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Publications Citing Global Ecosystem Dynamics Investigation (GEDI)

The following 109 publications cited the Global Ecosystem Dynamics Investigation (GEDI) project.

YearCitationDataset or Project
2024Bourgoin, 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/s41586-024-07629-0GEDI L4A Footprint Level Aboveground Biomass Density, Version 1
2024Bourgoin, 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/s41586-024-07629-0GEDI L4A Footprint Level Aboveground Biomass Density, Version 2.1
2024Burns, 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/s41597-024-03668-4GEDI L3 Gridded Land Surface Metrics, Version 2
2024Burns, 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/s41597-024-03668-4GEDI L4B Gridded Aboveground Biomass Density, Version 2
2024Burns, 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/s41597-024-03668-4GEDI L4A Footprint Level Aboveground Biomass Density, Version 2.1
2024Campos, 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.e03106GEDI L4A Footprint Level Aboveground Biomass Density, Version 2.1
2024Demol, 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-xGEDI L4A Footprint Level Aboveground Biomass Density, Version 2.1
2024Fararoda, R., R.S. Reddy, G. Rajashekar, T. Mayamanikandan, P. Mutyala, K. Satish, S.W. Pasha, and C. Jha. 2024. Improving plot-level above ground biomass estimation in tropical Indian forests. Ecological Informatics. 81:102621. https://doi.org/10.1016/j.ecoinf.2024.102621GEDI L4B Country-level Summaries of Aboveground Biomass
2024Friedman, N.R. and V. Remeš. 2024. Dorsal and Ventral Plumage Coloration Evolve as Distinct Modules with Different Environmental Correlations. The American Naturalist. 203(4):528-534. https://doi.org/10.1086/728766GEDI L4B Gridded Aboveground Biomass Density, Version 2
2024Holcomb, 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.2024.114174GEDI L4A Footprint Level Aboveground Biomass Density, Version 2.1
2024Jha, N., S.P. Healey, Z. Yang, G. Ståhl, and M.G. Betts. 2024. Vicarious calibration of GEDI biomass with Landsat age data for understanding secondary forest carbon dynamics. Environmental Research Letters. 19(4):044062. https://doi.org/10.1088/1748-9326/ad3661GEDI L4A Footprint Level Aboveground Biomass Density, Version 1
2024Leite, R.V., C. Amaral, C.S.R. Neigh, D.N. Cosenza, C. Klauberg, A.T. Hudak, L. Aragão, D.C. Morton, S. Coffield, T. McCabe, and C.A. Silva. 2024. Leveraging the next generation of spaceborne Earth observations for fuel monitoring and wildland fire management. Remote Sensing in Ecology and Conservation. https://doi.org/10.1002/rse2.416GEDI L3 Gridded Land Surface Metrics, Version 2
2024Leite, R.V., C. Amaral, C.S.R. Neigh, D.N. Cosenza, C. Klauberg, A.T. Hudak, L. Aragão, D.C. Morton, S. Coffield, T. McCabe, and C.A. Silva. 2024. Leveraging the next generation of spaceborne Earth observations for fuel monitoring and wildland fire management. Remote Sensing in Ecology and Conservation. https://doi.org/10.1002/rse2.416GEDI L4B Gridded Aboveground Biomass Density, Version 2
2024Leite, R.V., C. Amaral, C.S.R. Neigh, D.N. Cosenza, C. Klauberg, A.T. Hudak, L. Aragão, D.C. Morton, S. Coffield, T. McCabe, and C.A. Silva. 2024. Leveraging the next generation of spaceborne Earth observations for fuel monitoring and wildland fire management. Remote Sensing in Ecology and Conservation. https://doi.org/10.1002/rse2.416GEDI L4A Footprint Level Aboveground Biomass Density, Golden Weeks, Version 1
2024Li, H., T. Hiroshima, X. Li, M. Hayashi, and T. Kato. 2024. High-resolution mapping of forest structure and carbon stock using multi-source remote sensing data in Japan. Remote Sensing of Environment. 312:114322. https://doi.org/10.1016/j.rse.2024.114322GEDI L4B Gridded Aboveground Biomass Density, Version 2
2024Liu, 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/10.1080/01431161.2024.2343134GEDI L4A Footprint Level Aboveground Biomass Density, Version 2.1
2024May, P.B., M. Schlund, J. Armston, M.M. Kotowska, F. Brambach, A. Wenzel, and S. Erasmi. 2024. Mapping aboveground biomass in Indonesian lowland forests using GEDI and hierarchical models. Remote Sensing of Environment. 313:114384. https://doi.org/10.1016/j.rse.2024.114384GEDI L4B Gridded Aboveground Biomass Density, Version 2
2024May, P.B., R.O. Dubayah, J.M. Bruening, and G.C. Gaines. 2024. Connecting spaceborne lidar with NFI networks: A method for improved estimation of forest structure and biomass. International Journal of Applied Earth Observation and Geoinformation. 129:103797. https://doi.org/10.1016/j.jag.2024.103797GEDI L4A Footprint Level Aboveground Biomass Density, Version 1
2024May, P.B., R.O. Dubayah, J.M. Bruening, and G.C. Gaines. 2024. Connecting spaceborne lidar with NFI networks: A method for improved estimation of forest structure and biomass. International Journal of Applied Earth Observation and Geoinformation. 129:103797. https://doi.org/10.1016/j.jag.2024.103797GEDI L4B Gridded Aboveground Biomass Density, Version 2.1
2024Pascual, A., A. Grau-Neira, E. Morales-Santana, F. Cereceda-Espinoza, J. Pérez-Quezada, A. Cárdenas Martínez, and T. Fuentes-Castillo. 2024. Old-growth mapping in Patagonia’s evergreen forests must integrate GEDI data to overcome NFI data limitations and to effectively support biodiversity conservation. Forest Ecology and Management. 568:122059. https://doi.org/10.1016/j.foreco.2024.122059GEDI L4B Gridded Aboveground Biomass Density, Version 2
2024Pascual, A., A. Grau-Neira, E. Morales-Santana, F. Cereceda-Espinoza, J. Pérez-Quezada, A. Cárdenas Martínez, and T. Fuentes-Castillo. 2024. Old-growth mapping in Patagonia’s evergreen forests must integrate GEDI data to overcome NFI data limitations and to effectively support biodiversity conservation. Forest Ecology and Management. 568:122059. https://doi.org/10.1016/j.foreco.2024.122059GEDI L4B Country-level Summaries of Aboveground Biomass
2024Pletcher, 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/10.1080/01431161.2023.2299278GEDI L4A Footprint Level Aboveground Biomass Density, Version 2.1
2024Pronk, M., A. Hooijer, D. Eilander, A. Haag, T. de Jong, M. Vousdoukas, R. Vernimmen, H. Ledoux, and M. Eleveld. 2024. DeltaDTM: A global coastal digital terrain model. Scientific Data. 11(1). https://doi.org/10.1038/s41597-024-03091-9GEDI L3 Gridded Land Surface Metrics, Version 2
2024Sillett, 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.2024.121879GEDI L4A Footprint Level Aboveground Biomass Density, Version 2.1
2024Tolan, 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.2023.113888GEDI L3 Gridded Land Surface Metrics, Version 1
2024Tolan, 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.2023.113888GEDI L4A Footprint Level Aboveground Biomass Density, Version 2.1
2024Trew, B.T., D.P. Edwards, A.C. Lees, D.H. Klinges, R. Early, M. Svátek, R. Plichta, R. Matula, J. Okello, A. Niessner, M. Barthel, J. Six, E.E. Maeda, J. Barlow, R.O. do Nascimento, E. Berenguer, J. Ferreira, J. Sallo-Bravo, and I.M.D. Maclean. 2024. Novel temperatures are already widespread beneath the world’s tropical forest canopies. Nature Climate Change. 14(7):753-759. https://doi.org/10.1038/s41558-024-02031-0GEDI L3 Gridded Land Surface Metrics, Version 2
2023Bullock, 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/acdf03GEDI L4A Footprint Level Aboveground Biomass Density, Version 2.1
2023Chen, 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/acffddGEDI L4A Footprint Level Aboveground Biomass Density, Version 2.1
2023Choi, C., M. Pardini, J. Armston, and K.P. Papathanassiou. 2023. Forest Biomass Mapping Using Continuous InSAR and Discrete Waveform Lidar Measurements: A TanDEM-X/GEDI Test Study. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 16:7675-7689. https://doi.org/10.1109/JSTARS.2023.3302026GEDI L4A Footprint Level Aboveground Biomass Density, Version 1
2023Farrant, D.N., D.A. Roberts, C.M. D’Antonio, and A.E. Larsen. 2023. What follows fallow? Assessing revegetation patterns on abandoned sugarcane land in Hawai?i. Agriculture, Ecosystems & Environment. 355:108603. https://doi.org/10.1016/j.agee.2023.108603GEDI L4B Gridded Aboveground Biomass Density, Version 2
2023Geremew, T., A. Gonsamo, W. Zewdie, and P. Pellikka. 2023. Extrapolation of canopy height and cover metrics of GEDI LiDAR in tropical montane forest ecosystem. African Geographical Review. 1-17. https://doi.org/10.1080/19376812.2023.2164865GEDI L3 Gridded Land Surface Metrics, Version 2
2023Hoffrén, 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.2022.103175GEDI L4A Footprint Level Aboveground Biomass Density, Version 2.1
2023Holcomb, 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.2023.100106GEDI L4A Footprint Level Aboveground Biomass Density, Version 1
2023Holcomb, 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.2023.100106GEDI L4A Footprint Level Aboveground Biomass Density, Version 2
2023Holcomb, 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.2023.100106GEDI L4A Footprint Level Aboveground Biomass Density, Version 2.1
2023Hunka, N., M. Santoro, J. Armston, R. Dubayah, R.E. McRoberts, E. Næsset, S. Quegan, M. Urbazaev, A. Pascual, P.B. May, D. Minor, V. Leitold, P. Basak, M. Liang, J. Melo, M. Herold, N. Málaga, S. Wilson, P. Durán Montesinos, A. Arana, R. Ernesto De La Cruz Paiva, J. Ferrand, S. Keoka, J. Guerra-Hernández, and L. Duncanson. 2023. On the NASA GEDI and ESA CCI biomass maps: aligning for uptake in the UNFCCC global stocktake. Environmental Research Letters. 18(12):124042. https://doi.org/10.1088/1748-9326/ad0b60GEDI L4A Footprint Level Aboveground Biomass Density, Version 1
2023Hunka, N., M. Santoro, J. Armston, R. Dubayah, R.E. McRoberts, E. Næsset, S. Quegan, M. Urbazaev, A. Pascual, P.B. May, D. Minor, V. Leitold, P. Basak, M. Liang, J. Melo, M. Herold, N. Málaga, S. Wilson, P. Durán Montesinos, A. Arana, R. Ernesto De La Cruz Paiva, J. Ferrand, S. Keoka, J. Guerra-Hernández, and L. Duncanson. 2023. On the NASA GEDI and ESA CCI biomass maps: aligning for uptake in the UNFCCC global stocktake. Environmental Research Letters. 18(12):124042. https://doi.org/10.1088/1748-9326/ad0b60GEDI L4B Gridded Aboveground Biomass Density, Version 2
2023Lang, N., W. Jetz, K. Schindler, and J.D. Wegner. 2023. A high-resolution canopy height model of the Earth. Nature Ecology & Evolution. 7(11):1778-1789. https://doi.org/10.1038/s41559-023-02206-6GEDI L3 Gridded Land Surface Metrics, Version 1
2023Li, W., W. Guo, M. Pasgaard, Z. Niu, L. Wang, F. Chen, Y. Qin, and J. Svenning. 2023. Human fingerprint on structural density of forests globally. Nature Sustainability. 6(4):368-379. https://doi.org/10.1038/s41893-022-01020-5GEDI L3 Gridded Land Surface Metrics, Version 2
2023Liang, M., L. Duncanson, J.A. Silva, and F. Sedano. 2023. Quantifying aboveground biomass dynamics from charcoal degradation in Mozambique using GEDI Lidar and Landsat. Remote Sensing of Environment. 284:113367. https://doi.org/10.1016/j.rse.2022.113367GEDI L4A Footprint Level Aboveground Biomass Density, Version 1
2023Lombardo, S., J. Kinney, D. Blake, S. Chase, A. Stovall, A. Siddiqi, K. Arquilla, S. Israel, D. Wood, and O. de Weck. 2023. Accessible satellite data decision support systems for Yurok Tribe forest management. Acta Astronautica. 213:777-791. https://doi.org/10.1016/j.actaastro.2023.09.040GEDI L4B Gridded Aboveground Biomass Density, Version 2
2023May, P., K.S. McConville, G.G. Moisen, J. Bruening, and R. Dubayah. 2023. A spatially varying model for small area estimates of biomass density across the contiguous United States. Remote Sensing of Environment. 286:113420. https://doi.org/10.1016/j.rse.2022.113420GEDI L4B Gridded Aboveground Biomass Density, Version 2
2023Nathaniel, J., G. Nyirjesy, C.D. Watson, C.M. Albrecht, and L.J. Klein. 2023. Above Ground Carbon Biomass Estimate with Physics-Informed Deep Network. IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium. https://doi.org/10.1109/IGARSS52108.2023.10282838GEDI L4A Footprint Level Aboveground Biomass Density, Version 1
2023Padalia, H., A. Prakash, and T. Watham. 2023. Modelling aboveground biomass of a multistage managed forest through synergistic use of Landsat-OLI, ALOS-2 L-band SAR and GEDI metrics. Ecological Informatics. 77:102234. https://doi.org/10.1016/j.ecoinf.2023.102234GEDI L4B Gridded Aboveground Biomass Density, Version 2
2023Pascual, 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.2023.120975GEDI L4A Footprint Level Aboveground Biomass Density, Version 2.1
2023Retallack, A., G. Finlayson, B. Ostendorf, K. Clarke, and M. Lewis. 2023. Remote sensing for monitoring rangeland condition: Current status and development of methods. Environmental and Sustainability Indicators. 19:100285. https://doi.org/10.1016/j.indic.2023.100285GEDI L4B Gridded Aboveground Biomass Density, Version 2
2023Silveira, E.M., V.C. Radeloff, S. Martinuzzi, G.J. Martinez Pastur, J. Bono, N. Politi, L. Lizarraga, L.O. Rivera, L. Ciuffoli, Y.M. Rosas, A.M. Olah, G.I. Gavier-Pizarro, and A.M. Pidgeon. 2023. Nationwide native forest structure maps for Argentina based on forest inventory data, SAR Sentinel-1 and vegetation metrics from Sentinel-2 imagery. Remote Sensing of Environment. 285:113391. https://doi.org/10.1016/j.rse.2022.113391GEDI L3 Gridded Land Surface Metrics, Version 1
2023Silveira, E.M., V.C. Radeloff, S. Martinuzzi, G.J. Martinez Pastur, J. Bono, N. Politi, L. Lizarraga, L.O. Rivera, L. Ciuffoli, Y.M. Rosas, A.M. Olah, G.I. Gavier-Pizarro, and A.M. Pidgeon. 2023. Nationwide native forest structure maps for Argentina based on forest inventory data, SAR Sentinel-1 and vegetation metrics from Sentinel-2 imagery. Remote Sensing of Environment. 285:113391. https://doi.org/10.1016/j.rse.2022.113391GEDI L4A Footprint Level Aboveground Biomass Density, Golden Weeks, Version 1
2023V.C. Oliveira, P., X. Zhang, B. Peterson, and J.P. Ometto. 2023. Using simulated GEDI waveforms to evaluate the effects of beam sensitivity and terrain slope on GEDI L2A relative height metrics over the Brazilian Amazon Forest. Science of Remote Sensing. 100083. https://doi.org/10.1016/j.srs.2023.100083GEDI L4B Gridded Aboveground Biomass Density, Version 2
2023Wang, X., X. Liu, Y. Wu, R. Chen, and S. Wang. 2023. Dynamic Assessment and Change Analysis of Ecosystem Service Value Based on Physical Assessment Method in Cili County, China. Forests. 14(5):869. https://doi.org/10.3390/f14050869GEDI L4A Footprint Level Aboveground Biomass Density, Version 2
2022Chopping, M., Z. Wang, C. Schaaf, M.A. Bull, and R.R. Duchesne. 2022. Forest aboveground biomass in the southwestern United States from a MISR multi-angle index, 2000–2015. Remote Sensing of Environment. 275:112964. https://doi.org/10.1016/j.rse.2022.112964GEDI L4A Footprint Level Aboveground Biomass Density, Version 2
2022Guo, Y., Y. Lin, W.Y. Chen, J. Ling, Q. Li, J. Michalski, and H. Zhang. 2022. New two-step species-level AGB estimation model applied to urban parks. Ecological Indicators. 145:109694. https://doi.org/10.1016/j.ecolind.2022.109694GEDI L4B Gridded Aboveground Biomass Density, Version 2
2022Labrière, N., S.J. Davies, M.I. Disney, L.I. Duncanson, M. Herold, S.L. Lewis, O.L. Phillips, S. Quegan, S.S. Saatchi, D.G. Schepaschenko, K. Scipal, P. Sist, and J. Chave. 2022. Toward a forest biomass reference measurement system for remote sensing applications. Global Change Biology. 29(3):827-840. https://doi.org/10.1111/gcb.16497GEDI L3 Gridded Land Surface Metrics, Version 2
2022Vangi, 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/s12145-022-00915-3GEDI L4A Footprint Level Aboveground Biomass Density, Version 1
2022Vangi, 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/s12145-022-00915-3GEDI L4A Footprint Level Aboveground Biomass Density, Version 2.1
2022Zhang, S., Y. Chen, Y. Lu, H. Guo, X. Guo, C. Liu, X. Zhou, and Y. Zhang. 2022. Spatial variability and driving factors of soil multifunctionality in drylands of China. Regional Sustainability. 3(3):223-232. https://doi.org/10.1016/j.regsus.2022.10.001GEDI L4B Gridded Aboveground Biomass Density, Version 2
2024Elliott, L.H., J.C. Vogeler, J.D. Holbrook, B.R. Barry, and K.T. Vierling. 2024. Assessing GEDI data fusions to map woodpecker distributions and biodiversity hotspots. Environmental Research Letters. 19(9):094027. https://doi.org/10.1088/1748-9326/ad64ebGlobal Ecosystem Dynamics Investigation
2024Leite, R.V., C. Amaral, C.S.R. Neigh, D.N. Cosenza, C. Klauberg, A.T. Hudak, L. Aragão, D.C. Morton, S. Coffield, T. McCabe, and C.A. Silva. 2024. Leveraging the next generation of spaceborne Earth observations for fuel monitoring and wildland fire management. Remote Sensing in Ecology and Conservation. https://doi.org/10.1002/rse2.416Global Ecosystem Dynamics Investigation
2024Mohite, J., S. Sawant, A. Pandit, M. Sakkan, S. Pappula, and A. Parmar. 2024. Forest aboveground biomass estimation by GEDI and multi-source EO data fusion over Indian forest. International Journal of Remote Sensing. 45(4):1304-1338. https://doi.org/10.1080/01431161.2024.2307944Global Ecosystem Dynamics Investigation
2022Atmani, F., B. Bookhagen, and T. Smith. 2022. Measuring Vegetation Heights and Their Seasonal Changes in the Western Namibian Savanna Using Spaceborne Lidars. Remote Sensing. 14(12):2928. https://doi.org/10.3390/rs14122928Global Ecosystem Dynamics Investigation
2022Duncanson, L., J.R. Kellner, J. Armston, R. Dubayah, D.M. Minor, S. Hancock, S.P. Healey, P.L. Patterson, S. Saarela, S. Marselis, C.E. Silva, J. Bruening, S.J. Goetz, H. Tang, M. Hofton, B. Blair, S. Luthcke, L. Fatoyinbo, K. Abernethy, A. Alonso, H.E. Andersen, P. Aplin, T.R. Baker, N. Barbier, J.F. Bastin, P. Biber, P. Boeckx, J. Bogaert, L. Boschetti, P.B. Boucher, D.S. Boyd, D.F.R.P. Burslem, S. Calvo-Rodriguez, J. Chave, R.L. Chazdon, D.B. Clark, D.A. Clark, W.B. Cohen, D.A. Coomes, P. Corona, K.C. Cushman, M.E.J. Cutler, J.W. Dalling, M. Dalponte, J. Dash, S. de-Miguel, S. Deng, P.W. Ellis, B. Erasmus, P.A. Fekety, A. Fernandez-Landa, A. Ferraz, R. Fischer, A.G. Fisher, A. Garcia-Abril, T. Gobakken, J.M. Hacker, M. Heurich, R.A. Hill, C. Hopkinson, H. Huang, S.P. Hubbell, A.T. Hudak, A. Huth, B. Imbach, K.J. Jeffery, M. Katoh, E. Kearsley, D. Kenfack, N. Kljun, N. Knapp, K. Kral, M. Krucek, N. Labriere, S.L. Lewis, M. Longo, R.M. Lucas, R. Main, J.A. Manzanera, R.V. Martinez, R. Mathieu, H. Memiaghe, V. Meyer, A.M. Mendoza, A. Monerris, P. Montesano, F. Morsdorf, E. Naesset, L. Naidoo, R. Nilus, M. O'Brien, D.A. Orwig, K. Papathanassiou, G. Parker, C. Philipson, O.L. Phillips, J. Pisek, J.R. Poulsen, H. Pretzsch, C. Rudiger, S. Saatchi, A. Sanchez-Azofeifa, N. Sanchez-Lopez, R. Scholes, C.A. Silva, M. Simard, A. Skidmore, K. Sterenczak, M. Tanase, C. Torresan, R. Valbuena, H. Verbeeck, T. Vrska, K. Wessels, J.C. White, L.J.T. White, E. Zahabu, and C. Zgraggen. 2022. Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission. Remote Sensing of Environment. 270:112845. https://doi.org/10.1016/j.rse.2021.112845Global Ecosystem Dynamics Investigation
2022Fayad, I., N. Baghdadi, and F. Frappart. 2022. Comparative Analysis of GEDI's Elevation Accuracy from the First and Second Data Product Releases over Inland Waterbodies. Remote Sensing. 14(2):340. https://doi.org/10.3390/rs14020340Global Ecosystem Dynamics Investigation
2022Lang, N., N. Kalischek, J. Armston, K. Schindler, R. Dubayah, and J.D. Wegner. 2022. Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles. Remote Sensing of Environment. 268:112760. https://doi.org/10.1016/j.rse.2021.112760Global Ecosystem Dynamics Investigation
2022Leite, R.V., C.A. Silva, E.N. Broadbent, C.H.d. Amaral, V. Liesenberg, D.R.A.d. Almeida, M. Mohan, S. Godinho, A. Cardil, C. Hamamura, B.L.d. Faria, P.H.S. Brancalion, A. Hirsch, G.E. Marcatti, A.P. Dalla Corte, A.M.A. Zambrano, M.B.T.d. Costa, E.A.T. Matricardi, A.L.d. Silva, L.R.R.Y. Goya, R. Valbuena, B.A.F.d. Mendonca, C.H.L. Silva Junior, L.E.O.C. Aragao, M. Garcia, J. Liang, T. Merrick, A.T. Hudak, J. Xiao, S. Hancock, L. Duncason, M.P. Ferreira, D. Valle, S. Saatchi, and C. Klauberg. 2022. Large scale multi-layer fuel load characterization in tropical savanna using GEDI spaceborne lidar data. Remote Sensing of Environment. 268:112764. https://doi.org/10.1016/j.rse.2021.112764Global Ecosystem Dynamics Investigation
2022Liu, X., Y. Su, T. Hu, Q. Yang, B. Liu, Y. Deng, H. Tang, Z. Tang, J. Fang, and Q. Guo. 2022. Neural network guided interpolation for mapping canopy height of China's forests by integrating GEDI and ICESat-2 data. Remote Sensing of Environment. 269:112844. https://doi.org/10.1016/j.rse.2021.112844Global Ecosystem Dynamics Investigation
2021Bauer, L., N. Knapp, and R. Fischer. 2021. Mapping Amazon Forest Productivity by Fusing GEDI Lidar Waveforms with an Individual-Based Forest Model. Remote Sensing. 13(22):4540. https://doi.org/10.3390/rs13224540Global Ecosystem Dynamics Investigation
2021Chen, H., S.R. Cloude, and J.C. White. 2021. Using GEDI Waveforms for Improved TanDEM-X Forest Height Mapping: A Combined SINC + Legendre Approach. Remote Sensing. 13(15):2882. https://doi.org/10.3390/rs13152882Global Ecosystem Dynamics Investigation
2021Di Tommaso, S., S. Wang, and D.B. Lobell. 2021. Combining GEDI and Sentinel-2 for wall-to-wall mapping of tall and short crops. Environmental Research Letters. 16(12):125002. https://doi.org/10.1088/1748-9326/ac358cGlobal Ecosystem Dynamics Investigation
2021DiMiceli, C., J. Townshend, M. Carroll, and R. Sohlberg. 2021. Evolution of the representation of global vegetation by vegetation continuous fields. Remote Sensing of Environment. 254:112271. https://doi.org/10.1016/j.rse.2020.112271Global Ecosystem Dynamics Investigation
2021Dorado-Roda, I., A. Pascual, S. Godinho, C. Silva, B. Botequim, P. Rodriguez-Gonzalvez, E. Gonzalez-Ferreiro, and J. Guerra-Hernandez. 2021. Assessing the Accuracy of GEDI Data for Canopy Height and Aboveground Biomass Estimates in Mediterranean Forests. Remote Sensing. 13(12):2279. https://doi.org/10.3390/rs13122279Global Ecosystem Dynamics Investigation
2021Fayad, I., D. Ienco, N. Baghdadi, R. Gaetano, C.A. Alvares, J.L. Stape, H. Ferraco Scolforo, and G. Le Maire. 2021. A CNN-based approach for the estimation of canopy heights and wood volume from GEDI waveforms. Remote Sensing of Environment. 265:112652. https://doi.org/10.1016/j.rse.2021.112652Global Ecosystem Dynamics Investigation
2021Fayad, I., N. Baghdadi, and J. Riedi. 2021. Quality Assessment of Acquired GEDI Waveforms: Case Study over France, Tunisia and French Guiana. Remote Sensing. 13(16):3144. https://doi.org/10.3390/rs13163144Global Ecosystem Dynamics Investigation
2021Fayad, I., N. Baghdadi, C. Alcarde Alvares, J.L. Stape, J.S. Bailly, H.F. Scolforo, I.R. Cegatta, M. Zribi, and G. Le Maire. 2021. Terrain Slope Effect on Forest Height and Wood Volume Estimation from GEDI Data. Remote Sensing. 13(11):2136. https://doi.org/10.3390/rs13112136Global Ecosystem Dynamics Investigation
2021Kacic, P., A. Hirner, and E. Da Ponte. 2021. Fusing Sentinel-1 and -2 to Model GEDI-Derived Vegetation Structure Characteristics in GEE for the Paraguayan Chaco. Remote Sensing. 13(24):5105. https://doi.org/10.3390/rs13245105Global Ecosystem Dynamics Investigation
2021Kokalj, Ž. and J. Mast. 2021. Space lidar for archaeology? Reanalyzing GEDI data for detection of ancient Maya buildings. Journal of Archaeological Science: Reports. 36:102811. https://doi.org/10.1016/j.jasrep.2021.102811Global Ecosystem Dynamics Investigation
2021Potapov, P., 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, and M. Hofton. 2021. Mapping global forest canopy height through integration of GEDI and Landsat data. Remote Sensing of Environment. 253:112165. https://doi.org/10.1016/j.rse.2020.112165Global Ecosystem Dynamics Investigation
2021Rishmawi, K., C. Huang, and X. Zhan. 2021. Monitoring Key Forest Structure Attributes across the Conterminous United States by Integrating GEDI LiDAR Measurements and VIIRS Data. Remote Sensing. 13(3):442. https://doi.org/10.3390/rs13030442Global Ecosystem Dynamics Investigation
2021Silva, C.A., L. Duncanson, S. Hancock, A. Neuenschwander, N. Thomas, M. Hofton, L. Fatoyinbo, M. Simard, C.Z. Marshak, J. Armston, S. Lutchke, and R. Dubayah. 2021. Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping. Remote Sensing of Environment. 253:112234. https://doi.org/10.1016/j.rse.2020.112234Global Ecosystem Dynamics Investigation
2021Spracklen, B. and D.V. Spracklen. 2021. Determination of Structural Characteristics of Old-Growth Forest in Ukraine Using Spaceborne LiDAR. Remote Sensing. 13(7):1233. https://doi.org/10.3390/rs13071233Global Ecosystem Dynamics Investigation
2021Vittucci, C., L. Guerriero, P. Ferrazzoli, P. Richaume, and Y.H. Kerr. 2021. SMOS L-VOD Retrieved by Level 2 Algorithm and its Correlation With GEDI LIDAR Products. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 14:11870-11878. https://doi.org/10.1109/JSTARS.2021.3128022Global Ecosystem Dynamics Investigation
2021Xiang, J., H. Li, J. Zhao, X. Cai, and P. Li. 2021. Inland water level measurement from spaceborne laser altimetry: Validation and comparison of three missions over the Great Lakes and lower Mississippi River. Journal of Hydrology. 597:126312. https://doi.org/10.1016/j.jhydrol.2021.126312Global Ecosystem Dynamics Investigation
2020Adam, M., M. Urbazaev, C. Dubois, and C. Schmullius. 2020. Accuracy Assessment of GEDI Terrain Elevation and Canopy Height Estimates in European Temperate Forests: Influence of Environmental and Acquisition Parameters. Remote Sensing. 12(23):3948. https://doi.org/10.3390/rs12233948Global Ecosystem Dynamics Investigation
2020Boucher, P., S. Hancock, D. Orwig, L. Duncanson, J. Armston, H. Tang, K. Krause, B. Cook, I. Paynter, Z. Li, A. Elmes, and C. Schaaf. 2020. Detecting Change in Forest Structure with Simulated GEDI Lidar Waveforms: A Case Study of the Hemlock Woolly Adelgid (HWA; Adelges tsugae) Infestation. Remote Sensing. 12(8):1304. https://doi.org/10.3390/rs12081304Global Ecosystem Dynamics Investigation
2020Duncanson, L., A. Neuenschwander, S. Hancock, N. Thomas, T. Fatoyinbo, M. Simard, C.A. Silva, J. Armston, S.B. Luthcke, M. Hofton, J.R. Kellner, and R. Dubayah. 2020. Biomass estimation from simulated GEDI, ICESat-2 and NISAR across environmental gradients in Sonoma County, California. Remote Sensing of Environment. 242:111779. https://doi.org/10.1016/j.rse.2020.111779Global Ecosystem Dynamics Investigation
2020Fayad, I., N. Baghdadi, J.S. Bailly, F. Frappart, and M. Zribi. 2020. Analysis of GEDI Elevation Data Accuracy for Inland Waterbodies Altimetry. Remote Sensing. 12(17):2714. https://doi.org/10.3390/rs12172714Global Ecosystem Dynamics Investigation
2020Healey, S.P., Z. Yang, N. Gorelick, and S. Ilyushchenko. 2020. Highly Local Model Calibration with a New GEDI LiDAR Asset on Google Earth Engine Reduces Landsat Forest Height Signal Saturation. Remote Sensing. 12(17):2840. https://doi.org/10.3390/rs12172840Global Ecosystem Dynamics Investigation
2020Kumar, S., H. Govil, P.K. Srivastava, P.K. Thakur, and S.P.S. Kushwaha. 2020. Spaceborne Multifrequency PolInSAR-Based Inversion Modelling for Forest Height Retrieval. Remote Sensing. 12(24):4042. https://doi.org/10.3390/rs12244042Global Ecosystem Dynamics Investigation
2020Marselis, S.M., K. Abernethy, A. Alonso, J. Armston, T.R. Baker, J.F. Bastin, J. Bogaert, D.S. Boyd, P. Boeckx, D.F.R.P. Burslem, R. Chazdon, D.B. Clark, D. Coomes, L. Duncanson, S. Hancock, R. Hill, C. Hopkinson, E. Kearsley, J.R. Kellner, D. Kenfack, N. Labriere, S.L. Lewis, D. Minor, H. Memiaghe, A. Monteagudo, R. Nilus, M. O'Brien, O.L. Phillips, J. Poulsen, H. Tang, H. Verbeeck, and R. Dubayah. 2020. Evaluating the potential of full-waveform lidar for mapping pan-tropical tree species richness. Global Ecology and Biogeography. 29(10):1799-1816. https://doi.org/10.1111/geb.13158Global Ecosystem Dynamics Investigation
2020Sanchez-Lopez, N., L. Boschetti, A.T. Hudak, S. Hancock, and L.I. Duncanson. 2020. Estimating Time Since the Last Stand-Replacing Disturbance (TSD) from Spaceborne Simulated GEDI Data: A Feasibility Study. Remote Sensing. 12(21):3506. https://doi.org/10.3390/rs12213506Global Ecosystem Dynamics Investigation
2020Tan, P., J. Zhu, H. Fu, C. Wang, Z. Liu, and C. Zhang. 2020. Sub-Canopy Topography Estimation from TanDEM-X DEM by Fusing ALOS-2 PARSAR-2 InSAR Coherence and GEDI Data. Sensors. 20(24):7304. https://doi.org/10.3390/s20247304Global Ecosystem Dynamics Investigation
2019Fagua, J.C., P. Jantz, S. Rodriguez-Buritica, L. Duncanson, and S.J. Goetz. 2019. Integrating LiDAR, Multispectral and SAR Data to Estimate and Map Canopy Height in Tropical Forests. Remote Sensing. 11(22):2697. https://doi.org/10.3390/rs11222697Global Ecosystem Dynamics Investigation
2019Hancock, S., J. Armston, M. Hofton, X. Sun, H. Tang, L.I. Duncanson, J.R. Kellner, and R. Dubayah. 2019. The GEDI Simulator: A Large-Footprint Waveform Lidar Simulator for Calibration and Validation of Spaceborne Missions. Earth and Space Science. 6(2):294-310. https://doi.org/10.1029/2018EA000506Global Ecosystem Dynamics Investigation
2019Kellner, J.R., J. Armston, M. Birrer, K.C. Cushman, L. Duncanson, C. Eck, C. Falleger, B. Imbach, K. Kral, M. Krucek, J. Trochta, T. Vrska, and C. Zgraggen. 2019. New Opportunities for Forest Remote Sensing Through Ultra-High-Density Drone Lidar. Surveys in Geophysics. 40(4):959-977. https://doi.org/10.1007/s10712-019-09529-9Global Ecosystem Dynamics Investigation
2019Klein, V. and P. Axelrad. 2019. Advanced multipath modeling and validation for GPS onboard the International Space Station. Navigation. 66(3):559-575. https://doi.org/10.1002/navi.327Global Ecosystem Dynamics Investigation
2019Qi, W., S. Saarela, J. Armston, G. Stahl, and R. Dubayah. 2019. Forest biomass estimation over three distinct forest types using TanDEM-X InSAR data and simulated GEDI lidar data. Remote Sensing of Environment. 232:111283. https://doi.org/10.1016/j.rse.2019.111283Global Ecosystem Dynamics Investigation
2019Qi, W., S.K. Lee, S. Hancock, S. Luthcke, H. Tang, J. Armston, and R. Dubayah. 2019. Improved forest height estimation by fusion of simulated GEDI Lidar data and TanDEM-X InSAR data. Remote Sensing of Environment. 221:621-634. https://doi.org/10.1016/j.rse.2018.11.035Global Ecosystem Dynamics Investigation
2019Quegan, S., T. Le Toan, J. Chave, J. Dall, J.F. Exbrayat, D.H.T. Minh, M. Lomas, M.M. D'Alessandro, P. Paillou, K. Papathanassiou, F. Rocca, S. Saatchi, K. Scipal, H. Shugart, T.L. Smallman, M.J. Soja, S. Tebaldini, L. Ulander, L. Villard, and M. Williams. 2019. The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space. Remote Sensing of Environment. 227:44-60. https://doi.org/10.1016/j.rse.2019.03.032Global Ecosystem Dynamics Investigation
2019Scarth, P., J. Armston, R. Lucas, and P. Bunting. 2019. A Structural Classification of Australian Vegetation Using ICESat/GLAS, ALOS PALSAR, and Landsat Sensor Data. Remote Sensing. 11(2):147. https://doi.org/10.3390/rs11020147Global Ecosystem Dynamics Investigation
2019Tang, H., J. Armston, S. Hancock, S. Marselis, S. Goetz, and R. Dubayah. 2019. Characterizing global forest canopy cover distribution using spaceborne lidar. Remote Sensing of Environment. 231:111262. https://doi.org/10.1016/j.rse.2019.111262Global Ecosystem Dynamics Investigation
2019Tian, J., L. Wang, X. Li, D. Yin, H. Gong, S. Nie, C. Shi, R. Zhong, X. Liu, and R. Xu. 2019. Canopy Height Layering Biomass Estimation Model (CHL-BEM) with Full-Waveform LiDAR. Remote Sensing. 11(12):1446. https://doi.org/10.3390/rs11121446Global Ecosystem Dynamics Investigation
2018Pereira, L., L. Furtado, E. Novo, S. Sant'Anna, V. Liesenberg, and T. Silva. 2018. Multifrequency and Full-Polarimetric SAR Assessment for Estimating Above Ground Biomass and Leaf Area Index in the Amazon Varzea Wetlands. Remote Sensing. 10(9):1355. https://doi.org/10.3390/rs10091355Global Ecosystem Dynamics Investigation
2018Pourshamsi, M., M. Garcia, M. Lavalle, and H. Balzter. 2018. A Machine-Learning Approach to PolInSAR and LiDAR Data Fusion for Improved Tropical Forest Canopy Height Estimation Using NASA AfriSAR Campaign Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 11(10):3453-3463. https://doi.org/10.1109/JSTARS.2018.2868119Global Ecosystem Dynamics Investigation
2018Saarela, S., S. Holm, S. Healey, H.E. Andersen, H. Petersson, W. Prentius, P. Patterson, E. Naesset, T. Gregoire, and G. Stahl. 2018. Generalized Hierarchical Model-Based Estimation for Aboveground Biomass Assessment Using GEDI and Landsat Data. Remote Sensing. 10(11):1832. https://doi.org/10.3390/rs10111832Global Ecosystem Dynamics Investigation
2018Silva, C.A., S. Saatchi, M. Garcia, N. Labriere, C. Klauberg, A. Ferraz, V. Meyer, K.J. Jeffery, K. Abernethy, L. White, K. Zhao, S.L. Lewis, and A.T. Hudak. 2018. Comparison of Small- and Large-Footprint Lidar Characterization of Tropical Forest Aboveground Structure and Biomass: A Case Study From Central Gabon. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 11(10):3512-3526. https://doi.org/10.1109/JSTARS.2018.2816962Global Ecosystem Dynamics Investigation
2017Mahoney, C. and C. Hopkinson. 2017. Continental Estimates of Canopy Gap Fraction by Active Remote Sensing. Canadian Journal of Remote Sensing. 43(4):345-359. https://doi.org/10.1080/07038992.2017.1346469Global Ecosystem Dynamics Investigation
2017Mountrakis, G. and Y. Li. 2017. A linearly approximated iterative Gaussian decomposition method for waveform LiDAR processing. ISPRS Journal of Photogrammetry and Remote Sensing. 129:200-211. https://doi.org/10.1016/j.isprsjprs.2017.05.009Global Ecosystem Dynamics Investigation
2016Qi, W. and R.O. Dubayah. 2016. Combining Tandem-X InSAR and simulated GEDI lidar observations for forest structure mapping. Remote Sensing of Environment. 187:253-266. https://doi.org/10.1016/j.rse.2016.10.018Global Ecosystem Dynamics Investigation
2015Stysley, P.R., D.B. Coyle, R.B. Kay, R. Frederickson, D. Poulios, K. Cory, and G. Clarke. 2015. Long term performance of the High Output Maximum Efficiency Resonator (HOMER) laser for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar. Optics & Laser Technology. 68:67-72. https://doi.org/10.1016/j.optlastec.2014.11.001Global Ecosystem Dynamics Investigation