{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T01:52:48Z","timestamp":1778291568561,"version":"3.51.4"},"reference-count":73,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2020,5,15]],"date-time":"2020-05-15T00:00:00Z","timestamp":1589500800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Tropical forests have exceptional floristic diversity, but their characterization remains incomplete, in part due to the resource intensity of in-situ assessments. Remote sensing technologies can provide valuable, cost-effective, large-scale insights. This study investigates the combined use of airborne LiDAR and imaging spectroscopy to map tree species at landscape scale in French Guiana. Binary classifiers were developed for each of 20 species using linear discriminant analysis (LDA), regularized discriminant analysis (RDA) and logistic regression (LR). Complementing visible and near infrared (VNIR) spectral bands with short wave infrared (SWIR) bands improved the mean average classification accuracy of the target species from 56.1% to 79.6%. Increasing the number of non-focal species decreased the success rate of target species identification. Classification performance was not significantly affected by impurity rates (confusion between assigned classes) in the non-focal class (up to 5% of bias), provided that an adequate criterion was used for adjusting threshold probability assignment. A limited number of crowns (30 crowns) in each species class was sufficient to retrieve correct labels effectively. Overall canopy area of target species was strongly correlated to their basal area over 118 ha at 1.5 ha resolution, indicating that operational application of the method is a realistic prospect (R2 = 0.75 for six major commercial tree species).<\/jats:p>","DOI":"10.3390\/rs12101577","type":"journal-article","created":{"date-parts":[[2020,5,15]],"date-time":"2020-05-15T10:53:59Z","timestamp":1589540039000},"page":"1577","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Quantitative Airborne Inventories in Dense Tropical Forest Using Imaging Spectroscopy"],"prefix":"10.3390","volume":"12","author":[{"given":"Anthony","family":"Laybros","sequence":"first","affiliation":[{"name":"AMAP, IRD, CNRS, INRA, Universit\u00e9 Montpellier, CIRAD, 34000 Montpellier, France"},{"name":"P\u00f4le RDI, ONF Guyane, 97300 Cayenne, French Guiana, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4439-8626","authenticated-orcid":false,"given":"M\u00e9laine","family":"Aubry-Kientz","sequence":"additional","affiliation":[{"name":"AMAP, IRD, CNRS, INRA, Universit\u00e9 Montpellier, CIRAD, 34000 Montpellier, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0151-1334","authenticated-orcid":false,"given":"Jean-Baptiste","family":"F\u00e9ret","sequence":"additional","affiliation":[{"name":"TETIS, INRAE, University of Montpellier, 500 rue Fran\u00e7ois Breton, 34093 Montpellier CEDEX 5, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6988-6685","authenticated-orcid":false,"given":"Caroline","family":"Bedeau","sequence":"additional","affiliation":[{"name":"P\u00f4le RDI, ONF Guyane, 97300 Cayenne, French Guiana, France"}]},{"given":"Olivier","family":"Brunaux","sequence":"additional","affiliation":[{"name":"P\u00f4le RDI, ONF Guyane, 97300 Cayenne, French Guiana, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7239-2881","authenticated-orcid":false,"given":"G\u00e9raldine","family":"Derroire","sequence":"additional","affiliation":[{"name":"Cirad, UMR EcoFoG (AgroParistech, CNRS, INRAE, Universit\u00e9 des Antilles, Universit\u00e9 de la Guyane), 97379 Kourou, French Guiana, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9443-021X","authenticated-orcid":false,"given":"Gr\u00e9goire","family":"Vincent","sequence":"additional","affiliation":[{"name":"AMAP, IRD, CNRS, INRA, Universit\u00e9 Montpellier, CIRAD, 34000 Montpellier, France"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.pld.2016.01.001","article-title":"Plant diversity in a changing world: Status, trends, and conservation needs","volume":"38","author":"Corlett","year":"2016","journal-title":"Plant Divers."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2314","DOI":"10.1016\/j.biocon.2010.01.021","article-title":"Biodiversity conservation in human-modified Amazonian forest landscapes","volume":"143","author":"Peres","year":"2010","journal-title":"Biol. Conserv."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"779","DOI":"10.3390\/d5040779","article-title":"Land and Forest Degradation inside Protected Areas in Latin America","volume":"5","author":"Leisher","year":"2013","journal-title":"Diversity"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1770","DOI":"10.1126\/science.287.5459.1770","article-title":"Global Biodiversity Scenarios for the Year 2100","volume":"287","author":"Sala","year":"2000","journal-title":"Science"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1893","DOI":"10.1016\/j.cub.2014.06.065","article-title":"Thresholds of Logging Intensity to Maintain Tropical Forest Biodiversity","volume":"24","author":"Burivalova","year":"2014","journal-title":"Curr. Biol."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Putz, F.E., Zuidema, P.A., Pinard, M.A., Boot, R.G.A., Sayer, J.A., Sheil, D., Sist, P., and Vanclay, J.K. (2008). Improved Tropical Forest Management for Carbon Retention. PLoS Biol., 6.","DOI":"10.1371\/journal.pbio.0060166"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/j.foreco.2014.01.005","article-title":"Large trees as key elements of carbon storage and dynamics after selective logging in the Eastern Amazon","volume":"318","author":"Sist","year":"2014","journal-title":"For. Ecol. Manag."},{"key":"ref_8","first-page":"359","article-title":"Woody vines and forest management in Malaysia","volume":"64","author":"Putz","year":"1985","journal-title":"Commonw. For. Rev."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Putz, F.E., and Mooney, H.A. (1991). The Biology of Vines, Cambridge University Press.","DOI":"10.1017\/CBO9780511897658"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2176","DOI":"10.1016\/j.foreco.2011.08.009","article-title":"Thinning after selective logging facilitates floristic composition recovery in a tropical rain forest of Central Africa","volume":"262","author":"Beina","year":"2011","journal-title":"For. Ecol. Manag."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"6056","DOI":"10.1073\/pnas.1611855114","article-title":"Effects of habitat disturbance on tropical forest biodiversity","volume":"114","author":"Alroy","year":"2017","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1016\/S0378-1127(01)00506-0","article-title":"Effect of disturbance intensity on regeneration mechanisms in a tropical dry forest","volume":"162","author":"Kennard","year":"2002","journal-title":"For. Ecol. Manag."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"23954","DOI":"10.1038\/srep23954","article-title":"Impact of Forest Management on Species Richness: Global Meta-Analysis and Economic Trade-Offs","volume":"6","author":"Chaudhary","year":"2016","journal-title":"Sci. Rep."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4869","DOI":"10.3390\/s90604869","article-title":"Applications of Remote Sensing to Alien Invasive Plant Studies","volume":"9","author":"Huang","year":"2009","journal-title":"Sensors"},{"key":"ref_15","unstructured":"Ustin, S.L., DiPietro, D., Olmstead, K., Underwood, E., and Scheer, G.J. (2002, January 24\u201328). Hyperspectral remote sensing for invasive species detection and mapping. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Toronto, ON, Canada."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Waite, C.E., van der Heijden, G.M.F., Field, R., and Boyd, D.S. (2019). A view from above: Unmanned aerial vehicles (UAVs) provide a new tool for assessing liana infestation in tropical forest canopies. J. Appl. Ecol.","DOI":"10.1111\/1365-2664.13318"},{"key":"ref_17","first-page":"3","article-title":"Reduced-impact logging in the tropics: Objectives, principles and impacts","volume":"2","author":"Sist","year":"2000","journal-title":"Int. For. Rev."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2682","DOI":"10.3390\/rs6042682","article-title":"Improving Remote Species Identification through Efficient Training Data Collection","volume":"6","author":"Baldeck","year":"2014","journal-title":"Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Baldeck, C.A., Asner, G.P., Martin, R.E., Anderson, C.B., Knapp, D.E., Kellner, J.R., and Wright, S.J. (2015). Operational Tree Species Mapping in a Diverse Tropical Forest with Airborne Imaging Spectroscopy. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0118403"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1109\/TGRS.2012.2199323","article-title":"Tree Species Discrimination in Tropical Forests Using Airborne Imaging Spectroscopy","volume":"51","author":"Feret","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_21","first-page":"93","article-title":"Classification of tree species based on longwave hyperspectral data from leaves, a case study for a tropical dry forest","volume":"66","author":"Harrison","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Laybros, A., Schl\u00e4pfer, D., F\u00e9ret, J.-B., Descroix, L., Bedeau, C., Lefevre, M.-J., and Vincent, G. (2019). Across Date Species Detection Using Airborne Imaging Spectroscopy. Remote Sens., 11.","DOI":"10.3390\/rs11070789"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/j.rse.2005.03.009","article-title":"Hyperspectral discrimination of tropical rain forest tree species at leaf to crown scales","volume":"96","author":"Clark","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Ferreira, M.P., Zortea, M., Zanotta, D.C., Feret, J.B., Shimabukuro, Y.E., and Filho, C.R. (October, January 28). On the use of shortwave infrared for tree species discrimination in tropical semideciduous forest. Proceedings of the ISPRS Geospatial Week 2015, La Grande Motte, France.","DOI":"10.5194\/isprsarchives-XL-3-W3-473-2015"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1820","DOI":"10.3390\/rs4061820","article-title":"Species-Level Differences in Hyperspectral Metrics among Tropical Rainforest Trees as Determined by a Tree-Based Classifier","volume":"4","author":"Clark","year":"2012","journal-title":"Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2632","DOI":"10.1109\/TGRS.2012.2216272","article-title":"Tree Species Classification in Boreal Forests with Hyperspectral Data","volume":"51","author":"Dalponte","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Aubry-Kientz, M., Dutrieux, R., Ferraz, A., Saatchi, S., Hamraz, H., Williams, J., Coomes, D., Piboule, A., and Vincent, G. (2019). A Comparative Assessment of the Performance of Individual Tree Crowns Delineation Algorithms from ALS Data in Tropical Forests. Remote Sens., 11.","DOI":"10.3390\/rs11091086"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1016\/j.rse.2014.12.020","article-title":"On the use of binary partition trees for the tree crown segmentation of tropical rainforest hyperspectral images","volume":"159","author":"Tochon","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_29","first-page":"448","article-title":"Learning with Positive and Unlabeled Examples Using Weighted Logistic Regression","volume":"3","author":"Lee","year":"2003","journal-title":"ICML"},{"key":"ref_30","unstructured":"Gourlet-Fleury, S., Guehl, J.-M., Laroussinie, O., and ECOFOR (Group) (2004). Ecology and Management of a Neotropical Rainforest: Lessons Drawn from Paracou, a Long-Term Experimental Research Site in French Guiana, Elsevier."},{"key":"ref_31","unstructured":"Richter, R., and Schlapfer, D. (2018). Atmospheric\/Topographic Correction for Airborne Imagery (ATCOR-4 User Guide, Version 7.2.0), ReSe Applications LLC."},{"key":"ref_32","unstructured":"Schlapfer, D. (2006). PARametric Geocoding, Orthorectification for Airborne Scanner Data, User Manual Version 2.3, ReSe Applications Schlaepfer and Remote Sensing Laboratories (RSL) of the University of Zurich."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1861","DOI":"10.1080\/01431160310001598908","article-title":"Sun and view angle effects on NDVI determination of land cover types in the Brazilian Amazon region with hyperspectral data","volume":"25","author":"Ponzoni","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1016\/j.rse.2016.05.028","article-title":"Lidar detection of individual tree size in tropical forests","volume":"183","author":"Ferraz","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Xiao, W., Zaforemska, A., Smigaj, M., Wang, Y., and Gaulton, R. (2019). Mean Shift Segmentation Assessment for Individual Forest Tree Delineation from Airborne Lidar Data. Remote Sens., 11.","DOI":"10.3390\/rs11111263"},{"key":"ref_36","unstructured":"Roussel, J.-R., Auty, D., De Boissieu, F., and Meador, A. (2018). lidR: Airborne LiDAR Data Manipulation and Visualization for Forestry Applications, R Core Team."},{"key":"ref_37","first-page":"2825","article-title":"Scikit-learn: Machine Learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"Mach. Learn. PYTHON"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Kurtzer, G.M., Sochat, V., and Bauer, M.W. (2017). Singularity: Scientific containers for mobility of compute. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0177459"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"2067","DOI":"10.1016\/S0031-3203(00)00162-X","article-title":"A direct LDA algorithm for high-dimensional data\u2014With application to face recognition","volume":"34","author":"Yu","year":"2001","journal-title":"Pattern Recognit."},{"key":"ref_40","unstructured":"Duda, R.O., Hart, P.E., and Stork, D.G. (2012). Pattern Classification, John Wiley & Sons."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1080\/01621459.1989.10478752","article-title":"Regularized Discriminant Analysis","volume":"84","author":"Friedman","year":"1989","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_42","unstructured":"Guo, Y., Hastie, T., and Tibshirani, R. (2005). Regularized Discriminant Analysis and Its Application in Microarrays, Dept. of Statistics, Stanford University."},{"key":"ref_43","first-page":"143","article-title":"Comparison of Logistic Regression and Linear Discriminant Analysis: A Simulation Study","volume":"1","author":"Pohar","year":"2004","journal-title":"Metodol. Zv."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.rse.2016.03.021","article-title":"Mapping tree species in tropical seasonal semi-deciduous forests with hyperspectral and multispectral data","volume":"179","author":"Ferreira","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Graves, S.J., Asner, G.P., Martin, R.E., Anderson, C.B., Colgan, M.S., Kalantari, L., and Bohlman, S.A. (2016). Tree Species Abundance Predictions in a Tropical Agricultural Landscape with a Supervised Classification Model and Imbalanced Data. Remote Sens., 8.","DOI":"10.3390\/rs8020161"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/j.isprsjprs.2012.03.005","article-title":"Classification of savanna tree species, in the Greater Kruger National Park region, by integrating hyperspectral and LiDAR data in a Random Forest data mining environment","volume":"69","author":"Naidoo","year":"2012","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Boulicaut, J.-F., Esposito, F., Giannotti, F., and Pedreschi, D. (2004, January 20\u201324). Applying Support Vector Machines to Imbalanced Datasets. Proceedings of the Machine Learning: ECML 2004, Pisa, Italy.","DOI":"10.1007\/b100702"},{"key":"ref_48","unstructured":"Sattar, A., and Kang, B. (2006, January 4\u20138). z-SVM: An SVM for Improved Classification of Imbalanced Data. Proceedings of the AI 2006: Advances in Artificial Intelligence, Hobart, Australia."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1093\/bib\/bbs006","article-title":"Class-imbalanced classifiers for high-dimensional data","volume":"14","author":"Lin","year":"2013","journal-title":"Brief. Bioinform."},{"key":"ref_50","unstructured":"Wu, G., and Chang, E.Y. (2013, January 21\u201324). Adaptive Feature-Space Conformal Transformation for Imbalanced-Data Learning. Proceedings of the 20th International Conference on Machine Learning (ICML-03), Washington, DC, USA."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"2501","DOI":"10.1109\/JSTARS.2014.2346475","article-title":"Single-Species Detection with Airborne Imaging Spectroscopy Data: A Comparison of Support Vector Techniques","volume":"8","author":"Baldeck","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1558","DOI":"10.1016\/j.patcog.2007.11.008","article-title":"Do unbalanced data have a negative effect on LDA?","volume":"41","author":"Xue","year":"2008","journal-title":"Pattern Recognit."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1243092","DOI":"10.1126\/science.1243092","article-title":"Hyperdominance in the Amazonian Tree Flora","volume":"342","author":"Pitman","year":"2013","journal-title":"Science"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1023\/A:1009775025850","article-title":"The influence of soil cover organization on the floristic and structural heterogeneity of a Guianan rain forest","volume":"131","author":"Sabatier","year":"1997","journal-title":"Plant Ecol."},{"key":"ref_55","unstructured":"Traissac, S. (2003). Dynamique Spatiale de Vouacapoua Americana, Arbre de Foret Tropicale Humide a Repartition Agregee, Universit\u00e9 Claude Bernard Lyon 1."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1111\/jvs.12080","article-title":"Birth and life of tree aggregates in tropical forest: Hypotheses on population dynamics of an aggregated shade-tolerant species","volume":"25","author":"Traissac","year":"2014","journal-title":"J. Veg. Sci."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1017\/S0266467411000356","article-title":"A new case of neotropical monodominant forest: Spirotropis longifolia (Leguminosae-Papilionoideae) in French Guiana","volume":"27","author":"Fonty","year":"2011","journal-title":"J. Trop. Ecol."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"2651","DOI":"10.1890\/0012-9658(1999)080[2651:TSDIAU]2.0.CO;2","article-title":"Tree Species Distributions in an Upper Amazonian Forest","volume":"80","author":"Pitman","year":"1999","journal-title":"Ecology"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Marcon, E., Scotti, I., H\u00e9rault, B., Rossi, V., and Lang, G. (2014). Generalization of the Partitioning of Shannon Diversity. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0090289"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1111\/ele.13429","article-title":"Partitioning plant spectral diversity into alpha and beta components","volume":"23","author":"Schweiger","year":"2020","journal-title":"Ecol. Lett."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1111\/gcb.13388","article-title":"Allometric equations for integrating remote sensing imagery into forest monitoring programmes","volume":"23","author":"Jucker","year":"2017","journal-title":"Glob. Chang. Biol."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"1485","DOI":"10.1007\/s00468-013-0896-7","article-title":"Crown allometries are less responsive than stem allometry to tree size and habitat variations in an Indian monsoon forest","volume":"27","author":"Antin","year":"2013","journal-title":"Trees"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1275","DOI":"10.1007\/s00468-012-0703-x","article-title":"Tree shape plasticity in relation to crown exposure","volume":"26","author":"Harja","year":"2012","journal-title":"Trees"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"3460","DOI":"10.1109\/TGRS.2016.2518930","article-title":"Improving Sensor Fusion: A Parametric Method for the Geometric Coalignment of Airborne Hyperspectral and Lidar Data","volume":"54","author":"Brell","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/B978-0-444-63977-6.00013-4","article-title":"Fusion of hyperspectral imaging and LiDAR for forest monitoring","volume":"Volume 32","author":"Tusa","year":"2020","journal-title":"Data Handling in Science and Technology"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1139\/b95-020","article-title":"Phenology of tropical forests: Patterns, causes, and consequences","volume":"73","author":"Reich","year":"1995","journal-title":"Can. J. Bot."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"1440","DOI":"10.1111\/j.1365-2745.2012.02007.x","article-title":"Functional traits and their plasticity predict tropical trees regeneration niche even among species with intermediate light requirements","volume":"100","author":"Laurans","year":"2012","journal-title":"J. Ecol."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1890\/02-4047","article-title":"Leaf demography and phenology in Amazonian rain forest: A census of 40 000 leaves of 23 tree species","volume":"74","author":"Reich","year":"2004","journal-title":"Ecol. Monogr."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"2062","DOI":"10.1016\/j.rse.2011.04.008","article-title":"Variation and directional anisotropy of reflectance at the crown scale\u2014Implications for tree species classification in digital aerial images","volume":"115","author":"Korpela","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_70","unstructured":"Loubry, D. (1994). D\u00e9terminisme du Comportement Ph\u00e9nologique des Arbres en For\u00eat Tropicale Humide de Guyane Fran\u00e7aise (5\u00b0 lat. n.), Universit\u00e9 de Paris 6."},{"key":"ref_71","unstructured":"Saini, M., Christian, B., Joshi, N., Vyas, D., Marpu, P., and Krishnayya, N.S.R. (2020, May 02). Hyperspectral Data Dimensionality Reduction and the Impact of Multi-Seasonal Hyperion EO-1 Imagery on Classification Accuracies of Tropical Forest Species. Available online: https:\/\/www.ingentaconnect.com\/content\/asprs\/pers\/2014\/00000080\/00000008\/art00005."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"1449","DOI":"10.21273\/HORTSCI.21.6.1449","article-title":"A Rapid and Non-destructive Method to Determine Chlorophyll in Intact Leaves","volume":"21","author":"Yadava","year":"1986","journal-title":"HortScience"},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Schlapfer, D., and Richter, R. (2014, January 24\u201327). Evaluation of brefcor BRDF effects correction for HYSPEX, CASI, and APEX imaging spectroscopy data. Proceedings of the 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Lausanne, Switzerland.","DOI":"10.1109\/WHISPERS.2014.8077488"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/10\/1577\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:29:17Z","timestamp":1760174957000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/10\/1577"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,15]]},"references-count":73,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2020,5]]}},"alternative-id":["rs12101577"],"URL":"https:\/\/doi.org\/10.3390\/rs12101577","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,15]]}}}