Mangroves are found globally throughout tropical and sub-tropical inter-tidal coastlines. These highly biodiverse and carbon-dense ecosystems have multi-faceted value, providing critical goods and services to millions living in coastal communities and making significant contributions to global climate change mitigation through carbon sequestration and storage. Despite their many values, mangrove loss continues to be widespread in many regions due primarily to anthropogenic activities. Accessible, intuitive tools that enable coastal managers to map and monitor mangrove cover are needed to stem this loss. Remotely sensed data have a proven record for successfully mapping and monitoring mangroves, but conventional methods are limited by imagery availability, computing resources and accessibility. In addition, the variable tidal levels in mangroves presents a unique mapping challenge, particularly over geographically large extents. Here we present a new tool—the Google Earth Engine Mangrove Mapping Methodology (GEEMMM)—an intuitive, accessible and replicable approach which caters to a wide audience of non-specialist coastal managers and decision makers. The GEEMMM was developed based on a thorough review and incorporation of relevant mangrove remote sensing literature and harnesses the power of cloud computing including a simplified image-based tidal calibration approach. We demonstrate the tool for all of coastal Myanmar (Burma)—a global mangrove loss hotspot—including an assessment of multi-date mapping and dynamics outputs and a comparison of GEEMMM results to existing studies. Results—including both quantitative and qualitative accuracy assessments and comparisons to existing studies—indicate that the GEEMMM provides an accessible approach to map and monitor mangrove ecosystems anywhere within their global distribution.

Mangroves inhabit highly productive inter-tidal ecosystems in >120 countries in the tropics and subtropics providing critical goods and services to coastal communities and contributing to global climate change mitigation owing to substantial carbon stocks. Despite their importance, global mangrove distribution continues to decline primarily due to anthropogenic drivers which vary by region/country. South Asia, Southeast Asia and Asia-Pacific contain approximately 46% of the world’s mangrove ecosystems, including the most biodiverse mangrove forests. This region also exhibits the highest global rates of mangrove loss. Remotely sensed data provides timely and accurate information on mangrove distribution and dynamics critical for targeting loss hotspots and guiding intervention. This report inventories, describes and compares all known single- and multi-date remotely sensed datasets with regional coverage and provides areal mangrove extents by country. Multi-date datasets were used to estimate dynamics and identify loss hotspots (i.e., countries that exhibit greatest proportional loss). Results indicate Myanmar is the primary mangrove loss hotspot, exhibiting 35% loss from 1975–2005 and 28% between 2000–2014. Rates of loss in Myanmar were four times the global average from 2000–2012. The Philippines is additionally identified as a loss hotspot, with secondary hotspots including Malaysia, Cambodia and Indonesia. This information helps inform and guide mangrove conservation, restoration and managed-use within the region.

Mangrove ecosystems help mitigate climate change, are highly biodiverse, and provide critical goods and services to coastal communities. Despite their importance, anthropogenic activities are rapidly degrading and deforesting mangroves world-wide. Madagascar contains 2% of the world’s mangroves, many of which have undergone or are starting to exhibit signs of widespread degradation and deforestation. Remotely sensed data can be used to quantify mangrove loss and characterize remaining distributions, providing detailed, accurate, timely and updateable information. We use USGS maps produced from Landsat data to calculate nation-wide dynamics for Madagascar’s mangroves from 1990 to 2010, and examine change more closely by partitioning the national distribution in to primary (i.e., >1000 ha) ecosystems; with focus on four Areas of Interest (AOIs): Ambaro-Ambanja Bays (AAB), Mahajamba Bay (MHJ), Tsiribihina Manombolo Delta (TMD) and Bay des Assassins (BdA). Results indicate a nation–wide net-loss of 21% (i.e., 57,359 ha) from 1990 to 2010, with dynamics varying considerably among primary mangrove ecosystems. Given the limitations of national-level maps for certain localized applications (e.g., carbon stock inventories), building on two previous studies for AAB and MHJ, we employ Landsat data to produce detailed, contemporary mangrove maps for TMD and BdA. These contemporary, AOI-specific maps provide improved detail and accuracy over the USGS national-level maps, and are being applied to conservation and restoration initiatives through the Blue Ventures’ Blue Forests programme and WWF Madagascar West Indian Ocean Programme Office’s work in the region.

Mangroves are found throughout the tropics, providing critical ecosystem goods and services to coastal communities and supporting rich biodiversity. Globally, mangroves are being rapidly degraded and deforested at rates exceeding loss in many tropical inland forests. Madagascar contains around 2% of the global distribution, >20% of which has been deforested since 1990, primarily from over-harvest for forest products and conversion for agriculture and aquaculture. While historically not prominent, mangrove loss in Madagascar’s Mahajamba Bay is increasing. Here, we focus on Mahajamba Bay, presenting long-term dynamics calculated using United States Geological Survey (USGS) national-level mangrove maps contextualized with socio-economic research and ground observations, and the results of contemporary (circa 2011) mapping of dominant mangrove types. The analysis of the USGS data indicated 1050 hectares (3.8%) lost from 2000 to 2010, which socio-economic research suggests is increasingly driven by commercial timber extraction. Contemporary mapping results permitted stratified sampling based on spectrally distinct and ecologically meaningful mangrove types, allowing for the first-ever vegetation carbon stock estimates for Mahajamba Bay. The overall mean carbon stock across all mangrove classes was estimated to be 100.97 ± 10.49 Mg C ha⁻¹. High stature closed-canopy mangroves had the highest average carbon stock estimate (i.e., 166.82 ± 15.28 Mg C ha⁻¹). These estimates are comparable to other published values in Madagascar and elsewhere in the Western Indian Ocean and demonstrate the ecological variability of Mahajamba Bay’s mangroves and their value towards climate change mitigation.

Generic global conservation targets lack the ambition required for certain habitats of critical value for biodiversity and human well-being. Developing more challenging targets for such habitats may offer a solution. Mangrove forests provide an example: any and all future loss will have negative repercussions, while many impacts could be reversed through extensive restoration. The Global Mangrove Alliance, an international grouping of 100 civil society and academic partners, has set goals to halt anthropogenic losses, accelerate restoration and greatly enhance protection by 2030. Using global-scale data, we estimate that achieving these goals will avoid losses of some 1500 km ² ; restore some 4000 km ² ; and secure an additional 36 000 km ² of mangroves under effective and equitable protection. Multiple benefits will follow, and we present values for carbon storage gains and avoided losses. Global datasets can guide broad approaches, while quantifying the challenges and benefits provides inspiration and impetus for change.