This dataset has been archived, and we will no longer be updating or maintaining it. We recommend using this dataset as a replacement.
This data set was generated by Aberystwyth University and soloEO within the framework of the Global Mangrove Watch (GMW) project, which is a part of the Japan Aerospace Exploration Agency’s Kyoto and Carbon Initiative and the Mangrove Capital Africa Programme coordinated by Wetlands International and financed by DOB Ecology. The map (v1.2) depicts the global extent of mangrove forests for the year 2010, derived by Random Forest Classification of both L-band radar (ALOS PALSAR) and optical (Landsat-5, -7) data. All satellite data and software used to derive the GMW mangrove maps are available in the public domain. Approximately 15,000 Landsat scenes and 1,500 ALOS PALSAR (1 x 1 degree) mosaic tiles were used to create mosaics of optical and radar data covering the tropical, subtropical, and temperate coastlines of the Americas, Africa, Asia, and Oceania where mangroves occur. The classification was confined using a mangrove habitat mask, which defined regions where mangrove ecosystems can be expected to exist. The mangrove habitat definition was based on geographical parameters such as latitude, elevation, and distance from ocean water. Training for the habitat mask and classification of the 2010 mangrove mask was based on a randomly sample of 38 million points using the mangrove masks (for the year 2000) of Giri et al. (2011) and Spalding et al. (2010) and the water occurrence layer defined by Pekel et al. (2017). Resource Watch shows only a subset of the data set. For access to the full data set and additional information, see the Learn More link.
Global Distribution of Mangroves USGS, Version 1.3
The Landsat-7 ETM+ scanline error affects the classification in certain areas, resulting in striping artefacts in the data. Classification accuracy was assessed with over 53,800 randomly sampled points across 20 randomly selected regions. Overall accuracy was 95.25%, while User’s and Producer’s accuracies for the mangrove class were estimated at 97.5% and 94.0%, respectively. Users should be aware that this is a global-scale data set, generated with a single methodology applied over all regions. As such, the accuracy of the map may vary between locations. Factors such as satellite data availability (due to clouds, cloud shadows, and Landsat-7 ETM+ scanline error), mangrove species composition and level of degradation all influence the accuracy. The mangrove seaward border is generally more accurately defined than the landward side, where the distinction between mangrove and certain terrestrial vegetation types (e.g., tropical rainforest) can be lower. Areas known to be missing in this version (v1.2) of the data set include Bermuda (UK); Europa Island (France); Fiji, east of longitude 180°E; Maldives; Nicobar Islands (India); Guam and Saipan (United States); Peru, south of latitude 4°S; Kosrae island (Micronesia); and Wallis and Futuna Islands (France).
Giri C, Ochieng E, Tieszen LL, Zhu Z, Singh A, Loveland T, Masek J, Duke N (2011). "Status and distribution of mangrove forests of the world using earth observation satellite data (version 1.3, updated by UNEP-WCMC)." Global Ecology and Biogeography 20: 154-159. doi: 10.1111/j.1466-8238.2010.00584.x. http://data.unep-wcmc.org/datasets/4. Accessed through Resource Watch, (date). www.resourcewatch.org.