Research output per year
Research output per year
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.
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.
| Date made available | 10 Sept 2024 |
|---|---|
| Publisher | Wageningen University & Research |
| Temporal coverage | 1019 - 2023 |
| Geographical coverage | Congo Basin |
Research output
- 1 Article
-
Monitoring road development in Congo Basin forests with multi-sensor satellite imagery and deep learning
Slagter, B., Fesenmyer, K., Hethcoat, M., Belair, E., Ellis, P., Kleinschroth, F., Pena Claros, M., Herold, M. & Reiche, J., 2024, In: Remote Sensing of Environment. 315, p. 114380 114380.Research output: Contribution to journal › Article › Academic › peer-review
Open Access2 Citations (Scopus)