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logging roads, small-scale agriculture) are typically detected in a timely manner as forest edges are relatively straightforward to detect using short wavelength C-band radar.

windthrows, landslides, or meandering rivers). selective logging, clearing for agriculture or mining) are not separated from natural forest disturbances (e.g.

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For full description of the methodology and validation results refer to Reiche et al (accepted), ERL.

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.

Forest disturbance is defined as the complete or partial removal of tree cover within a 10 m Sentinel-1 pixel.

Forest disturbances are mapped only within the primary humid tropical forest mask from Turubanova et al (2018) with annual (Africa: 2001 - 2018 Other geographies: 2001-2019) forest loss ( Hansen et al 2013) and mangrove ( Bunting et al 2018) removed.

The product has a minimum mapping unit of 0.1 ha.

The date of the alert is set to the date of the image that first triggered the alert. Unconfirmed alerts (low confidence alerts) are provided for forest disturbance probabilities above 85%. Alerts are confirmed within a maximum 90-day period if the forest disturbance probability is above 97.5% (high confidence alerts).

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Subsequent observations are used to iteratively update the forest disturbance probability, increase confidence and confirm or reject the alert.

A new forest disturbance alert is triggered based on a single observation from the latest Sentinel-1 C-band radar image.

ESA plans an early launch of Sentinel-1C) The coverage for RADD alerts (humid tropics)Īlmost back to normal with a minor gap in the norther Amazon. (Note: ESA has expanded the coverage of Sentinel-1A after the Sentinel-1B anomaly in early 2022.

Primary humid tropical forest of South America (13 countries), Africa (25 countries), insular Southeast Asia (5 countries) and Pacific (1 country). 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.

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GEE script to download RADD alerts as GeoTIFF to GoogleDrive:.GEE script to access latest RADD alerts:.Image collection id: ee.ImageCollection('projects/radar-wur/raddalert/v1').RADD alerts are available openly via Google Earth Engine, the Global Forest Watch platform, SEPAL.io and .ĭata visualisation in Google Earth Engine The RADD alerts are implemented in Google Earth Engine. 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. Sentinel-1’s cloud-penetrating radar provides gap-free observations for the tropics consistently every 6 to 12 days.