Forest roads (Congo Basin)

Description Road development in the Congo Basin forest is continuously monitored from 2019 onwards in high spatial and temporal detail. A deep learning method is applied to 10 m scale Sentinel-1 and Sentinel-2 imagery for automated road detections on a monthly basis. This version presents 5 years of road development (46,311 km) from 2019-2023. The data is composed of line features distributed in .shp and .geojson formats. The following attributes are stored for the line features: NetworkID: A unique ID for each connected road network. SegLenM: The length of the road segment (in meters). NetLenM: The length of the connected road network (in meters). Month: The road segment opening month. Year: The road segment opening year. MonthNum: The road segment opening month, depicted as a continuing count since the start of monitoring (e.g. 13 = January 2020). This attribute can be used for smooth and continuous temporal analyses or visualizations. Additional information More information about the forest road mapping project can be found at: https://wur.eu/forest-roads Continuously updated road maps can be interactively viewed at: https://nrtwur.users.earthengine.app/view/forest-roads The dataset can be accessed in Google Earth Engine at: ee.FeatureCollection('projects/wurnrt-loggingroads/assets/distribution/forestroads_afr_2019-01_2023-12') The scientific paper (Slagter et al., 2024) describing the methods to produce this dataset can be found at: https://doi.org/10.1016/j.rse.2024.114380 Citation Please cite the following when referring to this dataset: Slagter B., Fesenmyer K., Hethcoat M., Belair E., Ellis P., Kleinschroth F., Peña-Claros M., Herold M., Reiche J. (2024). Monitoring road development in Congo Basin forests with multi-sensor satellite imagery and deep learning. Remote Sensing of Environment