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the capacity to monitor species diversity worldwide is of great importance in halting biodiversity loss. To this end, remote sensing plays a unique role. In this study, we evaluate the potential of Global Ecosystem Dynamics Investigation (GEDI) data, combined with conventional satellite optical imagery and climate reanalysis data, to predict in situ alpha diversity (Species richness, Simpson index, and Shannon index) among tree species. Data from Sentinel-2 optical imagery, ERA-5 climate data, SRTM-DEM imagery, and simulated GEDI data were selected for the characterization of diversity in four study areas. The integration of ancillary data can improve biodiversity metrics predictions. Random Forest (RF) regression models were suitable for estimating tree species diversity indices from remote sensing variables. From these models, we generated diversity index maps for the entire Cerrado using all GEDI data available in orbit. For all models, the structural metric Foliage Height Diversity (FHD) was selected; the Renormalized Difference Vegetation Index (RDVI) was also selected in all species diversity models. For the Shannon model, two GEDI variables were selected. Overall, the models indicated performances for species diversity ranging from (R2 = 0.24 to 0.56). In terms of RMSE%, the Shannon model had the lowest value among the diversity indices (31.98%). Our results suggested that the developed models are valuable tools for assessing species diversity in tropical savanna ecosystems, although each model can be chosen based on the objectives of a given study, the target amount of performance\/error, and the availability of data.<\/jats:p>","DOI":"10.3390\/s25020308","type":"journal-article","created":{"date-parts":[[2025,1,7]],"date-time":"2025-01-07T05:06:34Z","timestamp":1736226394000},"page":"308","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Spatial Characterization of Woody Species Diversity in Tropical Savannas Using GEDI and Optical Data"],"prefix":"10.3390","volume":"25","author":[{"given":"Franciel Eduardo","family":"Rex","sequence":"first","affiliation":[{"name":"Department of Forestry Engineering, Federal University of Paran\u00e1-UFPR, Curitiba 80050-380, PR, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7844-3560","authenticated-orcid":false,"given":"Carlos Alberto","family":"Silva","sequence":"additional","affiliation":[{"name":"Forest Biometrics and Remote Sensing Laboratory (Silva Lab), School of Forest, Fisheries, and Geomatics Sciences, University of Florida, P.O. 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Toosi University of Technology, P.O. Box 15875-4416, Tehran 15418-49611, Iran"},{"name":"Department of Remote Sensing, University of W\u00fcrzburg, Oswald K\u00fclpe Weg 86, 97074 W\u00fcrzburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0622-6903","authenticated-orcid":false,"given":"Jingfeng","family":"Xiao","sequence":"additional","affiliation":[{"name":"Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2295-3131","authenticated-orcid":false,"given":"Jeff W.","family":"Atkins","sequence":"additional","affiliation":[{"name":"USDA Forest Service, Southern Research Station, P.O. 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Third National Communication of Brazil to the United Nations Framework Convention on Climate Change Brasilia 333, UNFCCC."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Pennington, R.T., and Ratter, J. (2006). Neotropical Savanas and Seasonally Dry Forests, CRC.","DOI":"10.1201\/9781420004496"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1016\/j.biocon.2009.09.020","article-title":"Extent and conservation of tropical dry forests in the Americas","volume":"143","year":"2010","journal-title":"Biol. Conserv."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"105520","DOI":"10.1016\/j.ecolind.2019.105520","article-title":"Forest beta-diversity analysis by remote sensing: How scale and sensors affect the Rao\u2019s Q index","volume":"106","author":"Khare","year":"2019","journal-title":"Ecol. Indic."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.gloenvcha.2014.04.002","article-title":"Changes in the global value of ecosystem services","volume":"26","author":"Costanza","year":"2014","journal-title":"Glob. Environ. Change"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.ecolind.2018.12.013","article-title":"Assessing ecosystem service provision in a tropical region with high forest cover: Spatial overlap and the impact of land use change in Amap\u00e1, Brazil","volume":"99","author":"Milheiras","year":"2018","journal-title":"Ecol. Indic."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"656","DOI":"10.1016\/j.tree.2020.03.006","article-title":"Stand-ardizing ecosystem morphological traits from 3D information sources","volume":"35","author":"Valbuena","year":"2020","journal-title":"Trends Ecol. Evol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"045013","DOI":"10.1088\/1748-9326\/ab0bbe","article-title":"Beyond MRV: High-resolution forest carbon modeling for climate mitigation planning over Maryland, USA","volume":"14","author":"Hurtt","year":"2019","journal-title":"Environ. Res. Lett."},{"key":"ref_12","first-page":"121","article-title":"Quantitative tools for perfecting species lists","volume":"13","author":"Palmer","year":"2002","journal-title":"Environmetrics Off. J. Int. Environmetrics Soc."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Mallinis, G., Chrysafis, I., Korakis, G., Pana, E., and Kyriazopoulos, A.P. (2020). A Random Forest Modelling Procedure for a Multi-Sensor Assessment of Tree Species Diversity. Remote Sens., 12.","DOI":"10.3390\/rs12071210"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1177\/0309133308093606","article-title":"Measuring and modelling biodiversity from space","volume":"32","author":"Gillespie","year":"2008","journal-title":"Prog. Phys. Geogr. Earth Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.rse.2016.01.017","article-title":"Discrimination of tropical forest types, dominant species, and mapping of functional guilds by hyperspectral and simulated multispectral Sentinel-2 data","volume":"176","author":"Laurin","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_16","first-page":"101","article-title":"Investigating multiple data sources for tree species classification in temperate forest and use for single tree delineation","volume":"18","author":"Heinzel","year":"2012","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_17","first-page":"359","article-title":"Modeling \u03b1- and \u03b2-diversity in a tropical forest from remotely sensed and spatial data","volume":"19","author":"Meave","year":"2012","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"586","DOI":"10.1007\/s10661-017-6295-6","article-title":"Can tree species diversity be assessed with Landsat data in a temperate forest?","volume":"189","author":"Arekhi","year":"2017","journal-title":"Environ. Monit. Assess."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1016\/j.isprsjprs.2017.10.008","article-title":"Remote sensing of species diversity using Landsat 8 spectral variables","volume":"133","author":"Madonsela","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"de Souza Mendes, F., Baron, D., Gerold, G., Liesenberg, V., and Erasmi, S. (2019). Optical and SAR Remote Sensing Synergism for Mapping Vegetation Types in the Endangered Cerrado\/Amazon Ecotone of Nova Mutum\u2014Mato Grosso. Remote Sens., 11.","DOI":"10.3390\/rs11101161"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Chrysafis, I., Korakis, G., Kyriazopoulos, A.P., and Mallinis, G. (2021). Predicting Tree Species Diversity Using Geodiversity and Sentinel-2 Multi-Seasonal Spectral Information. Sustainability, 12.","DOI":"10.3390\/su12219250"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"107105","DOI":"10.1016\/j.ecolind.2020.107105","article-title":"A 15-year spatio-temporal analysis of plant \u03b2-diversity using Landsat time series derived Rao\u2019s Q index","volume":"121","author":"Khare","year":"2020","journal-title":"Ecol. Indic."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0034-4257(02)00096-2","article-title":"Overview of the radiometric and biophysical performance of the MODIS vegetation indices","volume":"83","author":"Huete","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"626","DOI":"10.1016\/j.rse.2018.07.023","article-title":"Distinguishing vegetation types with airborne waveform lidar data in a tropical forest-savanna mosaic: A case study in Lop\u00e9 National Park, Gabon","volume":"216","author":"Marselis","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1191\/0309133303pp360ra","article-title":"LiDAR remote sensing of forest structure","volume":"27","author":"Lim","year":"2003","journal-title":"Prog. Phys. Geogr. Earth Environ."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Rex, F.E., Silva, C.A., Corte, A.P.D., Klauberg, C., Mohan, M., Cardil, A., da Silva, V.S., de Almeida, D.R.A., Garcia, M., and Broadbent, E.N. (2020). Comparison of Statistical Modelling Approaches for Estimating Tropical Forest Aboveground Biomass Stock and Reporting Their Changes in Low-Intensity Logging Areas Using Multi-Temporal LiDAR Data. Remote Sens., 12.","DOI":"10.3390\/rs12091498"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Laurin, G.V., Chan, J.C.-W., Chen, Q., Lindsell, J.A., Coomes, D.A., Guerriero, L., Del Frate, F., Miglietta, F., and Valentini, R. (2014). Biodiversity Mapping in a Tropical West African Forest with Airborne Hyperspectral Data. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0097910"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.ecolind.2015.12.026","article-title":"Mapping tree species diversity of a tropical montane forest by unsupervised clustering of airborne imaging spectroscopy data","volume":"64","author":"Heiskanen","year":"2016","journal-title":"Ecol. Indic."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1016\/j.ecolind.2009.07.012","article-title":"Does using species abundance data improve estimates of species diversity from remotely sensed spectral heterogeneity?","volume":"10","author":"Oldeland","year":"2010","journal-title":"Ecol. Indic."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Peng, Y., Fan, M., Song, J., Cui, T., and Li, R. (2018). Assessment of plant species diversity based on hyperspectral indices at a fine scale. Sci. Rep., 8.","DOI":"10.1038\/s41598-018-23136-5"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"100002","DOI":"10.1016\/j.srs.2020.100002","article-title":"The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth\u2019s forests and topography","volume":"1","author":"Dubayah","year":"2020","journal-title":"Sci. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"094013","DOI":"10.1088\/1748-9326\/ab2dcd","article-title":"Exploring the relation between remotely sensed vertical canopy structure and tree species diversity in Gabon","volume":"14","author":"Marselis","year":"2019","journal-title":"Environ. Res. Lett."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"5751","DOI":"10.1080\/01431160902736635","article-title":"Quantification of spatial distribution of vegetation in the Qilian Mountain area with MODIS NDVI","volume":"30","author":"Jin","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"119155","DOI":"10.1016\/j.foreco.2021.119155","article-title":"Beyond trees: Mapping total aboveground biomass density in the Brazilian savanna using high-density UAV-lidar data","volume":"491","author":"Silva","year":"2021","journal-title":"For. Ecol. Manag."},{"key":"ref_35","unstructured":"Sano, S.M., Almeida, S.P., and Ribeiro, J.F. (2008). As Principais Fitofisionomias do Bioma Cerrado. Cerrado: Ecologia e Flora, Embrapa Cerrados."},{"key":"ref_36","unstructured":"Felfili, J.M. (2007). Biogeografia do Bioma Cerrado: Vegeta\u00e7\u00e3o e Solos da Chapada dos Veadeiros, UnB. [1st ed.]."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"419","DOI":"10.1111\/1365-2664.13794","article-title":"Tropical riparian forests in danger from large savanna wildfires","volume":"58","author":"Flores","year":"2020","journal-title":"J. Appl. Ecol."},{"key":"ref_38","unstructured":"Porto, A.C., Linares, J.A.H., and Neto, G.B.S. (May, January 30). An\u00e1lise da Estrutura e Din\u00e2mica da Paisagem do Parque Nacional da Chapada dos Veadeiros. Proceedings of the Anais do Simp\u00f3sio Brasileiro de Sensoriamento Remoto, SBSR, Curitiba, Brazil."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Oliveira, P.S., and Marquis, T.J. (2002). Vegetation Physiognomies and Woody Flora of the Cerrado Biome. The Cerrados of Brazil: Ecology and Natural History of a Neotropical Savanna, Columbia University Press.","DOI":"10.7312\/oliv12042"},{"key":"ref_40","first-page":"76","article-title":"Solos e vegeta\u00e7\u00e3o nos Complexos Rupestres de Altitude da Mantiqueira e do Espinha\u00e7o","volume":"10","author":"Benites","year":"2003","journal-title":"Floresta E Ambiente"},{"key":"ref_41","unstructured":"Durigan, G., Pilon, N.A.L., Assis, G.B., Souza, F.M., and Baitello, J.B. (2018). Plantas Pequenas do Cerrado: Biodiversidade Negli-Genciada, Secretaria do Meio Ambiente do Estado de S\u00e3o Paulo."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"577","DOI":"10.2307\/1934145","article-title":"The Nonconcept of Species Diversity: A Critique and Alternative Parameters","volume":"52","author":"Hurlbert","year":"1971","journal-title":"Ecology"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1146\/annurev.es.05.110174.001441","article-title":"The Measurement of Species Diversity","volume":"5","author":"Peet","year":"1974","journal-title":"Ann. Rev. Ecol. Syst."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1590\/S1676-06032008000300001","article-title":"O que Ganhamos \u2018Confundindo\u2019 Riqueza de Esp\u00e9cies e Equabilidade em um \u00cdndice de Diversidade?","volume":"8","author":"Melo","year":"2008","journal-title":"Biota Neotrop."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/S0143-6228(02)00002-4","article-title":"Opposite trends in response for the Shannon and Simpson indices of landscape diversity","volume":"22","author":"Nagendra","year":"2002","journal-title":"Appl. Geogr."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1016\/j.ecolind.2008.06.001","article-title":"Indices for monitoring biodiversity change: Are some more effective than others?","volume":"9","author":"Lamb","year":"2009","journal-title":"Ecol. Indic."},{"key":"ref_47","unstructured":"R Core Team (2023). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing. Available online: https:\/\/www.R-project.org\/."},{"key":"ref_48","unstructured":"Broadbent, E.N., Almeyda Zambrano, A.M., Omans, G., Adler, B., Alonso, P., Naylor, D., Chenevert, G., Murtha, T., Prata, G., and de Almeida, D.R.A. (2021, May 05). The GatorEye Uninhabited Flying Laboratory: Sensor Fusion for 4D Ecological Analysis Through Custom Hardware and Algorithm Integration. Available online: www.gatoreye.org."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"D\u2019Oliveira, M.V.N., Broadbent, E.N., Oliveira, L.C., Almeida, D.R.A., Papa, D.A., Ferreira, M.E., Zambrano, A.M.A., Silva, C.A., Avino, F.S., and Prata, G.A. (2020). Aboveground Biomass Estimation in Amazonian Tropical Forests: A Comparison of Aircraft- and GatorEye UAV-borne LiDAR Data in the Chico Mendes Extractive Reserve in Acre, Brazil. Remote Sens., 12.","DOI":"10.3390\/rs12111754"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"112764","DOI":"10.1016\/j.rse.2021.112764","article-title":"Large scale multi-layer fuel load characterization in tropical savanna using GEDI spaceborne lidar data","volume":"268","author":"Leite","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1029\/2018EA000506","article-title":"The GEDI Simulator: A Large-Footprint Waveform Lidar Simulator for Calibration and Validation of Spaceborne Missions","volume":"6","author":"Hancock","year":"2019","journal-title":"Earth Space Sci."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"2509","DOI":"10.1029\/1999GL010484","article-title":"Modeling laser altimeter return waveforms over complex vegetation using high-resolution elevationdata","volume":"26","author":"Blair","year":"1999","journal-title":"Geophys. Res. Lett."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"111779","DOI":"10.1016\/j.rse.2020.111779","article-title":"Biomass estimation from simulated GEDI, ICESat-2 and NISAR across environmental gradients in Sonoma County, California","volume":"242","author":"Duncanson","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_54","unstructured":"Silva, C.A., Hamamura, C., Valbuena, R., Hancock, S., Cardil, A., Broadbent, E.N., Almeida, D.R.A., Silva Junior, C.H.L., and Klauberg, C. (2020, October 22). rGEDI: NASA\u2019s Global Ecosystem Dynamics Investigation (GEDI) Data Visualization and Processing, Version 0.1.8. Available online: https:\/\/CRAN.R-project.org\/package=rGEDI."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Boucher, P.B., Hancock, S., A Orwig, D., Duncanson, L., Armston, J., Tang, H., Krause, K., Cook, B., Paynter, I., and Li, Z. (2020). Detecting Change in Forest Structure with Simulated GEDI Lidar Waveforms: A Case Study of the Hemlock Woolly Adelgid (HWA; Adelges tsugae) Infestation. Remote Sens., 12.","DOI":"10.3390\/rs12081304"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1016\/j.rse.2018.11.035","article-title":"Improved forest height estimation by fusion of simulated GEDI Lidar data and TanDEM-X InSAR data","volume":"221","author":"Qi","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"112234","DOI":"10.1016\/j.rse.2020.112234","article-title":"Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping","volume":"253","author":"Silva","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Ogilvie, A., Poussin, J.-C., Bader, J.-C., Bayo, F., Bodian, A., Dacosta, H., Dia, D., Diop, L., Martin, D., and Sambou, S. (2020). Combining Multi-Sensor Satellite Imagery to Improve Long-Term Monitoring of Temporary Surface Water Bodies in the Senegal River Floodplain. Remote Sens., 12.","DOI":"10.3390\/rs12193157"},{"key":"ref_59","unstructured":"Rouse, J.W. (1974). Monitoring the Vernal Advancement of Retrogradation of Natural Vegetation, NASA. Technical Report Type III, Final Report."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1109\/TGRS.1995.8746027","article-title":"A feedback based modification of the NDVI to minimize canopy background and at-mospheric noise","volume":"33","author":"Liu","year":"1995","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1016\/S0034-4257(00)00150-4","article-title":"Optical-biophysical relationships of vegetation spectra without background contamination","volume":"74","author":"Gao","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/0034-4257(88)90106-X","article-title":"A soil-adjusted vegetation index (SAVI)","volume":"25","author":"Huete","year":"1988","journal-title":"Remote Sens. Environ."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"663","DOI":"10.2307\/1936256","article-title":"Derivation of Leaf-Area Index from Quality of Light on the Forest Floor","volume":"50","author":"Jordan","year":"1969","journal-title":"Ecology"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/0034-4257(79)90013-0","article-title":"Red and photographic infrared linear combinations for monitoring vegetation","volume":"8","author":"Tucker","year":"1979","journal-title":"Remote Sens. Environ."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"1335","DOI":"10.1080\/01431168508948283","article-title":"Canopy reflectance, photosynthesis and transpiration","volume":"6","author":"Sellers","year":"1985","journal-title":"Int. J. Remote Sens."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.coal.2010.12.009","article-title":"Remote sensing of vegetation health for reclaimed areas of Seyit\u00f6mer open cast coal mine","volume":"86","author":"Erener","year":"2011","journal-title":"Int. J. Coal Geol."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"3097","DOI":"10.5194\/acp-19-3097-2019","article-title":"From ERA-Interim to ERA5: The considerable impact of ECMWF\u2019s next-generation reanalysis on Lagrangian transport simulations","volume":"19","author":"Hoffmann","year":"2019","journal-title":"Atmos. Chem. Phys."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Mukul, M., Srivastava, V., Jade, S., and Mukul, M. (2017). Uncertainties in the shuttle radar topography mission (SRTM) Heights: Insights from the Indian Himalaya and Peninsula. Sci. Rep., 7.","DOI":"10.1038\/srep41672"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"3875","DOI":"10.1080\/01431161003786016","article-title":"SRTM DEM and its application advances","volume":"32","author":"Yang","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_70","first-page":"913","article-title":"A global climatology of stratosphere\u2013troposphere exchange using the ERA-Interim data set from 1979 to 2011","volume":"14","author":"Sprenger","year":"2014","journal-title":"Atmos. Meas. Tech."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"RG2004","DOI":"10.1029\/2005RG000183","article-title":"The shuttle radar topography mission","volume":"45","author":"Farr","year":"2007","journal-title":"Rev. Geophys."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"2225","DOI":"10.1016\/j.patrec.2010.03.014","article-title":"Variable selection using random forests","volume":"31","author":"Genuer","year":"2010","journal-title":"Pattern Recognit. Lett."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"19","DOI":"10.32614\/RJ-2015-018","article-title":"VSURF: An R Package for Variable Selection Using Random Forests","volume":"7","author":"Genuer","year":"2015","journal-title":"R J."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.apgeog.2018.05.011","article-title":"Aboveground biomass estimation using multi-sensor data synergy and machine learning algorithms in a dense tropical forest","volume":"96","author":"Ghosh","year":"2018","journal-title":"Appl. Geogr."},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"Torbick, N., Ledoux, L., Salas, W., and Zhao, M. (2016). Regional Mapping of Plantation Extent Using Multisensor Imagery. Remote Sens., 8.","DOI":"10.3390\/rs8030236"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.isprsjprs.2011.11.002","article-title":"An assessment of the effectiveness of a random forest classifier for land-cover classification","volume":"67","author":"Ghimire","year":"2012","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.isprsjprs.2016.01.011","article-title":"Random forest in remote sensing: A review of applications and future directions","volume":"114","author":"Belgiu","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_79","first-page":"18","article-title":"Classification and regression by random forest","volume":"2","author":"Liaw","year":"2002","journal-title":"R News"},{"key":"ref_80","unstructured":"Dubayah, R., Hofton, M., Blair, J., Armston, J., Tang, H., and Luthcke, S. (2024). GEDI L2A Elevation and Height Metrics Data Global Footprint Level V002, NASA EOSDIS Land Processes DAAC."},{"key":"ref_81","unstructured":"Dubayah, R., Hofton, M., Blair, J., Armston, J., Tang, H., and Luthcke, S. (2021). GEDI L2B Canopy Cover and Vertical Profile Metrics Data Global Footprint Level V002, NASA EOSDIS Land Processes DAAC."},{"key":"ref_82","doi-asserted-by":"crossref","unstructured":"Souza, C.M., Shimbo, J.Z., Rosa, M.R., Parente, L.L., Alencar, A., Rudorff, B.F., Hasenack, H., Matsumoto, M., Ferreira, L.G., and Souza-Filho, P.W. (2020). Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine. Remote Sens., 12.","DOI":"10.3390\/rs12172735"},{"key":"ref_83","unstructured":"Hofton, M., and Blair, J.B. (2021, March 13). Algorithm Theoretical Basis Document (ATBD) for GEDI Transmit and Receive Waveform Processing for L1 and L2 Products, Available online: https:\/\/lpdaac.usgs.gov\/documents\/581\/GEDI_WF_ATBD_v1.0.pdf."},{"key":"ref_84","first-page":"8","article-title":"A new era in forest restoration monitoring","volume":"28","author":"Stark","year":"2019","journal-title":"Restor. Ecol."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1111\/j.1654-109X.2011.01143.x","article-title":"Spectral heterogeneity of QuickBird satellite data is related to fine-scale plant species spatial turnover in semi-natural grasslands","volume":"15","author":"Hall","year":"2011","journal-title":"Appl. Veg. Sci."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"8489","DOI":"10.3390\/rs70708489","article-title":"On the importance of training data sample selection in random forest image classification: A case study in peatland ecosystem mapping","volume":"7","author":"Millard","year":"2015","journal-title":"Remote Sens."},{"key":"ref_87","doi-asserted-by":"crossref","unstructured":"Dorado-Roda, I., Pascual, A., Godinho, S., Silva, C.A., Botequim, B., Rodr\u00edguez-Gonz\u00e1lvez, P., Gonz\u00e1lez-Ferreiro, E., and Guerra-Hern\u00e1ndez, J. (2021). Assessing the Accuracy of GEDI Data for Canopy Height and Aboveground Biomass Estimates in Mediterranean Forests. Remote Sens., 13.","DOI":"10.3390\/rs13122279"},{"key":"ref_88","first-page":"102326","article-title":"Improved estimation of forest stand volume by the integration of GEDI LiDAR data and multi-sensor imagery in the Changbai Mountains Mixed forests Ecoregion (CMMFE), northeast China","volume":"100","author":"Chen","year":"2021","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"840","DOI":"10.1111\/j.1523-1739.2012.01869.x","article-title":"Use of an Airborne Lidar System to Model Plant Species Composition and Diversity of Mediterranean Oak Forests","volume":"26","author":"Simonson","year":"2012","journal-title":"Conserv. Biol."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/0034-4257(94)00114-3","article-title":"Estimating PAR absorbed by vegetation from bidirectional reflectance measurements","volume":"51","author":"Roujean","year":"1995","journal-title":"Remote Sens. Environ."},{"key":"ref_91","unstructured":"Chuvieco, E. (2002). Teledetecci\u00f3n Ambiental, RIALP. [3rd ed.]."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.isprsjprs.2007.05.006","article-title":"A hyperspectral band selector for plant species discrimination","volume":"62","author":"Vaiphasa","year":"2007","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_93","doi-asserted-by":"crossref","unstructured":"Meng, J., Li, S., Wang, W., Liu, Q., Xie, S., and Ma, W. (2016). Estimation of Forest Structural Diversity Using the Spectral and Textural Information Derived from SPOT-5 Satellite Images. Remote Sens., 8.","DOI":"10.3390\/rs8020125"},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"2767","DOI":"10.1080\/01431160903095460","article-title":"Estimation of tropical forest structure from SPOT-5 satellite images","volume":"31","author":"Ricker","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"113576","DOI":"10.1016\/j.rse.2023.113576","article-title":"Mapping tree species diversity in temperate montane forests using Sentinel-1 and Sentinel-2 imagery and topography data","volume":"292","author":"Liu","year":"2023","journal-title":"Remote Sens. Environ."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.foreco.2009.03.043","article-title":"A hierarchical approach coupled with coarse DEM information for improving the efficiency and accuracy of forest mapping over very rugged terrains","volume":"258","author":"Ren","year":"2009","journal-title":"For. Ecol. Manag."},{"key":"ref_97","doi-asserted-by":"crossref","unstructured":"Robinson, C., Saatchi, S., Clark, D., Astaiza, J.H., Hubel, A.F., and Gillespie, T.W. (2018). Topography and Three-Dimensional Structure Can Estimate Tree Diversity along a Tropical Elevational Gradient in Costa Rica. Remote Sens., 10.","DOI":"10.3390\/rs10040629"},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"696","DOI":"10.1111\/geb.13061","article-title":"Beyond counts and averages: Relating geodiversity to dimensions of biodiversity","volume":"29","author":"Read","year":"2020","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"112103","DOI":"10.1016\/j.rse.2020.112103","article-title":"Evaluation of machine learning algorithms for forest stand species mapping using Sentinel-2 imagery and environmental data in the Polish Carpathians","volume":"251","author":"Grabska","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"3514","DOI":"10.1002\/ece3.1155","article-title":"Choosing and using diversity indices: Insights for ecological applications from the German Biodiversity Exploratories","volume":"4","author":"Morris","year":"2014","journal-title":"Ecol. Evol."},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1002\/ecy.2109","article-title":"Mapping multi-scale vascular plant richness in a forest landscape with integrated LiDAR and hyperspectral remote sensing","volume":"99","author":"Hakkenberg","year":"2018","journal-title":"Ecology"},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"1776","DOI":"10.1890\/14-1593.1","article-title":"Predicting spatial variations of tree species richness in tropical forests from high-resolution remote sensing","volume":"25","author":"Fricker","year":"2015","journal-title":"Ecol. Appl."},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"1080","DOI":"10.1111\/jbi.12696","article-title":"Environmental predictors of species richness in forest landscapes: Abiotic factors versus vegetation structure","volume":"43","author":"Zellweger","year":"2016","journal-title":"J. Biogeogr."},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.rse.2017.03.023","article-title":"Area-wide evapotranspiration monitoring at the crown level of a tropical mountain rain forest","volume":"194","author":"Silva","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_105","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1111\/aje.12622","article-title":"Remotely sensed C3 and C4 grass species aboveground biomass variability in response to seasonal climate and topography","volume":"57","author":"Shoko","year":"2019","journal-title":"Afr. J. Ecol."},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"692","DOI":"10.1111\/j.1472-4642.2007.00372.x","article-title":"Predicting mountain plant richness and rarity from space using satellite-derived vegetation indices","volume":"13","author":"Levin","year":"2007","journal-title":"Divers. Distrib."},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"7063","DOI":"10.3390\/s110707063","article-title":"Evaluation of Sentinel-2 Red-Edge Bands for Empirical Estimation of Green LAI and Chlorophyll Content","volume":"11","author":"Delegido","year":"2011","journal-title":"Sensors"},{"key":"ref_108","doi-asserted-by":"crossref","first-page":"5583","DOI":"10.1080\/01431161.2012.666812","article-title":"Testing the red edge channel for improving land-use classifications based on high-resolution multi-spectral satellite data","volume":"33","author":"Schuster","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1111\/j.1523-1739.1990.tb00309.x","article-title":"Indicators for Monitoring Biodiversity: A Hierarchical Approach","volume":"4","author":"Noss","year":"1990","journal-title":"Conserv. Biol."},{"key":"ref_110","first-page":"355","article-title":"An integrated approach to biological diversity assessment","volume":"17","author":"Debinski","year":"1997","journal-title":"Nat. Areas J."},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"446","DOI":"10.1016\/S0169-5347(01)02205-4","article-title":"Monitoring of biological diversity in space and time","volume":"16","author":"Yoccoz","year":"2001","journal-title":"Trends Ecol. Evol."},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"668","DOI":"10.1016\/j.tree.2006.08.007","article-title":"Monitoring for conservation","volume":"21","author":"Nichols","year":"2006","journal-title":"Trends Ecol. Evol."},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1890\/1540-9295(2007)5[253:WNEM]2.0.CO;2","article-title":"Who needs environmental monitoring?","volume":"5","author":"Lovett","year":"2007","journal-title":"Front. Ecol. Environ."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/25\/2\/308\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T10:24:13Z","timestamp":1759919053000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/25\/2\/308"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,7]]},"references-count":113,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2025,1]]}},"alternative-id":["s25020308"],"URL":"https:\/\/doi.org\/10.3390\/s25020308","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,7]]}}}