NEO
L o a d i n g
NEO (https://www.neo.nl/home-int/) is a leading company in the Earth Observation (EO) business based in the Netherlands. Established in 1996, NEO has 25 years track record in providing information services starting from the changes in our habitat. From the changes we detect, we built value-added services supporting both public and private organizations. NEO's EO-based solutions cover a wide range of applications including but not limited to: Energy and Asset management, Infrastructure monitoring, Environmental monitoring, Agriculture monitoring, as well as Land and water. With the strong expertise in geo-information/remote sensing and the patented and certified solution (ISO9001 and ISO27001) SignalEyes® for monitoring with earth observation data, NEO translates geodata into value-added services for the clients. NEO serves over 250 customers in The Netherlands, within the European Union and internationally. Its services empower our customers to make better decisions, reduce costs, increase safety and prevent errors, to comply with regulations and to manage our environment better.
Available DatasetsShowing 31 of 31 results
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Georgia. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedover 1 year ago
- This is the training dataset for power tower deep learning model development. The dataset contains 50cm resolution Mapbox image tiles (Maxar imagery) as well as the power tower location presence in the imagery as geojson file. Both the geographic coordinates and the pixel coordinates of the power towers have been incorporated. The dataset covers pilot areas in west coast of Liberia, Yemen and India.1Licence not specifiedover 1 year ago
- This dataset is about the training dataset used in the power tower deep learning model development. The training dataset includes the Mapbox imagery tiles and the power tower labels. The geographic coordinates and pixel coordinates of the power tower on the imagery have been incorporated in the dataset. This training dataset covers areas in Liberia, India, Yemen, Domincan Republic and Bangladesh.1Licence not specifiedover 1 year ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Karachi. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedover 1 year ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in South Africa. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedover 1 year ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Dominican Republic. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedover 1 year ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Lagos state. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedover 1 year ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Saint Lucia. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 2 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Maldives. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 2 years ago
- This dataset contains solar rooftop potential data (installable capacity, estimated electricity generation) for a sample area of interest in Mexico City. The data was gathered by extracting building rooftop footprint polygons from very high resolution stereosatelite imagery. Detailed methodology is available upon specific request.1Licence not specifiedalmost 2 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in SintMaarten Island. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 2 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in SintMaarten Island. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 2 years ago
- This dataset gives a full overview of the current (up to 2022) transmission grid infrastructure of Dominican Republic including power plants, power stations, power towers and power lines with attributes such as length, assumed voltage level etc.. The dataset was produced by using smart tracing algorithms developed by NEO in house which uses grid probability map for determining areas to look for power towers and a deep learning model for power tower automatic detection. The power plants and (sub)stations collected from open source (Global power plant database, Global dam dataset, OpenStreetMap and Energydata.info etc.) as well as some existing power towers from OpenStreetMap dataset were used as starting point for smart tracing alogirthm, and Mapbox 50cm Very High Resolution imagery was used as input for detecting power towers using the trained deep learning model. The OSM points are also included into the dataset to make best use of existing dataset to achieve complete grid mapping coverage as much as possible in an efficient and effective way. The probability map and path finder is adapted based on Global Grid Finder approach :https://gridfinder.org/ Global power plant database: https://datasets.wri.org/dataset/globalpowerplantdatabase Global dam dataset: http://globaldamwatch.org/data/1Licence not specifiedalmost 2 years ago
- This dataset gives a full overview of the current (up to 2022) transmission grid infrastructure of Liberia including power plants, power stations, power towers and power lines with attributes such as length, assumed voltage level etc.. The dataset was produced by using smart tracing algorithms developed by NEO in house which uses grid probability map for determining areas to look for power towers and a deep learning model for power tower automatic detection. The power plants and (sub)stations collected from open source (Global power plant database, Global dam dataset, OpenStreetMap and Energydata.info etc.) as well as some existing power towers from OpenStreetMap dataset were used as starting point for smart tracing alogirthm, and Mapbox 50cm Very High Resolution imagery was used as input for detecting power towers using the trained deep learning model. The OSM points are also included into the dataset to make best use of existing dataset to achieve complete grid mapping coverage as much as possible in an efficient and effective way. The probability map and path finder is adapted based on Global Grid Finder approach :https://gridfinder.org/ Global power plant database: https://datasets.wri.org/dataset/globalpowerplantdatabase Global dam dataset: http://globaldamwatch.org/data/1Licence not specifiedalmost 2 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Izmir. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 3 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Accra. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 3 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Saint Vincent and the Grenadines. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 3 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Colombo. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 3 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Dar Es Salaam. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 3 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Dhaka. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 3 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Almaty. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 3 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Karachi. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 3 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Manila. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 3 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Samarkand. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 3 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Dominica. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 3 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Antigua. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 3 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Addis Ababa. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 3 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Grenada Island. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 3 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Lagos. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 3 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Beirut. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 3 years ago
- This dataset contains solar rooftop potential data (suitable rooftop area, installable capacity, estimated yearly electricity generation, and building type ) at individual building structure level for a sample area of interest in Nairobi. The data was gathered by extracting building rooftop footprint polygons from very high-resolution satellite stereo imagery of 0.5m resolution. The rooftop angle, obstruction, and shading were taken into account during suitable area calculation. The results can be aggregated by different sectors or administrative units for further analysis, which is useful for planning and decision making. Detailed methodology is available upon specific request.1Licence not specifiedalmost 3 years ago
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