NASA Carbon Monitoring System (CMS) Estimated Global Mangroves in the 2000s

The Global Mangrove Forests Distribution, 2000 data set is a compilation of the extent of mangroves forests from the Global Land Survey and the Landsat archive with hybrid supervised and unsupervised digital image classification techniques. The data are available at 30-m spatial resolution. The total area of mangroves in the year 2000 was estimated at 137,760 km2 in 118 countries and territories in the tropical and subtropical regions of the world. **Data creation:** 2025-12-03 **Supplemental Information:** Platforms: LANDSAT-5 Instruments: TM Spatial Extent: N: 90 S: -90 E: 180 W: -180 Spatial Resolution: 30 Decimal Degrees x 30 Decimal Degrees Geographic Region: GLOBAL Coordinate System: CARTESIAN Granule Spatial Representation: CARTESIAN Temporal Extent: 2000-01-01 to 2000-12-31 Data Partner: Earth Science Data Information System (ESDIS) Concept ID: C3550194192-ESDIS Data State: COMPLETE Number of Files/Granules: 111 Processing Level: 4 Published: 2005-12-31 Updated: 2005-12-31 Science Keywords: Mangroves , Sustainability , Climate Adaptation **Citation:** Giri, C., Ochieng, E., Tieszen, L. L., Zhu, Z., Singh, A., Loveland, T., Masek, J., & Duke, N. (2013). Global Mangrove Forests Distribution, 2000 (Version 1.00) [Data set]. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/H4J67DW8 Date Accessed: 2025-12-03 **Contact points:** Resource Contact: [EARTH DATA](mailto:https://forum.earthdata.nasa.gov/viewforum.php?f=7) **Data lineage:** Data quality information not available **Resource constraints:** This work is made available under the license Creative Commons Zero (CC0). Find more information on the license here . **Online resources:** Global Mangrove Forests Distribution, 2000

This dataset was generated within the framework of the Global Mangrove Watch (GMW), an initiative convened by Aberystwyth University, soloEO, The Nature Conservancy and Wetlands International. The larger dataset (v3.0) depicts the global extent of mangrove forests for the years 1996, 2007-2010, and 2015-2020, derived by L-band Synthetic Aperture Radar (SAR) global mosaic datasets from the Japan Aerospace Exploration Agency (JAXA), thus developing a long-term time-series of global mangrove extent and change. The study used a map-to-image approach to change detection where the baseline map (GMW v2.5) was updated using thresholding and a contextual mangrove change mask. 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. The habitat mask was initially developed in GMW v2.0 and has been revised in subsequent versions. Global coverage of mangroves for 2020

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 (JAXA) Kyoto & Carbon Initiative and the Mangrove Capital Africa Programme coordinated by Wetlands International and financed by DOB Ecology. The map (v2.0) depicts the global extent of mangrove forests for the year 2010, derived by Random Forest Classification of a combination of L-band radar (ALOS PALSAR) and optical (Landsat-5, -7) satellite 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 optical and radar image composites covering the coastlines along the tropical and sub-tropical coastlines in the Americas, Africa, Asia and Oceania. 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 randomly sampling 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). The data set is available for download at http://data.unep-wcmc.org/datasets/45 Global coverage of mangroves for select years from 1996 to 2016

- This is a global, wall-to-wall map of aboveground biomass (AGB) at approximately 30-meter resolution. This data product expands on the methodology presented in Baccini et al. (2012) to generate a global map of aboveground live woody biomass (AGB) density (megagrams biomass per ha) at 0.00025-degree (approximately 30-meter) resolution for the year 2000. Aboveground biomass was estimated using a multi-step process of calculating AGB at more than seven hundred thousand points with LiDAR with regional allometric equations, then using those to train a wall-to-wall model based on Landsat imagery. Pixels without tree canopy were assigned a biomass density of 0 Mg/ha. Additional information on the creation of this map can be found in Harris et al. 2021.  - Aboveground biomass is available for download in two different units: 1) megagrams AGB per hectare, and 2) megagrams AGB per pixel. The first is appropriate for visualizing (mapping) AGB and estimating average AGB density in an area of interest because it represents the density of AGB per hectare. The second is appropriate for calculating the total aboveground biomass stock in an area of interest because the values of the pixels in the AOI can be summed to obtain the total AGB stock in that area. The values in the latter were calculated by adjusting the AGB per hectare by the size of each pixel, which varies by latitude.  Shows aboveground live woody biomass density in the year 2000

A new, 30-m spatial resolution global forest canopy height map was developed through the integration of the Global Ecosystem Dynamics Investigation (GEDI) lidar forest structure measurements and Landsat analysis-ready data time-series. The NASA GEDI is a spaceborne lidar instrument operating onboard the International Space Station since April 2019. It provides point-based measurements of vegetation structure, including forest canopy height between 52°N and 52°S globally. The Global Land Analysis and Discover team at the University of Maryland (UMD GLAD) integrated the GEDI data available to date (April-October 2019) with the year 2019 Landsat analysis-ready time-series data (Landsat ARD). The GEDI RH95 (relative height at 95%) metric was used to calibrate the model. The Landsat multi-temporal metrics that represent the surface phenology serve as the independent variables for global forest height modeling. The “moving window” locally calibrated and applied regression tree ensemble model was implemented to ensure high quality of forest height prediction and global map consistency. The model was extrapolated in the boreal regions (beyond the GEDI data range) to create the global forest height prototype map. Show the height of global forest canopy in the years 2000 and 2020.

This dataset contains annual, 100m-resolution above ground biomass (AGB) estimates from CTrees, a NASA-affiliated forest-carbon monitoring organization, clipped to this country's boundary from CTrees' global AGB raster. Pixel values are stored as int16, scaled x10 relative to the true value in megagrams per hectare (Mg/ha) -- divide by 10 to get Mg/ha. See the caveats field and resource description for details on how this scale factor is recorded and why it isn't applied automatically by most tools.