The following 15 publications cited the product GEDI L4A Footprint Level Aboveground Biomass Density, Version 2.1.
Year | Citation |
---|---|
2024 | Bourgoin, C., G. Ceccherini, M. Girardello, C. Vancutsem, V. Avitabile, P.S.A. Beck, R. Beuchle, L. Blanc, G. Duveiller, M. Migliavacca, G. Vieilledent, A. Cescatti, and F. Achard. 2024. Human degradation of tropical moist forests is greater than previously estimated. Nature. 631(8021):570-576. https://doi.org/10.1038/s41586-024-07629-0 |
2024 | Burns, P., C.R. Hakkenberg, and S.J. Goetz. 2024. Multi-resolution gridded maps of vegetation structure from GEDI. Scientific Data. 11(1). https://doi.org/10.1038/s41597-024-03668-4 |
2024 | Campos, M.S., L.J. Anjos, E.B.d. Souza, F.G.S. Bezerra, A.M.M.d. Lima, D.R. Galbraith, and M. Adami. 2024. Prioritizing Amazon Forest conservation: Assessing potential biomass under climate change. Global Ecology and Conservation. 54:e03106. https://doi.org/10.1016/j.gecco.2024.e03106 |
2024 | Demol, M., N. Aguilar-Amuchastegui, G. Bernotaite, M. Disney, L. Duncanson, E. Elmendorp, A. Espejo, A. Furey, S. Hancock, J. Hansen, H. Horsley, S. Langa, M. Liang, A. Locke, V. Manjate, F. Mapanga, H. Omidvar, A. Parsons, E. Peneva-Reed, T. Perry, B.L. Puma Vilca, P. Rodríguez-Veiga, C. Sutcliffe, R. Upham, B. de Walque, and A. Burt. 2024. Multi-scale lidar measurements suggest miombo woodlands contain substantially more carbon than thought. Communications Earth & Environment. 5(1). https://doi.org/10.1038/s43247-024-01448-x |
2024 | Holcomb, A., P. Burns, S. Keshav, and D.A. Coomes. 2024. Repeat GEDI footprints measure the effects of tropical forest disturbances. Remote Sensing of Environment. 308:114174. https://doi.org/10.1016/j.rse.2024.114174 |
2024 | Liu, X., C.S. Neigh, M. Pardini, and M. Forkel. 2024. Estimating forest height and above-ground biomass in tropical forests using P-band TomoSAR and GEDI observations. International Journal of Remote Sensing. 45(9):3129-3148. https://doi.org/10.1080/01431161.2024.2343134 |
2024 | Pletcher, E., S. Smith-Tripp, D. Evans, and N.B. Schwartz. 2024. Evaluating global vegetation products for application in heterogeneous forest-savanna landscapes. International Journal of Remote Sensing. 45(2):492-507. https://doi.org/10.1080/01431161.2023.2299278 |
2024 | Sillett, S.C., M.E. Graham, J.P. Montague, M.E. Antoine, and G.W. Koch. 2024. Ground-based calibration for remote sensing of biomass in the tallest forests. Forest Ecology and Management. 561:121879. https://doi.org/10.1016/j.foreco.2024.121879 |
2024 | Tolan, J., H. Yang, B. Nosarzewski, G. Couairon, H.V. Vo, J. Brandt, J. Spore, S. Majumdar, D. Haziza, J. Vamaraju, T. Moutakanni, P. Bojanowski, T. Johns, B. White, T. Tiecke, and C. Couprie. 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. 300:113888. https://doi.org/10.1016/j.rse.2023.113888 |
2023 | Bullock, E.L., S.P. Healey, Z. Yang, R. Acosta, H. Villalba, K.P. Insfrán, J.B. Melo, S. Wilson, L. Duncanson, E. Næsset, J. Armston, S. Saarela, G. Ståhl, P.L. Patterson, and R. Dubayah. 2023. Estimating aboveground biomass density using hybrid statistical inference with GEDI lidar data and Paraguay’s national forest inventory. Environmental Research Letters. 18(8):085001. https://doi.org/10.1088/1748-9326/acdf03 |
2023 | Chen, S., C.E. Woodcock, T. Saphangthong, and P. Olofsson. 2023. Satellite data reveals a recent increase in shifting cultivation and associated carbon emissions in Laos. Environmental Research Letters. 18(11):114012. https://doi.org/10.1088/1748-9326/acffdd |
2023 | Hoffrén, R., M.T. Lamelas, J. de la Riva, D. Domingo, A.L. Montealegre, A. García-Martín, and S. Revilla. 2023. Assessing GEDI-NASA system for forest fuels classification using machine learning techniques. International Journal of Applied Earth Observation and Geoinformation. 116:103175. https://doi.org/10.1016/j.jag.2022.103175 |
2023 | Holcomb, A., S.V. Mathis, D.A. Coomes, and S. Keshav. 2023. Computational tools for assessing forest recovery with GEDI shots and forest change maps. Science of Remote Sensing. 8:100106. https://doi.org/10.1016/j.srs.2023.100106 |
2023 | Pascual, A., J. Guerra-Hernández, J. Armston, D.M. Minor, L.I. Duncanson, P.B. May, J.R. Kellner, and R. Dubayah. 2023. Assessing the performance of NASA’s GEDI L4A footprint aboveground biomass density models using National Forest Inventory and airborne laser scanning data in Mediterranean forest ecosystems. Forest Ecology and Management. 538:120975. https://doi.org/10.1016/j.foreco.2023.120975 |
2022 | Vangi, E., G. D’Amico, S. Francini, and G. Chirici. 2022. GEDI4R: an R package for NASA’s GEDI level 4 A data downloading, processing and visualization. Earth Science Informatics. 16(1):1109-1117. https://doi.org/10.1007/s12145-022-00915-3 |