Tropical and Subtropical Peatland Distribution

- This data set delineates peatlands and other organic soils globally using five layers. Miettinen et al. 2016 was used for Indonesia and Malaysia, Hastie et al. 2022 was used in lowland Peru, Crezee et al. 2022 was used in the Congo basin, and Gumbricht et al. 2017 was used for all land between 40 degrees north and 60 degrees south (including areas covered by the aforementioned data sets). Xu et al. 2018 was used for all land above 40 degrees north. Miettinen et al. 2016 and Xu et al. 2018 were rasterized to ~30x30 m resolution while Gumbricht et al. 2017, Crezee et al. 2022, and Hastie et al. 2022 were resampled from their native resolutions to ~30x30 m resolution in order to align with the Global Forest Change maps from Hansen et al. 2013. All layers were combined, i.e. Gumbricht et al. 2017 was also used in Indonesia/Malaysia, the Peruvian Amazon, and the Congo basin. All data sources have different methods for peatland delineation, which are described in their original publications. - Crezee, B. et al. Mapping peat thickness and carbon stocks of the central Congo Basin using field data. Nature Geoscience 15: 639-644 (2022). https://www.nature.com/articles/s41561-022-00966-7. Data downloaded from https://congopeat.net/maps/, using classes 4 and 5 only (peat classes). - Gumbricht, T. et al. An expert system model for mapping tropical wetlands and peatlands reveals South America as the largest contributor. Glob. Change Biol. 23, 3581–3599 (2017). https://onlinelibrary.wiley.com/doi/full/10.1111/gcb.13689 - Hastie, A. et al. Risks to carbon storage from land-use change revealed by peat thickness maps of Peru. Nature Geoscience 15: 369-374 (2022). https://www.nature.com/articles/s41561-022-00923-4 - Miettinen, J., Shi, C. & Liew, S. C. Land cover distribution in the peatlands of Peninsular Malaysia, Sumatra and Borneo in 2015 with changes since 1990. Glob. Ecol. Conserv. 6, 67– 78 (2016). https://www.sciencedirect.com/science/article/pii/S2351989415300470 - Xu et al. PEATMAP: Refining estimates of global peatland distribution based on a meta-analysis. CATENA 160: 134-140 (2018). https://www.sciencedirect.com/science/article/pii/S0341816217303004 Delineates extent of peatlands

Model outputs were updated on Dec 20, 2017. This project used a machine learning data-driven model to predict the distribution of soil carbon under mangrove forests globally. Specifically this dataset contains: 1) a compilation of georeferenced and harmonized soil profile data under mangroves compiled from literature, reports and unpublished contributions 2) global mosaics of soil carbon stocks to 1m and 2m depths produced at 100 m resolution 3) tiled predictions of soil carbon stocks produced at 30 m resolution 4) shape file containing the tiling system 5) shape file containing country boundaries used for calculating national level statistics. For detailed methodologies, please see the scientific paper (https://doi.org/10.1088/1748-9326/aabe1c).

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

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

Soil organic carbon stock in t/ha for 0-30 cm depth interval. Predictions were derived using a digital soil mapping approach based on Quantile Random Forest, drawing on a global compilation of soil profile data and environmental layers. To visualize these layers please use www.soilgrids.org.

Soil organic carbon content (fine earth fraction) in dg/kg at 6 standard depths. Predictions were derived using a digital soil mapping approach based on Quantile Random Forest, drawing on a global compilation of soil profile data and environmental layers. To visualize these layers please use www.soilgrids.org.