés. Le permis d’exploitation qu’en a lui, est accordé par décret du Président de la République. La superficie à laquelle le permis d’exploitation est accordée est fonction du gisement et dois absolument être contenue à l’intérieur du permis de recherche. Cette couche se base sur les informations du Ministère de l'Industrie, des Mines et du développement Technologique (MINMIDT) et des sites Web de certains groupes miniers; par conséquent sa mise à jour est déterminer par la disponibilité de nouvelles données sur ces site officiel de l’Etat. Il est néanmoins, important de noter que le statut de validité de la plupart des titres est incertain. Cette couche représente les documents et décisions prises relatif à la vente de coupe depuis 2002, mais le statut de validité de la plupart des titres est incertain.1Licence not specifiedover 1 year ago
- The data used for the production of this map have been assembled by a team composed of staff from the World Resources Institute (WRI), the Ministry of Forestry and Wildlife (MINFOF) and other partners, including the Centre Technique de Forêt Communale (CTFC) and GIZ-ProPSFE. Rainforest Alliance (RA) actively participated in the data validation process. This map is produced by the WRI and MINFOF with the support of the United States Agency for International Development (USAID), the Nowegian Ministry for the Environment and the United Kingdom Department for International Development. This initiative is also supported with software contributions from ESRI and Erdas.1Licence not specifiedover 1 year ago
- over 1 year ago
- over 1 year ago
- {{description}}1Licence not specifiedover 1 year ago
- Les données utilisées pour l'élaboration de cette carte ont été rassemblées conjointement parune équipe composée du personnel du World Resources Institute (WRI), du Ministère desForêts et de la Faune (MINFOF) et d'autres partenaires à l'instar du Centre Technique de laForêt Communale (CTFC) et GIZ-ProPSFE. En outre, Rainforest Alliance (RA) a activementparticipé au processus de validation des données.Cette carte est produite par le WRI et le MINFOF avec le soutien de l'Agence Américaine pourle Développement International (USAID) à travers son Programme Régional de l'AfriqueCentrale pour l'Environnement (CARPE).Cette initiatve bénéficie également du support matériel (logiciels) de ESRI et Erdas.1Licence not specifiedover 1 year ago
- This archive contains all spatial data from the 2019 Interactive Forest Atlas of Cameroon.1Licence not specifiedover 1 year ago
- Cette carte reprend l'ensemble des informations du domaine forestier permanent (permis forestiers, aires protégées, réserves et zones tampons). Les permis sont représentés selon l'état d'avancement de leur plan d'aménagement.1Licence not specifiedover 1 year ago
- Carte produite par le Ministère de l'Environnement, Conservation de la Nature et Tourisme avec l'appui de WorldResources Institute (WRI), grâce au financement du Programme Régional pour l'Environnement en AfriqueCentrale (CARPE), de l'Agence Américaine pour le Développement (USAID).1Licence not specifiedover 1 year ago
- This layer shows the elevation (in meters) for Kalimantan. 90 meter resolution. Data was prepared by the World Resources Institute for use in the Suitability Mapper (2012).1Licence not specifiedover 1 year ago
- This archive contains all spatial data from the 2017 Interactive Forest Atlas of Equatorial Guinea.1Licence not specifiedover 1 year ago
- Cet archive contient toutes les données spatiales de l'Atlas forestier interactif du Cameroun 20191Licence not specifiedover 1 year ago
- over 1 year ago
- Les données utilisées pour l'élaboration de cette carte ont été rassemblées conjointement parune équipe composée du personnel du World Resources Institute (WRI), du Ministère desForêts et de la Faune (MINFOF) et d'autres partenaires à l'instar du Centre Technique de laForêt Communale (CTFC) et GTZ-ProPSFE. En outre, Rainforest Alliance (RA) a activementparticipé au processus de validation des données. Cette carte est produite par le WRI et le MINFOF avec le support de l'Agence Américaine pourle Développement International (USAID) à travers son Programme Régional de l'AfriqueCentrale pour l'Environnement (CARPE). Cette initiatve bénéficie également du support matériel (logiciels) de ESRI et Erdas.1Licence not specifiedover 1 year ago
- This publication highlights three promising opportunitites for DRC's development. First, DRC's new government can take advantage of opportunities for long-term conservation and sustainable use of forests. Second, the development assistance community can play an important role in support of measures to conserve forests. Third, the government and the development assistance community can collaborate to get forest policy high on DRC's development agenda.1Licence not specifiedover 1 year ago
- 1Licence not specifiedover 1 year ago
- over 1 year ago
- Depuis 2002, WRI et le Ministère des Forêts et de la Faune du Cameroun (MINFOF) oeuvrent conjointementà l'amélioration des capacités nationales de suivi de l'exploitation forestière par l'utilisation des données ettechniques modernes de gestion de l'information. Dans le cadre de cette collaboration, une cartographie complèteest à ce jour disponible pour les différents titres forestiers, aires protégées et infrastructures forestières duCameroun. Cette carte reprend l'ensemble des informations du domaine forestier permanent (UFA, forêts communales,aires protégées, et réserves forestières) ainsi que certains éléments du domaine forestier non permanent (forêtscommunautaires, ventes de coupes et principales zones d'extraction minière). Les UFA ont été représentéesselon leur avancement en terme de plan d'aménagement. Les Forêts communautaires reprises sur ce documentont une convention de gestion. Ces informations sont rassemblées dans l'Atlas Forestier Interactif du Cameroun.Lancé en Février 2004 au terme de deux ans de travaux, toutes les informationsy afférentes sont largement diffusées auprès de l'ensemble des intervenants du secteur et du grand public.Les données utilisées pour l'élaboration de cette carte ont été rassemblées conjointementpar une équipe composée du personnel de World Resources Institute (WRI), du Ministèredes Forêts et de la Faune (MINFOF) et les autres partenaires, incluant: le Centre Techniquede la Foresterie Communale (CTFC), GTZ-PROPSFE. En plus de ceux-ci, le Projet RIGG etTropical Forest Trust (TFT) ont aussi participé activement au processus de validation desdonnées.Cette carte est élaborée par WRI et le MINFOF avec l'appui de l'Agence Américaine pourle Développement International (USAID) à travers son Programme Régional de l'Afrique Centralepour l'Environnement (CARPE). Cette initiative est aussi appuyée par les contributions en logiciels de : ESRI et Leica Geosystems.1Licence not specifiedover 1 year ago
- Cet archive contient toutes les données spatiales de l'Atlas forestier interactif du Cameroun 20191Licence not specifiedover 1 year ago
- This archive contains all spatial data from the 2004 Interactive Forest Atlas of Cameroon.1Licence not specifiedover 1 year ago
- Ce document de synthèse de l’Atlas forestier interactif du Cameroun(V3.0) fournit au lecteur des informations sur les affectations et lestypes d’occupation des terres dans le Domaine Forestier Nationaljusqu’au mois de juin 2011. Il donne également un aperçu sur lestendances récentes de l’évolution des forêts de production, ainsique des développements récents dans le domaine de la foresteriecommunautaire. Il offre également les données actualisées sur lesaires protégées et le réseau routier public et privé, et donne de façonsubsidiaire des informations préliminaires sur les concessionsminières susceptibles d’empiéter sur le domaine forestier. En fin, cerapport met en exergue des exemples pratiques d’utilisation de l’Atlaset donne un aperçu de ses orientations et applications futures.1Licence not specifiedover 1 year ago
- Depuis 2002, GFW et le Ministère des Forêts et de la Faune du Cameroun (MINFOF) oeuvrent conjointement à l’amélioration des capacités nationales de suivi de l'exploitation forestière par l’utilisation des données et techniques modernes de gestion de l'information. Dans le cadre de cette collaboration, une cartographie complète et à jour des différents titres forestiers et aires protégées du Cameroun a été dressée à partir des données existantes sur l'affectation territoriale forestière. Cette carte reprend l'ensemble des informations du domaine forestier permanent (UFA, forêts communales, aires protégées et réserves forestières), ainsi que certains éléments du domaine forestier non permanent, tels que les forêts communautaires, les ventes de coupes et les principales zones d'extraction minière. Les UFA ont été représentées selon leur avancement en terme de plan d'aménagement. Les forêts communautaires reprises sur ce document ont une convention de gestion ou un plan simple de gestion approuvé. Seules les ventes de coupe valides en 2006 sont cartographiées. Ces informations sont rassemblées dans l'Atlas Forestier Interactif du Cameroun. Lancé en février 2004, au terme de deux ans de travaux, et largementdiffusé auprès de l’ensemble des intervenants du secteur et du grand public, cet Atlas constitue un important outil d’aide à la décision en rendant accessible un sommeimportante de données et d’informations sur l'affectation et l'utilisation des terres (entre autre par la cartographie des pistes d'exploitation).1Licence not specifiedover 1 year ago
- Limite regroupant une ou de plusieurs forêts de production, attribuées à une société forestière dont l'aménagement est commun. Une concession forestière est une unité d’exploitations forestières gérées par une compagnie qui peut être composée d'une ou plusieurs UFA. Les données de cette couche sont mises à jour continuellement suivant la disponibilité des nouveaux documents officiels à savoir les cartes inclues dans les plans d'aménagement dont les descriptifs sont faits à base des cartes topographiques (fond INC) à l'échelle de 1:200 000. Les données statistiques sont agrégées à l'échelle des concessions dans les cas où certaines concessions sont issues de regroupement de deux ou plusieurs UFA. La précision e chaque donnée presentee reste dependante de sa source.1Licence not specifiedover 1 year ago
- El Atlas Forestal Interactivo de Guinea Ecuatorial (Atlas) es un sistema de información forestal ubicado en el Ministerio de Agricultura y Bosques (MAB) y gestionado por un equipo conjunto compuesto por representantes del Instituto Nacional de Desarrollo Forestal y Gestión del Sistema de Áreas Protegidas (INDEFOR-AP) y el Instituto de Recursos Mundiales (WRI). Desarrollado en una plataforma del Sistema de Información Geográfica (SIG), el Atlas brinda información imparcial y actualizada sobre el sector forestal en Guinea Ecuatorial. Uno de sus objetivos principales es fortalecer el manejo forestal y el ordenamiento territorial al compilar todas las categorías de ordenación del territorio a través de la misma plataforma estandarizada.1Licence not specifiedover 1 year ago
- over 1 year ago
- This layer shows the mean rainfall (in mm) for the period from 1989 to 2009 (1000 m resolution). Data was prepared by the World Resources Institute for use in the Suitability Mapper (2012).1Licence not specifiedover 1 year ago
- This layer shows the slope (in percent) of Kalimantan calculated from the elevation layer (90 meter resolution): ArcToolBox, Spatial Analyst Tools, Surface, Slope (Output measurement: percent_rise).Data was prepared by the World Resources Institute for use in the Suitability Mapper (2012).1Licence not specifiedover 1 year ago
- This layer shows soil acidity, based on Kalimantan RePPProT data (1990, 1:250,000 scale). This data was provided and processed by Daemeter Consulting and was prepared by the World Resources Institute for use in the Suitability Mapper (2012). Data separated into categories of acidity: excessively acid (<4.0); extremely acid (4.0-4.5); very strongly acid (4.6-5.0); strongly acid (5.1-5.5); moderately acid (5.6-6.0); slightly acid (6.1-6.5); neutral (6.6-7.3).1Licence not specifiedover 1 year ago
- This publication highlights three promising opportunitites for DRC's development. First, DRC's new government can take advantage of opportunities for long-term conservation and sustainable use of forests. Second, the development assistance community can play an important role in support of measures to conserve forests. Third, the government and the development assistance community can collaborate to get forest policy high on DRC's development agenda.1Licence not specifiedover 1 year ago
- 1Licence not specifiedover 1 year ago
- over 1 year ago
- Cet archive contient toutes les données spatiales de l'Atlas forestier interactif du Cameroun 20191Licence not specifiedover 1 year ago
- This archive contains all spatial data from the 2013 Interactive Forest Atlas of the DRC.1Licence not specifiedover 1 year ago
- over 1 year ago
- This publication highlights three promising opportunitites for DRC's development. First, DRC's new government can take advantage of opportunities for long-term conservation and sustainable use of forests. Second, the development assistance community can play an important role in support of measures to conserve forests. Third, the government and the development assistance community can collaborate to get forest policy high on DRC's development agenda.1Licence not specifiedover 1 year ago
- over 1 year ago
- Cet archive contient toutes les données spatiales de l'Atlas forestier interactif du Cameroun 20191Licence not specifiedover 1 year ago
- 1Licence not specifiedover 1 year ago
- Depuis 2002, WRI et le Ministère des Forêts et de la Faune du Cameroun (MINFOF) oeuvrent conjointementà l'amélioration des capacités nationales de suivi de l'exploitation forestière par l'utilisation des données ettechniques modernes de gestion de l'information. Dans le cadre de cette collaboration une cartographie complèteest à ce jour disponible pour les différents titres forestiers, aires protégées et infrastructures forestières duCameroun. Cette carte reprend l'ensemble des informations du domaine forestier permanent (UFA, forêts communales,aires protégées, et reserves forestières) ainsi que certains éléments du domaine forestier non permanent (forêtscommunautaires, ventes de coupes et principales zone d'extraction minière). Les UFA ont été représentéesselon leur avancement en terme de plan d'aménagement. Les Forêts communautaires reprises sur ce documentont une convention de gestion ou un plan simple de gestion approuvé. Ces informations sont rassemblées dansl'Atlas Forestier Interactif du Cameroun. Lancé en Février 2004 au terme de deux ans de travaux, toutes les informationsy afférentes sont largement diffusées auprès de l'ensemble des intervenants du secteur et du grand public.Les données utilisées pour l'élaboration de cette carte ont été rassemblées conjointementpar une équipe composée du personnel de World Resources Institute (WRI), du Ministèredes Forêts et de la Faune (MINFOF) et les autres partenaires, incluant: le Centre Techniquede la Foresterie Communale (CTFC), GTZ-PROPSFE. En plus de ceux-ci, le Projet RIGG etTropical Forest Trust (TFT) ont aussi participé activement au processus de validation desdonnées.Cette carte est élaborée par WRI et le MINFOF avec l'appui de l'Agence Américaine pourle Développement International (USAID) à travers son Programme Régional de l'Afrique Centralepour l'Environnement (CARPE). Cette initiative est aussi appuyée par les contributions en logiciels de : ESRI et Leica Geosystems.1Licence not specifiedover 1 year ago
- Limites des forêts, attribuées dans le domaine non permanent et gérées par les communautés1Licence not specifiedover 1 year ago
- This publication highlights three promising opportunitites for DRC's development. First, DRC's new government can take advantage of opportunities for long-term conservation and sustainable use of forests. Second, the development assistance community can play an important role in support of measures to conserve forests. Third, the government and the development assistance community can collaborate to get forest policy high on DRC's development agenda.1Licence not specifiedover 1 year ago
- over 1 year ago
- almost 2 years ago
- This archive contains all spatial data from the 2009 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2008 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- Depuis 2002, WRI et le Ministère des Forêts et de la Faune du Cameroun (MINFOF) oeuvrentconjointement à l'amélioration des capacités nationales de suivi et d'aménagement forestier parl'utilisation des données de la télédétection et les techniques modernes de gestion de l'information.Les principaux objectifs de cette collaboration sont: (1) De développer à travers les méthodesstandards une base des données complète et conviviale pour la gestion de l'information forestiere,et (2) De renforcer les capacités du personnel du MINFOF et des ONG du domaine forestiersur la télédétection, le Système d'Information Geographique (SIG) et la gestion des bases desdonnées afin de promouvoir la bonne gestion de l'information forestière. Ces informations sontrassemblées dans l'Atlas Forestier Interactif du Cameroun dont la première version a été lancé enFévrier 2005. Après cette publication, les mises à jour sont faites regulièrement et de façon continueafin de répondre aux besoins des utilisateurs.Dans le cadre de cette collaboration, une cartographie complète de tous les titres forestiers (UFA,Aire protégée, Forêt communale, Forêt communautaire, Vente de coupe) et des infrastructuresforestières du Cameroun a été mise en place. Cette carte présente la situation à un temps précisdu statut du domaine forestier du Cameroun, extraite de la base des donnees del'Atlas Forestier Interactif.Les données utilisées pour l'élaboration de cette carte ont été rassemblées conjointementpar une équipe composée du personnel de World Resources Institute (WRI), du Ministèredes Forêts et de la Faune (MINFOF) et les autres partenaires, incluant: le Centre Techniquede la Foresterie Communale (CTFC), GTZ-PROPSFE. En plus de ceux-ci, le Projet RIGG etTropical Forest Trust (TFT) ont aussi participé activement au processus de validation desdonnées.Cette carte est élaborée par WRI et le MINFOF avec l'appui de l'Agence Américaine pourle Développement International (USAID) à travers son Programme Régional de l'Afrique Centralepour l'Environnement (CARPE). Cette initiative est aussi appuyée par les contributions en logiciels de : ESRI et Leica Geosystems.1Licence not specifiedalmost 2 years ago
- Cette seconde version de l’Atlas forestier interactifdu Cameroun constitue un outil pratique de gestionet de compréhension du secteur forestier camerounais.Il atteste d’autre part du sérieux de l’engagementdu partenariat mis en place entre la sociétécivile et le gouvernement.Cet atlas, unique en son genre, illustre l’engagementpour une transparence accrue dans le secteurforestier camerounais en assurant à tous les intervenantsun accès à des informations précises sur lagestion des forêts. Cet atlas est le fruit de cinq annéesde collaboration entre divers partenaires, notammentle Gouvernement camerounais, le WorldResources Institute (WRI) à travers son initiativeGlobal Forest Watch (GFW), le Jardin botaniqueet zoologique de Limbé, Cameroon EnvironmentalWatch, l’industrie forestière, les organismes donateurs internationaux et de nombreuses organisationsde la société civile et des institutions privées auCameroun et à l’étranger.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2013 Interactive Forest Atlas of the Central African Republic.1Licence not specifiedalmost 2 years ago
- Cette carte reprend l'ensemble des informations du domaine forestier permanent (permis forestiers, aires protégées, réserves et zones tampons).1Licence not specifiedalmost 2 years ago
- Processus de conversion des titres forestiers en contrats de concession forestière en République Democratique du Congo.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2013 Interactive Forest Atlas of the Central African Republic.1Licence not specifiedalmost 2 years ago
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- This archive contains all spatial data from the 2012 Interactive Forest Atlas of the DRC.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2009 Interactive Forest Atlas of the DRC.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2011 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2010 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2015 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2013 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2012 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
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- This archive contains all spatial data from the 2013 Interactive Forest Atlas of Equatorial Guinea.1Licence not specifiedalmost 2 years ago
- Cette base de données représente la situation des données (shapefile et divers documents) de l'AFI de la RDC au 31 Décembre 2017.1Licence not specifiedalmost 2 years ago
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- {{description}}1Licence not specifiedalmost 2 years ago
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- This layer shows the slope (in percent) of Kalimantan calculated from the elevation layer (90 meter resolution): ArcToolBox, Spatial Analyst Tools, Surface, Slope (Output measurement: percent_rise).Data was prepared by the World Resources Institute for use in the Suitability Mapper (2012).1Licence not specifiedalmost 2 years ago
- This layer shows the mean rainfall (in mm) for the period from 1989 to 2009 (1000 m resolution). Data was prepared by the World Resources Institute for use in the Suitability Mapper (2012).1Licence not specifiedalmost 2 years ago
- This layer shows the elevation (in meters) for Kalimantan. 90 meter resolution. Data was prepared by the World Resources Institute for use in the Suitability Mapper (2012).1Licence not specifiedalmost 2 years ago
- Limites des forêts, attribuées dans le domaine non permanent et gérées par les communautés1Licence not specifiedalmost 2 years ago
- This layer shows the soil drainage, based on result of a classification established from Kalimantan RePPProT dataon 'SL_drain1' field (1990, 1:250,000 scale) . This data was provided and processed by Daemeter Consulting and was prepared by the World Resources Institute for use in the Suitability Mapper (2012). Data separated into categories: stagnant; very poor; poor; moderately good; good; excessive; very excessive.1Licence not specifiedalmost 2 years ago
- This layer shows soil acidity, based on Kalimantan RePPProT data (1990, 1:250,000 scale). This data was provided and processed by Daemeter Consulting and was prepared by the World Resources Institute for use in the Suitability Mapper (2012). Data separated into categories of acidity: excessively acid (<4.0); extremely acid (4.0-4.5); very strongly acid (4.6-5.0); strongly acid (5.1-5.5); moderately acid (5.6-6.0); slightly acid (6.1-6.5); neutral (6.6-7.3).1Licence not specifiedalmost 2 years ago
- This layer shows the elevation (in meters) for Kalimantan. 90 meter resolution. Data was prepared by the World Resources Institute for use in the Suitability Mapper (2012).1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2019 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
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- This archive contains all spatial data from the 2017 Interactive Forest Atlas of Equatorial Guinea.1Licence not specifiedalmost 2 years ago
- This publication highlights three promising opportunitites for DRC's development. First, DRC's new government can take advantage of opportunities for long-term conservation and sustainable use of forests. Second, the development assistance community can play an important role in support of measures to conserve forests. Third, the government and the development assistance community can collaborate to get forest policy high on DRC's development agenda.1Licence not specifiedalmost 2 years ago
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- Carte produite par le Ministère de l'Environnement, Conservation de la Nature et Tourisme avec l'appui de WorldResources Institute (WRI), grâce au financement du Programme Régional pour l'Environnement en AfriqueCentrale (CARPE), de l'Agence Américaine pour le Développement (USAID).1Licence not specifiedalmost 2 years ago
- Processus de conversion des titres forestiers en contrats de concession forestière en République Democratique du Congo.1Licence not specifiedalmost 2 years ago
- Carte produite par le Ministère de l'Environnement, Conservation de la Nature et Tourisme avec l'appui de World Resources Institute (WRI), grâce au financement du Programme Régional pour l'Environnement en Afrique Centrale (CARPE), de l'Agence Américaine pour le Développement (USAID).1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2012 Interactive Forest Atlas of the DRC.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2013 Interactive Forest Atlas of the DRC.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2009 Interactive Forest Atlas of the DRC.1Licence not specifiedalmost 2 years ago
- Global Forest Watch, en étroite collaboration avec le Ministère de l'Environement et des Forêts, a élaboré cette carte à partir des données existantes sur l'aménagement forestier au Cameroun. Certaines données – encore indisponsibles ou incomplètes – n'ont pu figurer sur cette carte, telles qu'une partie des forêts communautaires attribuées et Ventes de coupe. Les limites des UFA pourront eventuellement être modifier dans le cadre du processus de classement en cours.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2011 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2010 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2007 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2004 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2009 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2008 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2015 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2013 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2012 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2014 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
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- This archive contains all spatial data from the 2008 Interactive Forest Atlas of the Congo.1Licence not specifiedalmost 2 years ago
- A standalone visualization application that can be used without an internet connection.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2013 Interactive Forest Atlas of Equatorial Guinea.1Licence not specifiedalmost 2 years ago
- Cette base de données représente la situation des données (shapefile et divers documents) de l'AFI de la RDC au 31 Décembre 2017.1Licence not specifiedalmost 2 years ago
- Cette carte reprend l'ensemble des informations du domaine forestier permanent (permis forestiers, aires protégées, réserves et zones tampons).1Licence not specifiedalmost 2 years ago
- Cette carte reprend l'ensemble des informations du domaine forestier permanent (permis forestiers, aires protégées, réserves et zones tampons). Les permis sont représentés selon l'état d'avancement de leur plan d'aménagement.1Licence not specifiedalmost 2 years ago
- Cette carte reprend l'ensemble des informations du domaine forestier permanent (permis forestiers, aires protégées, réserves et zones tampons). Les permis sont représentés selon l'état d'avancement de leur plan d'aménagement.1Licence not specifiedalmost 2 years ago
- Cette couche représente un réseau formé des routes classées, des routes rurales et des pistes forestières au Cameroun. La couche routière est mise à jour grâce à des images satellites de moyenne résolution récemment acquises pour la période allant de 2005 à 2010. Les nouvelles routes forestières ont été digitalisées et organisées en fonction de la source de données (type d’imagerie), de la date (date d’acquisition de l’image), ainsi que de l’état de la route et son utilisation principale. Le statut des anciennes routes a été actualisé en fonction des observations plus récentes au moyen d’images satellites. L’affinage des données sur les routes publiques, départementales, régionales et nationales existant a été effectué sur la base des informations fournies par les cartes topographiques et le suivi terrestre pour les zones où la couverture nuageuse au-dessus des images rendait leur identification difficile. Etant données les différentes sources de cette couches, la précision des données est fonction de la résolution spatiale des images satellites utilisées. La dernière mise à jour était en 2013.1Licence not specifiedalmost 2 years ago
- Cette couche est composé des chemins de fer fonctionnel ou en projet. Cette couche ferrovière a été mise à jour jusqu’en 2009 grâce à des images satellites de moyenne résolution récemment acquises pour la période allant de 2005 à 2010. Une mise à jour a été produite en 2013, avec des informations provenant d’OpenStreet Map et d'une étude supplémentaire du plan directeur ferroviaire national du Cameroun (KOTI, Soosung Engeneering, KR Network, KorPEC for MINEPAT).La précision des données est dependante de la résolution spatiale des images satellites utilisées. Par conséquent ce réseau doit être traite comme une estimation de l'état des lieux. Sa mise a jours est continuelle.1Licence not specifiedalmost 2 years ago
- Limites des espaces attribués pour la production agricole industrielle. Ces espaces sont en général des concessions à bail gérées par des sociétés nationales ou des filiales internationales. On peut citer entre autre la CDC, SOCAPALM, SAFACAM, PAMOL, HEVECAM, SUDCAM et SOSUCAM. Les données (contenant uniquement les limites géographiques) issues des décrets sont précises et correspondent aux limites de la concession. Le manque d’accès au sein du Ministère de l’Agriculture aux données spatiales et aux informations documentaires officielles sur les zones agro-industrielles rend la cartographie et le suivi de ces zones difficiles. La plupart des zones agro-industrielles incorporées dans cette couche a été cartographiée à partir d’images satellites, en combinaison avec une vérification sur le terrain pour déterminer les types de culture et l’identité des sociétés d’exploitation. Les limites géographiques doivent être considérées comme des estimations étant donné l’accès relatif à la documentation officielle, l’équipe de l’Atlas.1Licence not specifiedalmost 2 years ago
- This second version of the Interactive Forestry Atlasof Cameroon is a practical tool for understandingand working within Cameroons forest sector. Itdemonstrates the power of a committed partnershipbetween civil society and government.The Atlas, a first of its kind, demonstrates a commitmentto transparency in Cameroons forestsector by ensuring that all stakeholders have equalaccess to accurate forest management information.It is the result of Þ ve years of collaboration amongpartners including the Cameroon Government, theWorld Resources Institutes Global Forest Watchprogram, Limbé Botanical Gardens, Cameroon EnvironmentalWatch, the forest industry, internationaldonor agencies and countless civil society groupsand individuals both in Cameroon and abroad.1Licence not specifiedalmost 2 years ago
- In 2004, GFW’s interest in Cameroon and its continuedpresence in this country has been demonstrated ina much more meaningful manner with the productionof this Interactive Forestry Atlas of Cameroon. Thisfirst version of the interactive atlas is the product of aclose collaboration between GFW, forest managementauthorities, and all the stakeholders seekingsustainable forest management in the country.The current initiative is unique in that it gathers forestrydata and information, presents them in a visual manner,and combines data and information that have heretoforenot been connected nor easily accessible. Theimprovement in quality and accessibility of informationpertaining to the forestry sector through the use ofmodern tools such as RS and GIS may contributesignificantly to the improvement of the managementand rational, sustainable, and responsible use of forests.1Licence not specifiedalmost 2 years ago
- Limits of geographical spaces consisting of natural forests or reforestation areas reserved for conservation, research, or production functions. This layer includes integral ecological reserves, recreational forests, production reserves, and teaching and research forests. The data of this layer are updated continuously according to the availability of the new official documents, namely the notices to the public and the edges of creation whose descriptions are made based on topographic maps (INC) at the scale of 1: 200 000. Nevertheless, the lack of information on forest reserves at the level of MINFOF makes their follow-up difficult.1Licence not specifiedalmost 2 years ago
- The Ramsar Convention is an international treaty on the conservation and sustainable management of wetlands. The Convention entered into force in Cameroon on 20 July 2006. Since then, the country has had 7 Ramsar sites. Data from this layer were downloaded from the Ramsar site (www.ramsar.org) and boundaries were scanned from topographic maps and satellite imagery. Consequently, the limits presented are approximations of the state of the premises - information is essentially indicative in nature.1Licence not specifiedalmost 2 years ago
- Limits of allocated spaces for industrial agricultural production. These spaces are generally leases managed by national companies or international subsidiaries. These include CDC, SOCAPALM, SAFACAM, PAMOL, HEVECAM, SUDCAM and SOSUCAM. The data (containing only the geographical limits) resulting from the decrees are precise and correspond to the limits of the concession. The lack of access within the Ministry of Agriculture to spatial data and official documentary information on agro-industrial zones makes mapping and monitoring of these areas difficult. Most of the agro-industrial areas incorporated into this layer were mapped from satellite imagery in conjunction with a field audit to determine crop types and the identity of operating companies. Geographic boundaries should be considered as estimates given relative access to official documentation, the Atlas team.1Licence not specifiedalmost 2 years ago
- These data present community forests. They are part of the provisions of the forestry law of 1994 to facilitate the participation of local communities in the sustainable and equitable management of natural resources and their access to the socio-economic benefits of these resources. They are allocated in the non-permanent domain and managed by the communities and can measure up to 5000 hectares. The data for this layer are updated continuously according to the availability of new official documents, namely provisional management agreements and simple management plans and definitive management agreements, the descriptions of which are based on topographic maps (INC ) to The most recent data are from 2013. Nevertheless, it is important to note that the quality of these data may vary depending on the source. This layer does not guarantee the full presence of any community forests present in the country and the location of certain community forests may be imprecise.1Licence not specifiedalmost 2 years ago
- Cette carte a été établie à partir des informations brutes issues des extraits de cartes et des descriptifs des limites des titres contenus dans les dossiersde requête de conversion. Elle ne préjuge pas de leur convertibilité ni d'éventuels problèmes administratifs quant aux limites au moment de leur obtention.Source des données cartographiques: limites administratives (IGC, UN-OCHA), titres forestiers (SPIAF), aires protégées (ICCN, WWF, SYGIAP, OSFAC). Date: Avril, 20071Licence not specifiedalmost 2 years ago
- Carte produite par le Ministère de l'Environnement, Conservation de la Nature et Tourisme avec l'appui de WorldResources Institute (WRI), grâce au financement du Programme Régional pour l'Environnement en AfriqueCentrale (CARPE), de l'Agence Américaine pour le Développement (USAID).1Licence not specifiedalmost 2 years ago
- Les données utilisées pour l'élaboration de cette carte ont été rassemblées conjointement parune équipe composée du personnel du World Resources Institute (WRI), du Ministère desForêts et de la Faune (MINFOF) et d'autres partenaires à l'instar du Centre Technique de laForêt Communale (CTFC) et GTZ-ProPSFE. En outre, Rainforest Alliance (RA) a activementparticipé au processus de validation des données. Cette carte est produite par le WRI et le MINFOF avec le support de l'Agence Américaine pourle Développement International (USAID) à travers son Programme Régional de l'AfriqueCentrale pour l'Environnement (CARPE). Cette initiatve bénéficie également du support matériel (logiciels) de ESRI et Erdas.1Licence not specifiedalmost 2 years ago
- Les données utilisées pour l'élaboration de cette carte ont été rassemblées conjointement par une équipe composée du personnel du World Resources Institute (WRI), du Ministère des Forêts et de la Faune (MINFOF) et d'autres partenaires à l'instar du Centre Technique de la Forêt Communale (CTFC) et GIZ-ProPSFE. En outre, Rainforest Alliance (RA) a activement participé au processus de validation des données. Cette carte est produite par le WRI et le MINFOF avec le soutien de l'Agence Américaine pour le Développement International (USAID), du Ministère de l'Environnement de Norvège et du Département pour le Développement International de le Grande Bretagne (DFID). Cette initiatve bénéficie également du support matériel (logiciels) de ESRI et Erdas.1Licence not specifiedalmost 2 years ago
- Depuis 2002, WRI et le Ministère des Forêts et de la Faune du Cameroun (MINFOF) oeuvrent conjointementà l'amélioration des capacités nationales de suivi de l'exploitation forestière par l'utilisation des données ettechniques modernes de gestion de l'information. Dans le cadre de cette collaboration une cartographie complèteest à ce jour disponible pour les différents titres forestiers, aires protégées et infrastructures forestières duCameroun. Cette carte reprend l'ensemble des informations du domaine forestier permanent (UFA, forêts communales,aires protégées, et reserves forestières) ainsi que certains éléments du domaine forestier non permanent (forêtscommunautaires, ventes de coupes et principales zone d'extraction minière). Les UFA ont été représentéesselon leur avancement en terme de plan d'aménagement. Les Forêts communautaires reprises sur ce documentont une convention de gestion ou un plan simple de gestion approuvé. Ces informations sont rassemblées dansl'Atlas Forestier Interactif du Cameroun. Lancé en Février 2004 au terme de deux ans de travaux, toutes les informationsy afférentes sont largement diffusées auprès de l'ensemble des intervenants du secteur et du grand public.Les données utilisées pour l'élaboration de cette carte ont été rassemblées conjointementpar une équipe composée du personnel de World Resources Institute (WRI), du Ministèredes Forêts et de la Faune (MINFOF) et les autres partenaires, incluant: le Centre Techniquede la Foresterie Communale (CTFC), GTZ-PROPSFE. En plus de ceux-ci, le Projet RIGG etTropical Forest Trust (TFT) ont aussi participé activement au processus de validation desdonnées.Cette carte est élaborée par WRI et le MINFOF avec l'appui de l'Agence Américaine pourle Développement International (USAID) à travers son Programme Régional de l'Afrique Centralepour l'Environnement (CARPE). Cette initiative est aussi appuyée par les contributions en logiciels de : ESRI et Leica Geosystems.1Licence not specifiedalmost 2 years ago
- Depuis 2002, GFW et le Ministère des Forêts et de la Faune du Cameroun (MINFOF) oeuvrent conjointement à l’amélioration des capacités nationales de suivi de l'exploitation forestière par l’utilisation des données et techniques modernes de gestion de l'information. Dans le cadre de cette collaboration, une cartographie complète et à jour des différents titres forestiers et aires protégées du Cameroun a été dressée à partir des données existantes sur l'affectation territoriale forestière. Cette carte reprend l'ensemble des informations du domaine forestier permanent (UFA, forêts communales, aires protégées et réserves forestières), ainsi que certains éléments du domaine forestier non permanent, tels que les forêts communautaires, les ventes de coupes et les principales zones d'extraction minière. Les UFA ont été représentées selon leur avancement en terme de plan d'aménagement. Les forêts communautaires reprises sur ce document ont une convention de gestion ou un plan simple de gestion approuvé. Seules les ventes de coupe valides en 2006 sont cartographiées. Ces informations sont rassemblées dans l'Atlas Forestier Interactif du Cameroun. Lancé en février 2004, au terme de deux ans de travaux, et largementdiffusé auprès de l’ensemble des intervenants du secteur et du grand public, cet Atlas constitue un important outil d’aide à la décision en rendant accessible un sommeimportante de données et d’informations sur l'affectation et l'utilisation des terres (entre autre par la cartographie des pistes d'exploitation).1Licence not specifiedalmost 2 years ago
- Depuis 2002, WRI et le Ministère des Forêts et de la Faune du Cameroun (MINFOF) oeuvrent conjointementà l'amélioration des capacités nationales de suivi de l'exploitation forestière par l'utilisation des données ettechniques modernes de gestion de l'information. Dans le cadre de cette collaboration, une cartographie complèteest à ce jour disponible pour les différents titres forestiers, aires protégées et infrastructures forestières duCameroun. Cette carte reprend l'ensemble des informations du domaine forestier permanent (UFA, forêts communales,aires protégées, et réserves forestières) ainsi que certains éléments du domaine forestier non permanent (forêtscommunautaires, ventes de coupes et principales zones d'extraction minière). Les UFA ont été représentéesselon leur avancement en terme de plan d'aménagement. Les Forêts communautaires reprises sur ce documentont une convention de gestion. Ces informations sont rassemblées dans l'Atlas Forestier Interactif du Cameroun.Lancé en Février 2004 au terme de deux ans de travaux, toutes les informationsy afférentes sont largement diffusées auprès de l'ensemble des intervenants du secteur et du grand public.Les données utilisées pour l'élaboration de cette carte ont été rassemblées conjointementpar une équipe composée du personnel de World Resources Institute (WRI), du Ministèredes Forêts et de la Faune (MINFOF) et les autres partenaires, incluant: le Centre Techniquede la Foresterie Communale (CTFC), GTZ-PROPSFE. En plus de ceux-ci, le Projet RIGG etTropical Forest Trust (TFT) ont aussi participé activement au processus de validation desdonnées.Cette carte est élaborée par WRI et le MINFOF avec l'appui de l'Agence Américaine pourle Développement International (USAID) à travers son Programme Régional de l'Afrique Centralepour l'Environnement (CARPE). Cette initiative est aussi appuyée par les contributions en logiciels de : ESRI et Leica Geosystems.1Licence not specifiedalmost 2 years ago
- Depuis 2002, WRI et le Ministère des Forêts et de la Faune du Cameroun (MINFOF) oeuvrentconjointement à l'amélioration des capacités nationales de suivi et d'aménagement forestier parl'utilisation des données de la télédétection et les techniques modernes de gestion de l'information.Les principaux objectifs de cette collaboration sont: (1) De développer à travers les méthodesstandards une base des données complète et conviviale pour la gestion de l'information forestiere,et (2) De renforcer les capacités du personnel du MINFOF et des ONG du domaine forestiersur la télédétection, le Système d'Information Geographique (SIG) et la gestion des bases desdonnées afin de promouvoir la bonne gestion de l'information forestière. Ces informations sontrassemblées dans l'Atlas Forestier Interactif du Cameroun dont la première version a été lancé enFévrier 2005. Après cette publication, les mises à jour sont faites regulièrement et de façon continueafin de répondre aux besoins des utilisateurs.Dans le cadre de cette collaboration, une cartographie complète de tous les titres forestiers (UFA,Aire protégée, Forêt communale, Forêt communautaire, Vente de coupe) et des infrastructuresforestières du Cameroun a été mise en place. Cette carte présente la situation à un temps précisdu statut du domaine forestier du Cameroun, extraite de la base des donnees del'Atlas Forestier Interactif.Les données utilisées pour l'élaboration de cette carte ont été rassemblées conjointementpar une équipe composée du personnel de World Resources Institute (WRI), du Ministèredes Forêts et de la Faune (MINFOF) et les autres partenaires, incluant: le Centre Techniquede la Foresterie Communale (CTFC), GTZ-PROPSFE. En plus de ceux-ci, le Projet RIGG etTropical Forest Trust (TFT) ont aussi participé activement au processus de validation desdonnées.Cette carte est élaborée par WRI et le MINFOF avec l'appui de l'Agence Américaine pourle Développement International (USAID) à travers son Programme Régional de l'Afrique Centralepour l'Environnement (CARPE). Cette initiative est aussi appuyée par les contributions en logiciels de : ESRI et Leica Geosystems.1Licence not specifiedalmost 2 years ago
- Ce document de synthèse de l’Atlas forestier interactif du Cameroun(V3.0) fournit au lecteur des informations sur les affectations et lestypes d’occupation des terres dans le Domaine Forestier Nationaljusqu’au mois de juin 2011. Il donne également un aperçu sur lestendances récentes de l’évolution des forêts de production, ainsique des développements récents dans le domaine de la foresteriecommunautaire. Il offre également les données actualisées sur lesaires protégées et le réseau routier public et privé, et donne de façonsubsidiaire des informations préliminaires sur les concessionsminières susceptibles d’empiéter sur le domaine forestier. En fin, cerapport met en exergue des exemples pratiques d’utilisation de l’Atlaset donne un aperçu de ses orientations et applications futures.1Licence not specifiedalmost 2 years ago
- En 2004, l’intérêt de GFW pour le Cameroun et saprésence continue dans ce pays a été démontréd’une façon bien plus significative à travers laproduction de cet « Atlas forestier interactif duCameroun ». Cette première version de l’atlasinteractif est le fruit d’une étroite collaborationentre GFW, les autorités chargées de la gestion desforêts et toutes les parties prenantes recherchantune gestion forestière durable dans le pays.L’initiative actuelle est unique parce qu’ellerecueille des données et des informations forestières,les présente d’une façon visuelle et combinedes données et des informations qui, jusqu’ici,n’étaient ni reliées, ni facilement accessibles.L’amélioration de la qualité et l’accessibilité accrueaux informations sur le secteur forestier à traversl’utilisation d’outils modernes, tels que la télédétectionet les SIG, peut contribuer de manière significativeà l’amélioration de la gestion et à l’utilisationrationnelle, durable et responsable des forêts.1Licence not specifiedalmost 2 years ago
- Cette couche représente un réseau formé des routes classées, des routes rurales et des pistes forestières au Cameroun. La couche routière est mise à jour grâce à des images satellites de moyenne résolution récemment acquises pour la période allant de 2005 à 2010. Les nouvelles routes forestières ont été digitalisées et organisées en fonction de la source de données (type d’imagerie), de la date (date d’acquisition de l’image), ainsi que de l’état de la route et son utilisation principale. Le statut des anciennes routes a été actualisé en fonction des observations plus récentes au moyen d’images satellites. L’affinage des données sur les routes publiques, départementales, régionales et nationales existant a été effectué sur la base des informations fournies par les cartes topographiques et le suivi terrestre pour les zones où la couverture nuageuse au-dessus des images rendait leur identification difficile. Etant données les différentes sources de cette couches, la précision des données est fonction de la résolution spatiale des images satellites utilisées. La dernière mise à jour était en 2013.1Licence not specifiedalmost 2 years ago
- Cette couche est composé des chemins de fer fonctionnel ou en projet. Cette couche ferrovière a été mise à jour jusqu’en 2009 grâce à des images satellites de moyenne résolution récemment acquises pour la période allant de 2005 à 2010. Une mise à jour a été produite en 2013, avec des informations provenant d’OpenStreet Map et d'une étude supplémentaire du plan directeur ferroviaire national du Cameroun (KOTI, Soosung Engeneering, KR Network, KorPEC for MINEPAT).La précision des données est dependante de la résolution spatiale des images satellites utilisées. Par conséquent ce réseau doit être traite comme une estimation de l'état des lieux. Sa mise a jours est continuelle.1Licence not specifiedalmost 2 years ago
- Cette couche représente un réseau de transport de haute tension des barrages hydroélectriques vers les centres de distribution au Cameroun. Le manque d’accès au sein des présentations étatiques des données spatiales et des informations documentaires officielles sur les lignes électriques rende la cartographie ces réseaux difficiles. Néanmoins, les données suivantes proviennent de la numérisation sur imagerie satellitaire Landsat et de la collecte de données auprès des compagnies d'électricité. La précision des données est dépendent de la résolution spatiale des images satellites utilisées et ne sont pas exhaustives sur l'étendue du pays. La dernière mise à jour ce réseau au niveau national a été effectué en 2013.1Licence not specifiedalmost 2 years ago
- Limites des espaces attribués pour la production agricole industrielle. Ces espaces sont en général des concessions à bail gérées par des sociétés nationales ou des filiales internationales. On peut citer entre autre la CDC, SOCAPALM, SAFACAM, PAMOL, HEVECAM, SUDCAM et SOSUCAM. Les données (contenant uniquement les limites géographiques) issues des décrets sont précises et correspondent aux limites de la concession. Le manque d’accès au sein du Ministère de l’Agriculture aux données spatiales et aux informations documentaires officielles sur les zones agro-industrielles rend la cartographie et le suivi de ces zones difficiles. La plupart des zones agro-industrielles incorporées dans cette couche a été cartographiée à partir d’images satellites, en combinaison avec une vérification sur le terrain pour déterminer les types de culture et l’identité des sociétés d’exploitation. Les limites géographiques doivent être considérées comme des estimations étant donné l’accès relatif à la documentation officielle, l’équipe de l’Atlas.1Licence not specifiedalmost 2 years ago
- Espaces territoriaux habités et dirigés au moins par un chef de troisième degré. Ce tableau regroupe les villages, Chef-lieu de Arrondissements , Chef-lieu de Départements , Villes et capitale. La liste des localité n'est pas exhaustive et les données ont été numérisées à partir des cartes topographiques et d'un fond provenant de l'Institue Nationale de Cartographie, à l'échelle de 1:200 000. Ces informations sont des approximations et ne presentent pas l'etat exacte des lieux habitees. En effet, la qualite et precision depend fortement de la source des donnees.1Licence not specifiedalmost 2 years ago
- Ce document regroupe les limites des permis de recherche (qui ne sont pas en exploitation) et permis d’exploitation minière au Cameroun. Selon la loi n 001-2001 d’Avril 2001, les permis de recherche sont délivrés par l’arrêté du Ministère chargé des mines, délivrées pour une durée de 3 ans, et ne doivent pas dépasser une superficie de plus de 1000 km carrés. Le permis d’exploitation qu’en a lui, est accordé par décret du Président de la République. La superficie à laquelle le permis d’exploitation est accordée est fonction du gisement et dois absolument être contenue à l’intérieur du permis de recherche. Cette couche se base sur les informations du Ministère de l'Industrie, des Mines et du développement Technologique (MINMIDT) et des sites Web de certains groupes miniers; par conséquent sa mise à jour est déterminer par la disponibilité de nouvelles données sur ces site officiel de l’Etat. Il est néanmoins, important de noter que le statut de validité de la plupart des titres est incertain. Cette couche représente les documents et décisions prises relatif à la vente de coupe depuis 2002, mais le statut de validité de la plupart des titres est incertain.1Licence not specifiedalmost 2 years ago
- Limite regroupant une ou de plusieurs forêts de production, attribuées à une société forestière dont l'aménagement est commun. Une concession forestière est une unité d’exploitations forestières gérées par une compagnie qui peut être composée d'une ou plusieurs UFA. Les données de cette couche sont mises à jour continuellement suivant la disponibilité des nouveaux documents officiels à savoir les cartes inclues dans les plans d'aménagement dont les descriptifs sont faits à base des cartes topographiques (fond INC) à l'échelle de 1:200 000. Les données statistiques sont agrégées à l'échelle des concessions dans les cas où certaines concessions sont issues de regroupement de deux ou plusieurs UFA. La précision e chaque donnée presentee reste dependante de sa source.1Licence not specifiedalmost 2 years ago
- El Atlas Forestal Interactivo de Guinea Ecuatorial (Atlas) es un sistema de información forestal ubicado en el Ministerio de Agricultura y Bosques (MAB) y gestionado por un equipo conjunto compuesto por representantes del Instituto Nacional de Desarrollo Forestal y Gestión del Sistema de Áreas Protegidas (INDEFOR-AP) y el Instituto de Recursos Mundiales (WRI). Desarrollado en una plataforma del Sistema de Información Geográfica (SIG), el Atlas brinda información imparcial y actualizada sobre el sector forestal en Guinea Ecuatorial. Uno de sus objetivos principales es fortalecer el manejo forestal y el ordenamiento territorial al compilar todas las categorías de ordenación del territorio a través de la misma plataforma estandarizada.1Licence not specifiedalmost 2 years ago
- El Instituto de Recursos Mundiales (WRI) y el Ministerio de Agricultura y Bosques (MAB) trabajan en estrecha colaboración para mejorar las capacidades nacionales de monitoreo de la tala forestal, en base a la utilización de datos y técnicas modernas de gestión de la información. En el marco de esta colaboración, y con el apoyo del Programa Regional de África Central para el Medio Ambiente (CARPE) de la Agencia de Estados Unidos para el Desarrollo Internacional (USAID), se realizó una cartografía completa y actualizada de títulos forestales y áreas protegidas diferentes de la República de Guinea Ecuatorial a partir de datos existentes. La representación de los títulos forestales está basada en información disponibles hasta el 31 de julio de 2013. Todas la información se encuentran en el Atlas Forestal Interactivo de la República de Guinea Ecuatorial. Al poner a disposición una cantidad considerable de información sobre la ordenación del territorio y la utilización de suelos, el Atlas convierte en una herramienta importante de ayuda a la toma de decisiones.1Licence not specifiedalmost 2 years ago
- El Instituto de Recursos Mundiales (WRI) y el Ministerio de Agricultura y Bosques (MAB) trabajan en estrecha colaboración desde el 2010 para mejorar las capacidades nacionales en monitoreo y manejo de bosques, enfocándoseen técnicas modernas para recopilar y gestionar datos. Los dos objetivos principales de esta colaboración son: (1) Desarrollar un sistema de información para el manejo de bosques completo y fácil de acceso, y (2) Entrenar al MABy al sector ONG que trabaja en bosques sobre sistemas de información geográfica (SIG), ánalisis de información, para mejorar el monitoreo, manejo y toma de decisiones acerca del uso de recursos forestales.Conjunta, esta información se integra al Atlas Forestal Interactivo de la República de Guinea Ecuatorial, una base de datos geográficos con información sobre la ordenación del territorio, uso desuelos y títutlos de bosques en Guina Ecuatorial. Este poster muestra el estado de bosques con información del Atlas de Diciembre 2016. La información más reciente puede ser descargada enel sitio web gnq.forest-atlas.org1Licence not specifiedalmost 2 years ago
- This second version of the Interactive Forestry Atlasof Cameroon is a practical tool for understandingand working within Cameroons forest sector. Itdemonstrates the power of a committed partnershipbetween civil society and government.The Atlas, a first of its kind, demonstrates a commitmentto transparency in Cameroons forestsector by ensuring that all stakeholders have equalaccess to accurate forest management information.It is the result of Þ ve years of collaboration amongpartners including the Cameroon Government, theWorld Resources Institutes Global Forest Watchprogram, Limbé Botanical Gardens, Cameroon EnvironmentalWatch, the forest industry, internationaldonor agencies and countless civil society groupsand individuals both in Cameroon and abroad.1Licence not specifiedalmost 2 years ago
- In 2004, GFW’s interest in Cameroon and its continuedpresence in this country has been demonstrated ina much more meaningful manner with the productionof this Interactive Forestry Atlas of Cameroon. Thisfirst version of the interactive atlas is the product of aclose collaboration between GFW, forest managementauthorities, and all the stakeholders seekingsustainable forest management in the country.The current initiative is unique in that it gathers forestrydata and information, presents them in a visual manner,and combines data and information that have heretoforenot been connected nor easily accessible. Theimprovement in quality and accessibility of informationpertaining to the forestry sector through the use ofmodern tools such as RS and GIS may contributesignificantly to the improvement of the managementand rational, sustainable, and responsible use of forests.1Licence not specifiedalmost 2 years ago
- Cette seconde version de l’Atlas forestier interactifdu Cameroun constitue un outil pratique de gestionet de compréhension du secteur forestier camerounais.Il atteste d’autre part du sérieux de l’engagementdu partenariat mis en place entre la sociétécivile et le gouvernement.Cet atlas, unique en son genre, illustre l’engagementpour une transparence accrue dans le secteurforestier camerounais en assurant à tous les intervenantsun accès à des informations précises sur lagestion des forêts. Cet atlas est le fruit de cinq annéesde collaboration entre divers partenaires, notammentle Gouvernement camerounais, le WorldResources Institute (WRI) à travers son initiativeGlobal Forest Watch (GFW), le Jardin botaniqueet zoologique de Limbé, Cameroon EnvironmentalWatch, l’industrie forestière, les organismes donateurs internationaux et de nombreuses organisationsde la société civile et des institutions privées auCameroun et à l’étranger.1Licence not specifiedalmost 2 years ago
- Limits of geographical spaces consisting of natural forests or reforestation areas reserved for conservation, research, or production functions. This layer includes integral ecological reserves, recreational forests, production reserves, and teaching and research forests. The data of this layer are updated continuously according to the availability of the new official documents, namely the notices to the public and the edges of creation whose descriptions are made based on topographic maps (INC) at the scale of 1: 200 000. Nevertheless, the lack of information on forest reserves at the level of MINFOF makes their follow-up difficult.1Licence not specifiedalmost 2 years ago
- This layer represents a network of classified roads, rural roads and forest tracks in Cameroon. The road layer is updated using recently acquired medium-resolution satellite images for the period 2005 to 2010. The new forest roads have been digitized and organized according to the data source (type of imagery), The date (acquisition date of the image), as well as the state of the road and its main use. The status of the old roads has been updated based on more recent observations using satellite imagery. The refining of data on existing public, departmental, regional and national roads was carried out on the basis of information provided by topographical maps and ground tracking for areas where cloud cover over the images made identification difficult. Given the different sources of this layer, the accuracy of the data is a function of the spatial resolution of the satellite images used. The last update was in 2013.1Licence not specifiedalmost 2 years ago
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- Table regroupant toutes les filiales internationales auxquelles appartiennent une ou plusieurs sociétés d'exploitation forestière exerçant au Cameroun. Ces données fournissent des informations sur le nom et origine de la société; le type d'exploitation; et le volume exploitée annuellement. Sa mise à jour est effectuée de façon continue par les cadres du service de la cartographie du MINFOF avec l'appui de WRI.1Licence not specifiedalmost 2 years ago
- The Ramsar Convention is an international treaty on the conservation and sustainable management of wetlands. The Convention entered into force in Cameroon on 20 July 2006. Since then, the country has had 7 Ramsar sites. Data from this layer were downloaded from the Ramsar site (www.ramsar.org) and boundaries were scanned from topographic maps and satellite imagery. Consequently, the limits presented are approximations of the state of the premises - information is essentially indicative in nature.1Licence not specifiedalmost 2 years ago
- Limits of allocated spaces for industrial agricultural production. These spaces are generally leases managed by national companies or international subsidiaries. These include CDC, SOCAPALM, SAFACAM, PAMOL, HEVECAM, SUDCAM and SOSUCAM. The data (containing only the geographical limits) resulting from the decrees are precise and correspond to the limits of the concession. The lack of access within the Ministry of Agriculture to spatial data and official documentary information on agro-industrial zones makes mapping and monitoring of these areas difficult. Most of the agro-industrial areas incorporated into this layer were mapped from satellite imagery in conjunction with a field audit to determine crop types and the identity of operating companies. Geographic boundaries should be considered as estimates given relative access to official documentation, the Atlas team.1Licence not specifiedalmost 2 years ago
- The data for this layer correspond to the subdivisions of the concessions to be managed for a period of five years included in the management plans validated by MINFOF. The data for this layer are continually updated according to the availability of the new management plans, the descriptions of which are based on topographic maps (INC ) at a scale of 1: 200,000 and 1: 50,000.1Licence not specifiedalmost 2 years ago
- These data present community forests. They are part of the provisions of the forestry law of 1994 to facilitate the participation of local communities in the sustainable and equitable management of natural resources and their access to the socio-economic benefits of these resources. They are allocated in the non-permanent domain and managed by the communities and can measure up to 5000 hectares. The data for this layer are updated continuously according to the availability of new official documents, namely provisional management agreements and simple management plans and definitive management agreements, the descriptions of which are based on topographic maps (INC ) to The most recent data are from 2013. Nevertheless, it is important to note that the quality of these data may vary depending on the source. This layer does not guarantee the full presence of any community forests present in the country and the location of certain community forests may be imprecise.1Licence not specifiedalmost 2 years ago
- The boundaries of the geographical areas represent the non-industrial average plantations or areas planted in the agro-industrial plantations. Therefore, two databases have been combined to produce this layer (planted areas and agro-industrial plantation boundaries). The information presented was detected from the Landsat 8, Landsat 7 Aster, Alos satellite images and the missing information was replaced by the contents of the planted areas. This layer is treated with great caution, given its approximate nature. The accuracy of the information can thus vary from one polygon to another. This layer is continually updated.1Licence not specifiedalmost 2 years ago
- Les données utilisées pour l'élaboration de cette carte ont été rassemblées conjointement parune équipe composée du personnel du World Resources Institute (WRI), du Ministère desForêts et de la Faune (MINFOF) et d'autres partenaires à l'instar du Centre Technique de laForêt Communale (CTFC) et GIZ-ProPSFE. En outre, Rainforest Alliance (RA) a activementparticipé au processus de validation des données.Cette carte est produite par le WRI et le MINFOF avec le soutien de l'Agence Américaine pourle Développement International (USAID) à travers son Programme Régional de l'AfriqueCentrale pour l'Environnement (CARPE).Cette initiatve bénéficie également du support matériel (logiciels) de ESRI et Erdas.1Licence not specifiedalmost 2 years ago
- The data used for the production of this map have been assembled by a team composed of staff from the World Resources Institute (WRI), the Ministry of Forestry and Wildlife (MINFOF) and other partners, including the Centre Technique de Forêt Communale (CTFC) and GIZ-ProPSFE. Rainforest Alliance (RA) actively participated in the data validation process. This map is produced by the WRI and MINFOF with the support of the United States Agency for International Development (USAID), the Nowegian Ministry for the Environment and the United Kingdom Department for International Development. This initiative is also supported with software contributions from ESRI and Erdas.1Licence not specifiedalmost 2 years ago
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- This layer shows the slope (in percent) of Kalimantan calculated from the elevation layer (90 meter resolution): ArcToolBox, Spatial Analyst Tools, Surface, Slope (Output measurement: percent_rise).Data was prepared by the World Resources Institute for use in the Suitability Mapper (2012).1Licence not specifiedalmost 2 years ago
- This layer shows the mean rainfall (in mm) for the period from 1989 to 2009 (1000 m resolution). Data was prepared by the World Resources Institute for use in the Suitability Mapper (2012).1Licence not specifiedalmost 2 years ago
- This layer shows the elevation (in meters) for Kalimantan. 90 meter resolution. Data was prepared by the World Resources Institute for use in the Suitability Mapper (2012).1Licence not specifiedalmost 2 years ago
- Limites des forêts, attribuées dans le domaine non permanent et gérées par les communautés1Licence not specifiedalmost 2 years ago
- This layer shows the soil drainage, based on result of a classification established from Kalimantan RePPProT dataon 'SL_drain1' field (1990, 1:250,000 scale) . This data was provided and processed by Daemeter Consulting and was prepared by the World Resources Institute for use in the Suitability Mapper (2012). Data separated into categories: stagnant; very poor; poor; moderately good; good; excessive; very excessive.1Licence not specifiedalmost 2 years ago
- This layer shows soil acidity, based on Kalimantan RePPProT data (1990, 1:250,000 scale). This data was provided and processed by Daemeter Consulting and was prepared by the World Resources Institute for use in the Suitability Mapper (2012). Data separated into categories of acidity: excessively acid (<4.0); extremely acid (4.0-4.5); very strongly acid (4.6-5.0); strongly acid (5.1-5.5); moderately acid (5.6-6.0); slightly acid (6.1-6.5); neutral (6.6-7.3).1Licence not specifiedalmost 2 years ago
- This layer shows the elevation (in meters) for Kalimantan. 90 meter resolution. Data was prepared by the World Resources Institute for use in the Suitability Mapper (2012).1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2019 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
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- This archive contains all spatial data from the 2017 Interactive Forest Atlas of Equatorial Guinea.1Licence not specifiedalmost 2 years ago
- This publication highlights three promising opportunitites for DRC's development. First, DRC's new government can take advantage of opportunities for long-term conservation and sustainable use of forests. Second, the development assistance community can play an important role in support of measures to conserve forests. Third, the government and the development assistance community can collaborate to get forest policy high on DRC's development agenda.1Licence not specifiedalmost 2 years ago
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- Carte produite par le Ministère de l'Environnement, Conservation de la Nature et Tourisme avec l'appui de WorldResources Institute (WRI), grâce au financement du Programme Régional pour l'Environnement en AfriqueCentrale (CARPE), de l'Agence Américaine pour le Développement (USAID).1Licence not specifiedalmost 2 years ago
- Processus de conversion des titres forestiers en contrats de concession forestière en République Democratique du Congo.1Licence not specifiedalmost 2 years ago
- Carte produite par le Ministère de l'Environnement, Conservation de la Nature et Tourisme avec l'appui de World Resources Institute (WRI), grâce au financement du Programme Régional pour l'Environnement en Afrique Centrale (CARPE), de l'Agence Américaine pour le Développement (USAID).1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2012 Interactive Forest Atlas of the DRC.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2013 Interactive Forest Atlas of the DRC.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2009 Interactive Forest Atlas of the DRC.1Licence not specifiedalmost 2 years ago
- Global Forest Watch, en étroite collaboration avec le Ministère de l'Environement et des Forêts, a élaboré cette carte à partir des données existantes sur l'aménagement forestier au Cameroun. Certaines données – encore indisponsibles ou incomplètes – n'ont pu figurer sur cette carte, telles qu'une partie des forêts communautaires attribuées et Ventes de coupe. Les limites des UFA pourront eventuellement être modifier dans le cadre du processus de classement en cours.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2011 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2010 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2007 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2004 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2009 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2008 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2015 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2013 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2012 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2014 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
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- This archive contains all spatial data from the 2008 Interactive Forest Atlas of the Congo.1Licence not specifiedalmost 2 years ago
- A standalone visualization application that can be used without an internet connection.1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2013 Interactive Forest Atlas of Equatorial Guinea.1Licence not specifiedalmost 2 years ago
- Cette base de données représente la situation des données (shapefile et divers documents) de l'AFI de la RDC au 31 Décembre 2017.1Licence not specifiedalmost 2 years ago
- Cette carte reprend l'ensemble des informations du domaine forestier permanent (permis forestiers, aires protégées, réserves et zones tampons).1Licence not specifiedalmost 2 years ago
- Cette carte reprend l'ensemble des informations du domaine forestier permanent (permis forestiers, aires protégées, réserves et zones tampons). Les permis sont représentés selon l'état d'avancement de leur plan d'aménagement.1Licence not specifiedalmost 2 years ago
- Cette carte reprend l'ensemble des informations du domaine forestier permanent (permis forestiers, aires protégées, réserves et zones tampons). Les permis sont représentés selon l'état d'avancement de leur plan d'aménagement.1Licence not specifiedalmost 2 years ago
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- This layer shows the slope (in percent) of Kalimantan calculated from the elevation layer (90 meter resolution): ArcToolBox, Spatial Analyst Tools, Surface, Slope (Output measurement: percent_rise).Data was prepared by the World Resources Institute for use in the Suitability Mapper (2012).1Licence not specifiedalmost 2 years ago
- This layer shows the mean rainfall (in mm) for the period from 1989 to 2009 (1000 m resolution). Data was prepared by the World Resources Institute for use in the Suitability Mapper (2012).1Licence not specifiedalmost 2 years ago
- This layer shows the elevation (in meters) for Kalimantan. 90 meter resolution. Data was prepared by the World Resources Institute for use in the Suitability Mapper (2012).1Licence not specifiedalmost 2 years ago
- Limites des forêts, attribuées dans le domaine non permanent et gérées par les communautés1Licence not specifiedalmost 2 years ago
- This layer shows the soil drainage, based on result of a classification established from Kalimantan RePPProT dataon 'SL_drain1' field (1990, 1:250,000 scale) . This data was provided and processed by Daemeter Consulting and was prepared by the World Resources Institute for use in the Suitability Mapper (2012). Data separated into categories: stagnant; very poor; poor; moderately good; good; excessive; very excessive.1Licence not specifiedalmost 2 years ago
- This layer shows soil acidity, based on Kalimantan RePPProT data (1990, 1:250,000 scale). This data was provided and processed by Daemeter Consulting and was prepared by the World Resources Institute for use in the Suitability Mapper (2012). Data separated into categories of acidity: excessively acid (<4.0); extremely acid (4.0-4.5); very strongly acid (4.6-5.0); strongly acid (5.1-5.5); moderately acid (5.6-6.0); slightly acid (6.1-6.5); neutral (6.6-7.3).1Licence not specifiedalmost 2 years ago
- This layer shows the elevation (in meters) for Kalimantan. 90 meter resolution. Data was prepared by the World Resources Institute for use in the Suitability Mapper (2012).1Licence not specifiedalmost 2 years ago
- This archive contains all spatial data from the 2019 Interactive Forest Atlas of Cameroon.1Licence not specifiedalmost 2 years ago
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- This archive contains all spatial data from the 2017 Interactive Forest Atlas of Equatorial Guinea.1Licence not specifiedalmost 2 years ago
- This publication highlights three promising opportunitites for DRC's development. First, DRC's new government can take advantage of opportunities for long-term conservation and sustainable use of forests. Second, the development assistance community can play an important role in support of measures to conserve forests. Third, the government and the development assistance community can collaborate to get forest policy high on DRC's development agenda.1Licence not specifiedalmost 2 years ago
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- To avoid the worst climate impacts, global greenhouse gas (GHG) emissions must be slashed in half during the next decade and reach net-zero early in the second half of the century. Given this need, a growing number of Parties to the Paris Agreement are adopting net-zero emissions targets. This dataset contains the net-zero targets that have been communicated in a Party’s nationally determined contribution (NDC), long-term low GHG emissions development strategy (LTS), domestic law, policy, or high-level political pledge such as head of state commitment. The Paris Agreement requires participating countries to submit emission inventories that are based on activities within their territory. All the inventories on Climate Watch are based on this production-based accounting.1Licence not specifiedover 2 years ago
- Under the Paris Agreement, countries are invited to communicate “mid-century long-term low greenhouse gas emissions development strategies” (long-term strategies, or LTS). These strategies are central to the goal of limiting global warming to well below 2°C and to pursue efforts to limit the increase to 1.5°C, representing a significant opportunity for countries to lay out their vision for achieving a low-carbon economy by 2050 while also pursuing sustainable development. It is advantageous for countries to align their NDCs and long-term strategies for consistency and to avoid the lock-in of carbon-intensive behavior, technologies and policies. This dataset is published via Climate Watch, a free online platform designed to empower policymakers, researchers, media and other stakeholders with the open climate data, visualizations and resources they need to gather insights on national and global progress on climate change. All the inventories on Climate Watch are based on this production-based accounting.1Licence not specifiedover 2 years ago
- Under the Paris Agreement, nearly every nation made a commitment to tackle climate change and strengthen their efforts over time. To explore the content of these Nationally Determined Contributions (NDCs), search for key terms. Also, this dataset allows you to analyze and compare NDCs using over 150 structured indicators. Parties (representing 171 countries) have submitted their new or updated NDCs. This dataset is published via Climate Watch, a free online platform designed to empower policymakers, researchers, media and other stakeholders with the open climate data, visualizations and resources they need to gather insights on national and global progress on climate change. All the inventories on Climate Watch are based on this production-based accounting.1Licence not specifiedover 2 years ago
- Identify potential alignment between the targets, actions, policy measures, and needs in countries' Nationally Determined Contributions (NDCs) and the Sustainable Development Goals (SDGs) targets. The analysis covers NDCs submitted prior to May 2021. This dataset is published via Climate Watch, a free online platform designed to empower policymakers, researchers, media, and other stakeholders with the open climate data, visualizations, and resources they need to gather insights on national and global progress on climate change. All the inventories on Climate Watch are based on this production-based accounting.1Licence not specifiedover 2 years ago
- Emissions Pathways are transformational process that delivers long-term emissions reductions and sustainable development in collaboration with local communities, businesses and other key actors. This dataset is published via Climate Watch, a free online platform designed to empower policymakers, researchers, media and other stakeholders with the open climate data, visualizations and resources they need to gather insights on national and global progress on climate change. The Paris Agreement requires participating countries to submit emission inventories that are based on activities within their territory. All the inventories on Climate Watch are based on this production-based accounting.1Licence not specifiedover 2 years ago
- Human-caused greenhouse gas (GHG) emissions drive climate change. This dataset includes time series of emissions data by country using four measures that differ in scope and methodology: Climate Watch, PIK PRIMAP-hist, UNFCCC and GCP. The Paris Agreement requires participating countries to submit emission inventories that are based on activities within their territory. All the inventories on Climate Watch are based on this production-based accounting. This dataset is published via Climate Watch, a free online platform designed to empower policymakers, researchers, media and other stakeholders with the open climate data, visualizations and resources they need to gather insights on national and global progress on climate change.1Licence not specifiedover 2 years ago
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