Docs
Map Catalog Sources
Map Catalog Sources
Sources to datasets visualized in the map catalog
Map Catalog
LandOS integrates a wide range of global and regional geospatial datasets to support ecosystem assessment, carbon accounting, and project design. To ensure scientific transparency and reproducibility, this section provides full citations for every dataset displayed in the LandOS map catalog.
Users are encouraged to reference these datasets in project documentation, feasibility assessments, and reporting to align with methodological and verification standards.
Sources
| Category | Dataset | Reference |
|---|---|---|
| Biomass | Current Biomass | Walker, W. S., Gorelik, S. R., Cook-Patton, S. C., Baccini, A., Farina, M. K., Solvik, K. K., ... & Griscom, B. W. (2022). The global potential for increased storage of carbon on land. Proceedings of the National Academy of Sciences, 119(23), e2111312119. |
| Potential Biomass | Walker, W. S., Gorelik, S. R., Cook-Patton, S. C., Baccini, A., Farina, M. K., Solvik, K. K., ... & Griscom, B. W. (2022). The global potential for increased storage of carbon on land. Proceedings of the National Academy of Sciences, 119(23), e2111312119. | |
| Unrealized Biomass | Walker, W. S., Gorelik, S. R., Cook-Patton, S. C., Baccini, A., Farina, M. K., Solvik, K. K., ... & Griscom, B. W. (2022). The global potential for increased storage of carbon on land. Proceedings of the National Academy of Sciences, 119(23), e2111312119. | |
| Carbon Offset Project Boundaries | Karnik, A., Kilbride, J., Goodbody, T., Rachel, R., & Ayrey, E. (2024). A global database of nature-based carbon offset project boundaries [Data set]. Zenodo. https://doi.org/10.5281/zenodo.11459391 | |
| Canopy | ETH Canopy Height | Lang, Nico, Walter Jetz, Konrad Schindler, and Jan Dirk Wegner. "A high-resolution canopy height model of the Earth." arXiv preprint arXiv:2204.08322 (2022). |
| ETH Binary Tree Cover | Lang, Nico, Walter Jetz, Konrad Schindler, and Jan Dirk Wegner. "A high-resolution canopy height model of the Earth." arXiv preprint arXiv:2204.08322 (2022). | |
| ETH Canopy Height STD | Lang, Nico, Walter Jetz, Konrad Schindler, and Jan Dirk Wegner. "A high-resolution canopy height model of the Earth." arXiv preprint arXiv:2204.08322 (2022). | |
| Africa Tree Cover 2019 | Reiner, F., Brandt, M., Tong, X., Skole, D., Kariryaa, A., Ciais, P., ... & Fensholt, R. (2023). More than one quarter of Africa’s tree cover is found outside areas previously classified as forest. Nature Communications, 14(1), 2258. | |
| Amazon Canopy Height | Wagner, F.H., et al. (2025) Wall-to-wall Amazon forest height mapping with planet NICFI, Aerial LiDAR, and a U-Net regression model. Remote Sens Ecol Conserv. https://doi.org/10.1002/rse2.70041 | |
| Meta Canopy Height | Tolan, J., Yang, H.I., Nosarzewski, B., Couairon, G., Vo, H.V., Brandt, J., Spore, J., Majumdar, S., Haziza, D., Vamaraju, J. and Moutakanni, T., 2024. Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on aerial lidar. Remote Sensing of Environment, 300, p.113888. | |
| Meta Binary Tree Cover | Tolan, J., Yang, H.I., Nosarzewski, B., Couairon, G., Vo, H.V., Brandt, J., Spore, J., Majumdar, S., Haziza, D., Vamaraju, J. and Moutakanni, T., 2024. Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on aerial lidar. Remote Sensing of Environment, 300, p.113888. | |
| UMD Canopy Height | P. Potapov, X. Li, A. Hernandez-Serna, A. Tyukavina, M.C. Hansen, A. Kommareddy, A. Pickens, S. Turubanova, H. Tang, C. E. Silva, J. Armston, R. Dubayah, J. B. Blair, M. Hofton (2020). https://doi.org/10.1016/j.rse.2020.112165 | |
| UMD Binary Tree Cover | P. Potapov, X. Li, A. Hernandez-Serna, A. Tyukavina, M.C. Hansen, A. Kommareddy, A. Pickens, S. Turubanova, H. Tang, C. E. Silva, J. Armston, R. Dubayah, J. B. Blair, M. Hofton (2020). https://doi.org/10.1016/j.rse.2020.112165 | |
| Climate | Ecozone (FAO GEZ) | FAO, 2001. Global Ecological Zoning for the Global Forest Resources Assessment 2000. FAO FRA Working Paper 56, Rome, Italy. |
| Precipitation (WorldClim) | Fick, S.E. and R.J. Hijmans, 2017. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37 (12): 4302-4315. | |
| Evaporative Stress Index | Anderson, M. C., C. R. Hain, B. Wardlow, J. R. Mecikalski, and W. P. Kustas (2011), Evaluation of a drought index based on thermal remote sensing of evapotranspiration over the continental U.S., J. Climate, 24, 2025-2044. | |
| Human Impact | Crop Yield (MapSPAM) | SPAM2000 in You, L., S. Wood, U. Wood-Sichra, W. Wu. 2014. Generating global crop distribution maps: From census to grid. Agricultural Systems 127 (2014) 53–60 |
| Livestock Density (GLW4) | Gilbert, M., Nicolas, G., Cinardi, G., Van Boeckel, T. P., Vanwambeke, S. O., Wint, G. R. W., and Robinson, T. P.: Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010, Sci. Data, 5, 180227, https://doi.org/10.1038/sdata.2018.227, 2018. | |
| Logging Concessions | "Logging concessions." Accessed through Global Forest Watch. www.globalforestwatch.org. | |
| Mining Concessions | "Mining concessions." Accessed through Global Forest Watch. www.globalforestwatch.org. | |
| Palm Oil Concessions | "Oil palm concessions." Accessed through Global Forest Watch. www.globalforestwatch.org. | |
| Indigenous and Community Lands | LandMark, 2025. “Indigenous and Community Lands.” www.landmarkmap.org. Accessed from Global Forest Watch. www.globalforestwatch.org. | |
| Landcover | Dynamic World | Brown, C.F., Brumby, S.P., Guzder-Williams, B. et al. Dynamic World, Near real-time global 10 m land use land cover mapping. Sci Data 9, 251 (2022). doi:10.1038/s41597-022-01307-4 |
| ESA WorldCover 2021 | Zanaga, D., Van De Kerchove, R., Daems, D., De Keersmaecker, W., Brockmann, C., Kirches, G., Wevers, J., Cartus, O., Santoro, M., Fritz, S., Lesiv, M., Herold, M., Tsendbazar, N.E., Xu, P., Ramoino, F., Arino, O., 2022. ESA WorldCover 10 m 2021 v200. https://doi.org/10.5281/zenodo.7254221 | |
| ESRI 10m Annual Land Cover | Karra, Kontgis, et al. “Global land use/land cover with Sentinel-2 and deep learning.” IGARSS 2021-2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2021. | |
| Forest Loss Due to Fire | Tyukavina, A., Potapov, P., Hansen, M. C., Pickens, A. H., Stehman, S. V., Turubanova, S., ... & Harris, N. (2022). Global trends of forest loss due to fire from 2001 to 2019. Frontiers in Remote Sensing, 3, 825190. | |
| Global Natural & Planted Forests 2021 | Xiao, Y., Wang, Q., & Zhang, H. K. (2024). Global Natural and Planted Forests Mapping at Fine Spatial Resolution of 30 m. Journal of Remote Sensing, 4, 0204. | |
| GWL FCS30 Wetlands | Lehner, B., Anand, M., Fluet-Chouinard, E., Tan, F., Aires, F., Allen, G. H., Bousquet, P., Canadell, J. G., Davidson, N., Ding, M., Finlayson, C. M., Gumbricht, T., Hilarides, L., Hugelius, G., Jackson, R. B., Korver, M. C., Liu, L., McIntyre, P. B., Nagy, S., Olefeldt, D., Pavelsky, T. M., Pekel, J.-F., Poulter, B., Prigent, C., Wang, J., Worthington, T. A., Yamazaki, D., Zhang, X., and Thieme, M.: Mapping the world's inland surface waters: an upgrade to the Global Lakes and Wetlands Database (GLWD v2), Earth Syst. Sci. Data, 17, 2277–2329, https://doi.org/10.5194/essd-17-2277-2025, 2025. | |
| Hansen Deforestation Year | Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342 (15 November): 850-53. Data available on-line from: https://glad.earthengine.app/view/global-forest-change. | |
| Hansen Tree Cover 2000 | Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342 (15 November): 850-53. Data available on-line from: https://glad.earthengine.app/view/global-forest-change. | |
| MapBiomass Deforestation Year | MapBiomas Project - Collection of the Annual Land Use Land Cover Maps of Brazil | |
| MapBiomass Forest Cover | MapBiomas Project - Collection of the Annual Land Use Land Cover Maps of Brazil | |
| SBTN Natural Cover Classification | Mazur, E., Sims, M., et al., SBTN Natural Lands Map v1.1, 2025 | |
| SBTN Natural Lands | Mazur, E., Sims, M., et al., SBTN Natural Lands Map v1.1, 2025 | |
| Satellite | Landsat 8 False Color | Earth Resources Observation and Science (EROS) Center. (2020). Landsat 8-9 Operational Land Imager / Thermal Infrared Sensor Level-2, Collection 2 [dataset]. U.S. Geological Survey. https://doi.org/10.5066/P9OGBGM6. |
| Landsat 8 RGB | Earth Resources Observation and Science (EROS) Center. (2020). Landsat 8-9 Operational Land Imager / Thermal Infrared Sensor Level-2, Collection 2 [dataset]. U.S. Geological Survey. https://doi.org/10.5066/P9OGBGM6. | |
| Landsat 9 False Color | Earth Resources Observation and Science (EROS) Center. (2020). Landsat 8-9 Operational Land Imager / Thermal Infrared Sensor Level-2, Collection 2 [dataset]. U.S. Geological Survey. https://doi.org/10.5066/P9OGBGM6. | |
| Landsat 9 RGB | Earth Resources Observation and Science (EROS) Center. (2020). Landsat 8-9 Operational Land Imager / Thermal Infrared Sensor Level-2, Collection 2 [dataset]. U.S. Geological Survey. https://doi.org/10.5066/P9OGBGM6. | |
| Sentinel-2 False Color | Copernicus Sentinel data for Sentinel data | |
| Sentinel-2 RGB | Copernicus Sentinel data for Sentinel data | |
| Topography | Elevation | Jarvis, A., H.I. Reuter, A. Nelson, E. Guevara, 2008, Hole-filled SRTM for the globe Version 4, available from the CGIAR-CSI SRTM 90m Database (http://srtm.csi.cgiar.org). |
| Slope | Jarvis, A., H.I. Reuter, A. Nelson, E. Guevara, 2008, Hole-filled SRTM for the globe Version 4, available from the CGIAR-CSI SRTM 90m Database (http://srtm.csi.cgiar.org). |