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As little as 10% of the original seasonally dry tropical forest (SDTF) remains for Ecuador, Peru, and Colombia. Remnant forests show high rates of species endemism, but experience degradation from climate change, wood-cutting, and livestock-grazing. Forest census data provide a vital resource for examining remote sensing methods to estimate diversity levels. We used spatially referenced trees \u22655 cm in diameter and simulated 0.10 ha plots measured from a 9 ha SDTF in southwestern Ecuador to compare machine learning (ML) models for six \u03b1-diversity indices. We developed 1 m tree canopy height and elevation models from stem mapped trees, at a scale conventionally derived from light detection and ranging (LiDAR). We then used an ensemble ML approach comparing single- and combined-sensor models from RapidEye, Sentinel-2 and interpolated canopy height and topography surfaces. Validation data showed that combined models often outperformed single-sensor approaches. Combined sensor and model ensembles for tree species richness, Shannon\u2019s H, inverse Simpson\u2019s, unbiased Simpson\u2019s, and Fisher\u2019s alpha indices typically showed lower root mean squared error (RMSE) and increased goodness of fit (R2). Pi\u00e9lou\u2019s J, a measure of evenness, was poorly predicted. Mapped tree species richness (R2 = 0.54, F = 27.3, p = &lt;0.001) and Shannon\u2019s H\u2032 (R2 = 0.54, F = 26.9, p = &lt;0.001) showed the most favorable agreement with field validation observations (n = 25). Small-scale model experiments revealed essential relationships between dry forest tree diversity and data from multiple satellite sensors with repeated global coverage that can help guide larger-scale biodiversity mapping efforts.<\/jats:p>","DOI":"10.3390\/rs15030583","type":"journal-article","created":{"date-parts":[[2023,1,19]],"date-time":"2023-01-19T05:06:14Z","timestamp":1674104774000},"page":"583","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Ensemble Machine Learning for Mapping Tree Species Alpha-Diversity Using Multi-Source Satellite Data in an Ecuadorian Seasonally Dry Forest"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7939-0109","authenticated-orcid":false,"given":"Steven","family":"Sesnie","sequence":"first","affiliation":[{"name":"Division of Biological Sciences, U.S. Fish and Wildlife Service, Albuquerque, NM 87102, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5330-4505","authenticated-orcid":false,"given":"Carlos","family":"Espinosa","sequence":"additional","affiliation":[{"name":"Departamento de Ciencias Biol\u00f3gicas, Universidad T\u00e9cnica Particular de Loja, Loja 1101608, Ecuador"}]},{"given":"Andrea","family":"Jara-Guerrero","sequence":"additional","affiliation":[{"name":"Departamento de Ciencias Biol\u00f3gicas, Universidad T\u00e9cnica Particular de Loja, Loja 1101608, Ecuador"}]},{"given":"Mar\u00eda","family":"Tapia-Armijos","sequence":"additional","affiliation":[{"name":"Departamento de Ciencias Biol\u00f3gicas, Universidad T\u00e9cnica Particular de Loja, Loja 1101608, Ecuador"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.ecolmodel.2005.11.007","article-title":"Mapping the species richness and composition of tropical forest from remotely sensed data with neural networks","volume":"195","author":"Foody","year":"2006","journal-title":"Ecol. Model."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1016\/j.ecoinf.2010.06.001","article-title":"Remotely sensed spectral heterogeneity as a proxy of species diversity: Recent advances and open challenges","volume":"5","author":"Rocchini","year":"2010","journal-title":"Ecol. Inform."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1111\/gcb.13087","article-title":"Toward an integrated monitoring framework to assess the effect of tropical forest degradation and recovery on carbon stocks and biodiversity","volume":"22","author":"Bustamonte","year":"2016","journal-title":"Glob. Change Biol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.foreco.2018.09.003","article-title":"Towards rapid assessment of tree species diversity and structure in fragmented tropical forests: A review of perspectives offered by remotely-sensed and field-based data","volume":"432","author":"Ganivet","year":"2019","journal-title":"For. Ecol. Manag."},{"key":"ref_5","first-page":"1385","article-title":"Plant diversity patterns in neotropical dry forests and their conservation implications","volume":"353","author":"Dexter","year":"2016","journal-title":"Science"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1111\/j.1365-2699.2005.01424.x","article-title":"A global overview of the conservation status of tropical dry forests","volume":"33","author":"Miles","year":"2006","journal-title":"J. Biogeogr."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.rse.2014.01.010","article-title":"Quantifying tropical dry forest succession in the Americas using CHRIS\/PROBA","volume":"144","author":"Rivard","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"045007","DOI":"10.1088\/1748-9326\/aaad74","article-title":"Disentangling the environmental heterogeneity, floristic distinctiveness and current threats of tropical dry forests in Colombia","volume":"13","author":"Isaacs","year":"2018","journal-title":"Environ. Res. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Pennington, T.R., and Ratter, J.A. (2006). Neotropical Savannas and Seasonally Dry Forests, CRC Press.","DOI":"10.1201\/9781420004496"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Manchego, C.E., Hildebrandt, P., Cueva, J., Espinosa, C.I., Stimm, B., and G\u00fcnter, S. (2017). Climate change versus deforestation: Implications for tree species distribution in the dry forests of southern Ecuador. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0190092"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Cueva Ortiz, J., Espinosa, C.I., Dahik, C.Q., Mendoza, Z.A., Ortiz, E.C., Gusm\u00e1n, E., Weber, M., and Hildebrandt, P. (2019). Influence of anthropogenic factors on the diversity and structure of a dry forest in the central part of the Tumbesian Region (Ecuador-Per\u00fa). Forests, 10.","DOI":"10.3390\/f10010031"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"9786","DOI":"10.1038\/s41598-020-66743-x","article-title":"Natural regeneration in the Tumbesian dry forest: Identification of the drivers affecting abundance and diversity","volume":"10","author":"Espinosa","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"108106","DOI":"10.1016\/j.ecolind.2021.108106","article-title":"Remote sensing of spectral diversity: A new methodological approach to account for spatio-temporal dissimilarities between plan communities","volume":"130","author":"Rossi","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"506","DOI":"10.1038\/s41559-022-01702-5","article-title":"Integrating remote sensing with ecology and evolution to advance biodiversity conservation","volume":"6","author":"Schnelder","year":"2022","journal-title":"Nat. Ecol. Evol."},{"key":"ref_15","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_16","doi-asserted-by":"crossref","first-page":"045003","DOI":"10.1088\/1748-9326\/ac583f","article-title":"The use of GEDI canopy structure for explaining variation in tree species richness in natural forests","volume":"17","author":"Marselis","year":"2022","journal-title":"Environ. Res. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2115","DOI":"10.1890\/11-1300.1","article-title":"Unraveling plant-animal diversity relationships: A meta-regression analysis","volume":"93","author":"Castagneyrol","year":"2012","journal-title":"Ecology"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1434","DOI":"10.1111\/1365-2664.12290","article-title":"Robustness of habitat-based surrogates of animal diversity: A multitaxa comparison over time","volume":"51","author":"Barton","year":"2014","journal-title":"J. Appl. Ecol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1940082920978143","DOI":"10.1177\/1940082920978143","article-title":"Relationship between genetic variation and diversity of tree species in tropical forests in the Ocote Biosphere Reserve, Chiapas, Mexico","volume":"14","year":"2021","journal-title":"Trop. Conserv. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Wu, J., Li, H., Wan, H., Wang, Y., Sun, C., and Zhou, H. (2021). Analyzing the relationship between animal diversity and remote sensing vegetation parameters: The case of Xinjiang, China. Sustainability, 13.","DOI":"10.3390\/su13179897"},{"key":"ref_21","first-page":"1000024","article-title":"The impact of geolocation uncertainty on GEDI tropical forest canopy height estimation and change monitoring","volume":"4","author":"Roy","year":"2021","journal-title":"Sci. Remote Sens."},{"key":"ref_22","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_23","doi-asserted-by":"crossref","unstructured":"Daly, A.J., Baetens, J.M., and Baets, B.D. (2018). Ecological diversity: Measuring the unmeasurable. Mathematics, 6.","DOI":"10.3390\/math6070119"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"207","DOI":"10.3390\/d2020207","article-title":"The relation between evenness and diversity","volume":"2","author":"Jost","year":"2010","journal-title":"Diversity"},{"key":"ref_25","first-page":"387","article-title":"Measuring species diversity for conservation biology: Incorporating social and ecological importance of species","volume":"5","author":"Ontoy","year":"2014","journal-title":"Biodivers. J."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"933","DOI":"10.1038\/s41893-021-00753-z","article-title":"Towards a multidimensional biodiversity index for national application","volume":"4","author":"Harfoot","year":"2021","journal-title":"Nat. Sustain."},{"key":"ref_27","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_28","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1002\/env.516","article-title":"Quantitative tools for predicting species lists","volume":"13","author":"Palmer","year":"2002","journal-title":"Environmetrics"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1016\/j.rse.2007.03.018","article-title":"Effects of spatial and spectral resolution in estimating ecosystem \u03b1-diversity by satellite imagery","volume":"111","author":"Rocchini","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"111218","DOI":"10.1016\/j.rse.2019.111218","article-title":"Remote sensing of terrestrial plant biodiversity","volume":"231","author":"Wang","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Ochoa-Franco, A.P., Valdez-Lazalde, J.R., \u00c1ngeles-P\u00e9rez, G., Santos-Posadas, H.M., Hern\u00e1dez-Stefanoni, J.L., Valdez-Hern\u00e1ndez, J.I., and P\u00e9rez-Rodr\u00edguez, P. (2019). Beta-diversity modeling and mapping with LiDAR and multispectral sensors in a semi-evergreen tropical forest. Forests, 10.","DOI":"10.3390\/f10050419"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"975","DOI":"10.1016\/j.ecolind.2019.02.015","article-title":"Combining high resolution satellite imagery and lidar data to model woody plant species diversity of tropical dry forests","volume":"101","author":"Dupuy","year":"2019","journal-title":"Ecol. Indic."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Humphries, G.R.W., Magness, D.R., and Huettmann, F. (2018). Machine Learning for Ecology and Sustainable Natural Resource Management, Springer Nature.","DOI":"10.1007\/978-3-319-96978-7"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Civantos-G\u00f3mez, I., Garc\u00eda-Algarra, J., Garc\u00eda-Callejas, D., Galeano, J., Godoy, O., and Bartomeus, I. (2021). Fine scale prediction of ecological community composition using a two-step sequential machine learning ensemble. PLoS Comput. Biol., 17.","DOI":"10.1101\/2021.03.24.436771"},{"key":"ref_35","first-page":"33","article-title":"Relationship among leaf area index, below canopy light availability and tree diversity along a transect from tropical lowland to montane forest in NE Ecuador","volume":"54","author":"Unger","year":"2013","journal-title":"Trop. Ecol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"5","DOI":"10.7818\/ECOS.2016.25-2.02","article-title":"Reserva Ecol\u00f3gica Arenillas \u00bfun refugio de diversidad biol\u00f3gica o una isla en extinci\u00f3n","volume":"25","author":"Espinosa","year":"2016","journal-title":"Ecosistemas"},{"key":"ref_37","unstructured":"Instituto Espacial Ecuatoriano (IEE) (2012). Memoria T\u00e9cnica Cant\u00f3n Huaquillas, Proyecto: Generaci\u00f3n de Geoinformaci\u00f3n Para la Gesti\u00f3 del Territorio a Nivel Nacional Escala 1:25.000, Instituto Espacial Ecuatoriano (IEE). Clima e Hidrolog\u00eda."},{"key":"ref_38","unstructured":"Sierra, R. (1999). Propuesta Preliminar de un Sistema de Clasificaci\u00f3n de Vegetaci\u00f3n para el Ecuador Continental, Editorial Rimana. Proyecto INEFAN\/GEF-BIRF y EcoCiencia."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1111\/ecog.01328","article-title":"The effects of individual tree species on species diversity in a tropical dry forest change throughout ontogeny","volume":"39","author":"Espinosa","year":"2015","journal-title":"Ecography"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1016\/j.rse.2003.12.013","article-title":"Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture","volume":"90","author":"Haboudane","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_41","unstructured":"Rouse, J.W., Hass, R.H., Schell, J.A., Deering, D.W., and Harlan, J.C. (1973). NASA\/GSFC Type III Final Report, Greenbelt."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"286","DOI":"10.1016\/S0176-1617(11)81633-0","article-title":"Spectral reflectance changes associates with autumn senescence of Aesculus hippocastum L. and Acer platanoides L. leaves. Spectral features and relation to chlorophyll estimation","volume":"143","author":"Gitelson","year":"1994","journal-title":"J. Plant Physiol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/S0034-4257(96)00072-7","article-title":"Use of a green channel in remote sensing of global vegetation from EOS-MODIS","volume":"58","author":"Gitelson","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"640","DOI":"10.2134\/agronj1968.00021962006000060016x","article-title":"Measuring the color of growing turn with a reflectance spectrometer","volume":"60","author":"Birth","year":"1969","journal-title":"Agron. J."},{"key":"ref_45","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_46","first-page":"512","article-title":"New index for crop canopy fresh biomass estimation","volume":"30","author":"Chen","year":"2010","journal-title":"Spectrosc. Spectr. Anal."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"111368","DOI":"10.1016\/j.rse.2019.111368","article-title":"Inferring plant functional diversity from space: The potential of Sentinel-2","volume":"233","author":"Ma","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Chrysafis, I., Korakis, G., Kyriazopoulos, A.P., and Mallinis, G. (2020). Predicting tree species diversity using geodiversity and Sentinel-2 multi-seasonal spectral information. Sustainability, 12.","DOI":"10.3390\/su12219250"},{"key":"ref_49","first-page":"187","article-title":"Retrieval of crop biophysical parameters from Sentinel-2 remote sensing imagery","volume":"80","author":"Xie","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_50","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_51","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/0034-4257(89)90076-X","article-title":"Application of a weighted infrared-red vegetation index for estimating leaf area index by correcting for soil moisture","volume":"29","author":"Clevers","year":"1988","journal-title":"Remote Sens. Environ."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/S0034-4257(01)00342-X","article-title":"Airborne multispectral data for quantifying leaf area index, nitrogen concentration, and photosynthetic efficiency in agriculture","volume":"81","author":"Boegh","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"478","DOI":"10.3390\/rs2020478","article-title":"Assessing plant diversity in a dry tropical forest: Comparing the utility of Landsat and Ikonos satellite images","volume":"2","author":"Nagendra","year":"2010","journal-title":"Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"4741","DOI":"10.3390\/rs6064741","article-title":"Improving species diversity and biomass estimates of tropical dry forests using airborne LiDAR","volume":"6","author":"Dupuy","year":"2014","journal-title":"Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1016\/j.cageo.2004.03.012","article-title":"Multivariable geostatistics in S: The gstat package","volume":"30","author":"Pebesma","year":"2004","journal-title":"Comput. Geosci."},{"key":"ref_56","unstructured":"R Core Team (2022, June 10). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available online: https:\/\/www.R-project.org\/."},{"key":"ref_57","unstructured":"Oksanen, J., Blanchet, F.G., Friendly, M., Kindt, R., Legendre, P., McGlinn, D., Minchin, P.R., O\u2019Hara, R.B., Simpson, G.L., and Solymos, P. (2022, June 10). Vegan: Community Ecology Package. R package version 2.5-7. Available online: https:\/\/CRAN.R-project.org\/package=vegan."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1002\/j.1538-7305.1948.tb01338.x","article-title":"A mathematical theory of communication","volume":"27","author":"Shannon","year":"1948","journal-title":"Bell Syst. Tech. J."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"688","DOI":"10.1038\/163688a0","article-title":"Measurement of diversity","volume":"163","author":"Simpson","year":"1949","journal-title":"Nature"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1111\/j.2006.0030-1299.14714.x","article-title":"Entropy and diversity","volume":"113","author":"Jost","year":"2006","journal-title":"Oikos"},{"key":"ref_61","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_62","doi-asserted-by":"crossref","first-page":"42","DOI":"10.2307\/1411","article-title":"The relation between the number of species and the number of individuals in a random sample of animal population","volume":"12","author":"Fisher","year":"1943","journal-title":"J. Anim. Ecol."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/0022-5193(66)90013-0","article-title":"The measurement of diversity in different types of biological collections","volume":"13","year":"1966","journal-title":"J. Theor. Biol."},{"key":"ref_64","unstructured":"Magurran, A.E. (2004). Measuring Biological Diversity, Blackwell Publishing."},{"key":"ref_65","first-page":"55","article-title":"What do we mean by diversity: The path towards quantification","volume":"9","author":"Jost","year":"2018","journal-title":"M\u00e9tode"},{"key":"ref_66","unstructured":"Hijmans, R.J. (2022, June 10). Raster: Geographic Data Analysis and Modeling. R Package Version 3.5-15. Available online: https:\/\/CRAN.R-project.org\/package=raster."},{"key":"ref_67","unstructured":"Evans, J.S. (2022, June 10). _spatialEco_. R package version 1.3-6. Available online: https:\/\/github.com\/jeffreyevans\/spatialEco."},{"key":"ref_68","unstructured":"Deane-Mayer, Z.A., and Knowles, J.E. (2022, June 10). caretEnsemble: Ensembles of caret models 2019, R Package 2.0.1. Available online: https:\/\/CRAN.R-project.org\/package=caretEnsemble."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v033.i01","article-title":"Regularization Paths for Generalized Linear Models via Coordinate Descent","volume":"33","author":"Friedman","year":"2010","journal-title":"J. Stat. Softw."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"3374","DOI":"10.1109\/TGRS.2006.880628","article-title":"Toward an optimal SVM classification system for hyperspectral remote sensing images","volume":"44","author":"Bazi","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_71","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_72","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/BF00994018","article-title":"Support vector networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Mach. Learn."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1002\/1099-131X(200007)19:4<299::AID-FOR775>3.0.CO;2-V","article-title":"A quantile regression neural network approach to estimating the conditional density of multiperiod returns","volume":"19","author":"Taylor","year":"2000","journal-title":"J. Forecast."},{"key":"ref_74","unstructured":"Kuhn, M. (2022, June 10). caret: Classification and Regression Training 2017, R Package Version 6.0-78. Available online: https:\/\/CRAN.R-project.org\/package=caret."},{"key":"ref_75","first-page":"3245","article-title":"DALEX: Explainers for Complex Predictive Models in R","volume":"19","author":"Biecek","year":"2018","journal-title":"J. Mach. Learn. Res."},{"key":"ref_76","first-page":"209","article-title":"The detection of disease clustering and a generalized regression approach","volume":"27","author":"Mantel","year":"1967","journal-title":"Cancer Res."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1002\/rse2.9","article-title":"Satellite remote sensing to monitor species diversity: Potential and pitfalls","volume":"2","author":"Rocchini","year":"2016","journal-title":"Remote Sens. Ecol. Conserv."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"1360","DOI":"10.1111\/oik.02098","article-title":"Does spatial heterogeniety blur the signatura of dispersal sindormes on spatial patterns of woody species? A test in a tropical dry forest","volume":"124","author":"Espinosa","year":"2015","journal-title":"Oikos"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"723985","DOI":"10.3389\/ffgc.2021.723985","article-title":"Chronic disturbance in a tropical dry forest: Disentangling direct and indirect pathways behind the loss of plant richness","volume":"4","author":"Escudero","year":"2021","journal-title":"Front. For. Glob. Change"},{"key":"ref_80","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_81","doi-asserted-by":"crossref","unstructured":"Sun, H., Hu, J., Wang, J., Zhou, J., Lv, L., and Nie, J. (2021). RSPD: A novel remote sensing index of plant biodiversity combining the spectral variation hypothesis and productivity hypothesis. Remote Sens., 13.","DOI":"10.3390\/rs13153007"},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1186\/s40663-015-0048-1","article-title":"Spatial patter of tree diversity and evenness across forest types in Majella National Park, Italy","volume":"2","author":"Redowan","year":"2015","journal-title":"For. Ecosyst."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"1799","DOI":"10.1111\/geb.13158","article-title":"Evaluating the potential of full-waveform lidar for mapping pan-tropical tree species richness","volume":"29","author":"Marselis","year":"2020","journal-title":"Global Ecol. Biogeogr."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/3\/583\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:09:25Z","timestamp":1760119765000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/3\/583"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,18]]},"references-count":83,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["rs15030583"],"URL":"https:\/\/doi.org\/10.3390\/rs15030583","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,18]]}}}