RADD Forest Disturbance Alert
Radar satellite imagery from the European Space Agency’s Sentinel-1 mission is used to map new disturbances in primary humid tropical forest at 10 m spatial scale and in near real-time.
Sentinel-1’s cloud-penetrating radar provides gap-free observations for the tropics consistently every 6 to 12 days. In the densely cloud covered tropics, this represents a major advantage for the rapid detection of small-scale forest disturbances such as subsistence agriculture and selective logging. The RADD (RAdar for Detecting Deforestation) alerts contribute to the World Resources Institute’s Global Forest Watch initiative in providing timely and accurate information to support a wide range of stakeholders in sustainable forest management and law enforcement activities against illegal deforestation. The RADD alerts are implemented in Google Earth Engine. RADD alerts are available openly via Google Earth Engine and the Global Forest Watch platform.
Data visualisation in Google Earth Engine
https://gena.users.earthengine.app/view/raddalert
Data access in Google Earth Engine
Image collection id: ee.ImageCollection('projects/radar-wur/raddalert/v1')
GEE script to access latest RADD alerts: https://code.earthengine.google.com/6efa1be38aecac3cf0ab28a9781f2080
Dataset reference
Reiche J, Mullissa A, Slagter B, Gou Y, Tsendbazar N, Odongo-Braun C, Vollrath A, Weisse M, 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/abd0a8.
Disturbance detection algorithm
- A new forest disturbance alert is triggered based on a single observation from the latest Sentinel-1 C-band radar image. Subsequent observations are used to iteratively update the forest disturbance probability, increase confidence and confirm or reject the alert. Alerts are confirmed within a maximum 90-day period if the forest disturbance probability is above 97.5% (high confidence alerts). Unconfirmed alerts (low confidence alerts) are provided for forest disturbance probabilities above 85%. The date of the alert is set to the date of the image that first triggered the alert.
- The product has a minimum mapping unit of 0.1 ha.
- Forest disturbances are mapped only within the primary humid tropical forest mask from Turubanova et al (2018) with 2001-2018 forest loss (Hansen et al 2013) and mangrove (Bunting et al 2018) removed.
- Forest disturbance is defined as the complete or partial removal of tree cover within a 10 m Sentinel-1 pixel. Complete tree cover removal is associated with stand-replacement disturbance at the Sentinel-1 pixel scale, while partial removal mainly represents disturbances associated with boundary pixels and selective logging. Human-induced disturbances (e.g. selective logging, clearing for agriculture or mining) are not separated from natural forest disturbances (e.g. windthrows, landslides, or meandering rivers).
- For full description of the methodology and validation results refer to Reiche et al (accepted), ERL.
Current geographic coverage
Primary humid tropical forest of Africa (25 countries).
Versions and updates
v.0 (2020-06-01)
- as described in Reiche et al., 2021 (ERL)
v.1 (2021-01-01)
- minimum mapping unit reduced to 0.1 ha
- improved forest baseline mask now based on the primary humid tropical forest mask from Turubanova et al (2018) with 2001-2018 forest loss (Hansen et al 2013) and mangrove (Bunting et al 2018) removed
- improved detection in swamp forests
- Reiche et al. (2021), ERL
Related research and publications
Credit
Wageningen University, in collaboration with World Resources Institute‘s Global Forest Watch program, Google, European Space Agency, University of Maryland and Deltares (2020).