{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T21:58:06Z","timestamp":1770069486814,"version":"3.49.0"},"reference-count":121,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2020,7,29]],"date-time":"2020-07-29T00:00:00Z","timestamp":1595980800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002749","name":"Belgian Federal Science Policy Office","doi-asserted-by":"publisher","award":["SR\/00\/307;SR\/01\/354"],"award-info":[{"award-number":["SR\/00\/307;SR\/01\/354"]}],"id":[{"id":"10.13039\/501100002749","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Declining urban tree health can affect critical ecosystem services, such as air quality improvement, temperature moderation, carbon storage, and biodiversity conservation. The application of state-of-the-art remote sensing data to characterize tree health has been widely examined in forest ecosystems. However, such application to urban trees has not yet been fully explored\u2014due to the presence of heterogeneous tree species and backgrounds, severely complicating the classification of tree health using remote sensing information. In this study, tree health was represented by a set of field-assessed tree health indicators (defoliation, discoloration, and a combination thereof), which were classified using airborne laser scanning (ALS) and hyperspectral imagery (HSI) with a Random Forest classifier. Different classification scenarios were established aiming at: (i) Comparing the performance of ALS data, HSI and their combination, and (ii) examining to what extent tree species mixtures affect classification accuracy. Our results show that although the predictive power of ALS and HSI indices varied between tree species and tree health indicators, overall ALS indices performed better. The combined use of both ALS and HSI indices results in the highest accuracy, with weighted kappa coefficients (Kc) ranging from 0.53 to 0.79 and overall accuracy ranging from 0.81 to 0.89. Overall, the most informative remote sensing indices indicating urban tree health are ALS indices related to point density, tree size, and shape, and HSI indices associated with chlorophyll absorption. Our results further indicate that a species-specific modelling approach is advisable (Kc points improved by 0.07 on average compared with a mixed species modelling approach). Our study constitutes a basis for future urban tree health monitoring, which will enable managers to guide early remediation management.<\/jats:p>","DOI":"10.3390\/rs12152435","type":"journal-article","created":{"date-parts":[[2020,7,30]],"date-time":"2020-07-30T03:36:38Z","timestamp":1596080198000},"page":"2435","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Urban Tree Health Classification Across Tree Species by Combining Airborne Laser Scanning and Imaging Spectroscopy"],"prefix":"10.3390","volume":"12","author":[{"given":"Dengkai","family":"Chi","sequence":"first","affiliation":[{"name":"Department of Earth and Environmental Sciences, University of Leuven, 3001 Heverlee, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9022-9623","authenticated-orcid":false,"given":"Jeroen","family":"Degerickx","sequence":"additional","affiliation":[{"name":"Flemish Institute for Technological Research-VITO NV, Boeretang 200, 2400 Mol, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0686-6783","authenticated-orcid":false,"given":"Kang","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Earth and Environmental Sciences, University of Leuven, 3001 Heverlee, Belgium"},{"name":"Department of Life Science Engineering, Technical University of Munich (TUM), 85354 Freising, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7875-107X","authenticated-orcid":false,"given":"Ben","family":"Somers","sequence":"additional","affiliation":[{"name":"Department of Earth and Environmental Sciences, University of Leuven, 3001 Heverlee, Belgium"}]}],"member":"1968","published-online":{"date-parts":[[2020,7,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.landurbplan.2014.10.013","article-title":"A review of benefits and challenges in growing street trees in paved urban environments","volume":"134","author":"Mullaney","year":"2015","journal-title":"Landsc. Urban. Plan."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1016\/j.ufug.2012.06.006","article-title":"A systematic quantitative review of urban tree benefits, costs, and assessment methods across cities in different climatic zones","volume":"11","author":"Roy","year":"2012","journal-title":"Urban. For. Urban. Green."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1890\/090220","article-title":"Coupling biogeochemical cycles in urban environments: Ecosystem services, green solutions, and misconceptions","volume":"9","author":"Pataki","year":"2011","journal-title":"Front. Ecol. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"984","DOI":"10.1111\/oik.05874","article-title":"Urbanization drives unique latitudinal patterns of insect herbivory and tree condition","volume":"128","author":"Just","year":"2019","journal-title":"Oikos"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"597","DOI":"10.1111\/j.1466-8238.2010.00608.x","article-title":"Increased water-use efficiency during the 20th century did not translate into enhanced tree growth","volume":"20","author":"Canadell","year":"2011","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"135","DOI":"10.48044\/jauf.2009.024","article-title":"Soil moisture and aeration beneath pervious and impervious pavements","volume":"35","author":"Morgenroth","year":"2009","journal-title":"Arboric. Urban. For."},{"key":"ref_7","first-page":"203","article-title":"Water as a limiting factor in the development of urban trees","volume":"16","author":"Clark","year":"1990","journal-title":"J. Arboric."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Dale, A.G., and Frank, S.D. (2017). Warming and drought combine to increase pest insect fitness on urban trees. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0173844"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"895","DOI":"10.1016\/j.ecolind.2018.08.047","article-title":"Foliar optical traits indicate that sealed planting conditions negatively affect urban tree health","volume":"95","author":"Yu","year":"2018","journal-title":"Ecol. Indic."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"596","DOI":"10.1080\/02827589908540825","article-title":"Soil compaction and growth of Woody plants","volume":"14","author":"Kozlowski","year":"1999","journal-title":"Scand. J. For. Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"158764","DOI":"10.1155\/2013\/158764","article-title":"Contaminated Sites in Europe: Review of the Current Situation Based on Data Collected through a European Network","volume":"2013","author":"Panagos","year":"2013","journal-title":"J. Environ. Public Health"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/j.envint.2015.12.017","article-title":"Heavy metals in agricultural soils of the European Union with implications for food safety","volume":"88","author":"Hermann","year":"2016","journal-title":"Environ. Int."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1912","DOI":"10.1016\/j.envpol.2018.09.053","article-title":"Vegetation reflectance spectroscopy for biomonitoring of heavy metal pollution in urban soils","volume":"243","author":"Yu","year":"2018","journal-title":"Environ. Pollut."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1146\/annurev-arplant-042110-103829","article-title":"The effects of tropospheric ozone on net primary productivity and implications for climate change","volume":"63","author":"Ainsworth","year":"2012","journal-title":"Annu. Rev. Plant. Biol."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Beck, I., Jochner, S., Gilles, S., McIntyre, M., Buters, J.T.M., Schmidt-Weber, C., Behrendt, H., Ring, J., Menzel, A., and Traidl-Hoffmann, C. (2013). High environmental ozone levels lead to enhanced allergenicity of birch pollen. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0080147"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/S0269-7491(99)00285-7","article-title":"Relationship between leaf life-span and photosynthetic activity of Quercus ilex in polluted urban areas (Rome)","volume":"110","author":"Gratani","year":"2000","journal-title":"Environ. Pollut."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1016\/j.sbspro.2016.10.237","article-title":"Roadside tree management in selected local authorities for public safety","volume":"234","author":"Hasan","year":"2016","journal-title":"Procedia. Soc. Behav. Sci."},{"key":"ref_18","unstructured":"Lonsdale, D. (1999). Principles of Tree Hazard Assessment and Management, Stationery Office Ltd., Publications Centre."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.ufug.2018.01.010","article-title":"Remote sensing of bark beetle damage in urban forests at individual tree level using a novel hyperspectral camera from UAV and aircraft","volume":"30","author":"Honkavaara","year":"2018","journal-title":"Urban. For. Urban. Green."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1080\/03071375.2009.9747570","article-title":"Hazard tree identification by visual tree assessment (VTA): Scientifically solid and practically approved","volume":"32","author":"Fink","year":"2009","journal-title":"Arboric. J."},{"key":"ref_21","first-page":"W2","article-title":"Remote Sensing of Forest Health","volume":"36","author":"Solberg","year":"2004","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_22","unstructured":"Lakatos, F., Mirtchev, S., Mehmeti, A., and Shabanaj, H. (2014). Manual for Visual Assessment of Forest Crown Condition, FAO."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1487","DOI":"10.1093\/treephys\/26.11.1487","article-title":"Assessment of oak forest condition based on leaf biochemical variables and chlorophyll fluorescence","volume":"26","author":"Rossini","year":"2006","journal-title":"Tree Physiol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1080\/00049158.2008.10675034","article-title":"Forest health surveillance in Victoria","volume":"71","author":"Smith","year":"2008","journal-title":"Aust. Forest."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1111\/j.1326-6756.2004.00432.x","article-title":"Assessment and monitoring of damage from insects in Australian eucalypt forests and commercial plantations","volume":"43","author":"Stone","year":"2004","journal-title":"Aust. J. Entomol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1016\/j.foreco.2017.08.052","article-title":"Airborne laser scanning and tree crown fragmentation metrics for the assessment of Phytophthora ramorum infected larch forest stands","volume":"404","author":"Barnes","year":"2017","journal-title":"For. Ecol. Manag."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1016\/j.rse.2013.09.014","article-title":"Assessing the potential of hyperspectral imagery to map bark beetle-induced tree mortality","volume":"140","author":"Fassnacht","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.foreco.2013.07.043","article-title":"Forecasting potential bark beetle outbreaks based on spruce forest vitality using hyperspectral remote-sensing techniques at different scales","volume":"308","author":"Lausch","year":"2013","journal-title":"For. Ecol. Manag."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.rse.2018.06.008","article-title":"Mapping canopy defoliation by herbivorous insects at the individual tree level using bi-temporal airborne imaging spectroscopy and LiDAR measurements","volume":"215","author":"Meng","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1016\/j.rse.2016.10.014","article-title":"Mapping individual tree health using full-waveform airborne laser scans and imaging spectroscopy: A case study for a floodplain eucalypt forest","volume":"187","author":"Shendryk","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.rse.2006.03.012","article-title":"Assessment of quickbird high spatial resolution imagery to detect red attack damage due to mountain pine beetle infestation","volume":"103","author":"Coops","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2431","DOI":"10.1016\/j.rse.2010.05.018","article-title":"Assessing canopy mortality during a mountain pine beetle outbreak using GeoEye-1 high spatial resolution satellite data","volume":"114","author":"Dennison","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"4427","DOI":"10.1080\/01431160802566439","article-title":"Mapping white bark pine mortality caused by a mountain pine beetle outbreak with high spatial resolution satellite imagery","volume":"30","author":"Hicke","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.foreco.2011.10.008","article-title":"Managing drought-induced mortality in Pinus radiata plantations under climate change conditions: A local approach using digital camera data","volume":"265","author":"Stone","year":"2012","journal-title":"For. Ecol. Manag."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1080\/01431161.2011.639400","article-title":"Dieback classification modelling using high-resolution digital multispectral imagery and in situ assessments of crown condition","volume":"3","author":"Evans","year":"2012","journal-title":"Remote Sens. Lett."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1093\/jee\/tou015","article-title":"A 10-year assessment of hemlock decline in the Catskill mountain region of New York state using hyperspectral remote sensing techniques","volume":"108","author":"Hanavan","year":"2015","journal-title":"J. Econ. Entomol."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"L\u00f3pez-L\u00f3pez, M., Calder\u00f3n, R., Gonz\u00e1lez-Dugo, V., Zarco-Tejada, P.J., and Fereres, E. (2016). Early Detection and Quantification of Almond Red Leaf Blotch Using High-Resolution Hyperspectral and Thermal Imagery. Remote Sens., 8.","DOI":"10.3390\/rs8040276"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"15467","DOI":"10.3390\/rs71115467","article-title":"Using UAV-based photogrammetry and hyperspectral imaging for mapping bark beetle damage at tree level","volume":"7","author":"Honkavaara","year":"2015","journal-title":"Remote Sens."},{"key":"ref_39","first-page":"270","article-title":"Spectral mixture analysis to monitor defoliation in mixed-aged Eucalyptus globulus Labill plantations in southern Australia using Landsat 5-TM and EO-1 Hyperion data","volume":"12","author":"Somers","year":"2010","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2665","DOI":"10.3390\/rs2122665","article-title":"Classification of defoliated trees using tree-level airborne laser scanning data combined with aerial images","volume":"2","author":"Kantola","year":"2010","journal-title":"Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1016\/j.rse.2006.03.001","article-title":"Mapping defoliation during a severe insect attack on Scots pine using airborne laser scanning","volume":"102","author":"Solberg","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1220","DOI":"10.3390\/rs5031220","article-title":"Area-based mapping of defoliation of Scots pine stands using airborne scanning LiDAR","volume":"5","author":"Vastaranta","year":"2013","journal-title":"Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Barnes, C., Balzter, H., Barrett, K., Eddy, J., Milner, S., and Su\u00e1rez, J.C. (2017). Individual tree crown delineation from airborne laser scanning for diseased larch forest stands. Remote Sens., 9.","DOI":"10.3390\/rs9030231"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1016\/S0034-4257(03)00008-7","article-title":"Detection and analysis of individual leaf-off tree crowns in small footprint, high sampling density lidar data from the eastern deciduous forest in North America","volume":"85","author":"Brandtberg","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"126634","DOI":"10.1016\/j.ufug.2020.126634","article-title":"Street tree health from space? An evaluation using WorldView-3 data and the Washington, D.C. Street Tree Spatial Database","volume":"49","author":"Fang","year":"2020","journal-title":"Urban. For. Urban. Green."},{"key":"ref_46","first-page":"26","article-title":"Urban tree health assessment using airborne hyperspectral and LiDAR imagery","volume":"73","author":"Degerickx","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1007\/s11252-005-4867-7","article-title":"Tree health mapping with multispectral remote sensing data at UC Davis, California","volume":"8","author":"Xiao","year":"2005","journal-title":"Urban. Ecosyst."},{"key":"ref_48","unstructured":"Biesemans, J., Sterckx, S., Knaeps, E., Vreys, K., Adriaensen, S., and Hooy, J. (2007, January 23\u201325). Image Processing Workflows for Airborne Remote. Proceedings of the 5th EARSeL Work, Imaging Spectroscopy, Bruges, Belgium."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1016\/j.isprsjprs.2009.01.006","article-title":"Calibration facility for airborne imaging spectrometers","volume":"64","author":"Gege","year":"2009","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Berk, A., Anderson, G.P., Bernstein, L.S., Acharya, P.K., Dothe, H., Matthew, M.W., Adler-Golden, S.M., Chetwynd, J.H., Richtsmeier, S.C., and Pukall, B. (1999). MODTRAN4 radiative transfer modeling for atmospheric correction. Proc. SPIE 3756, Optical Spectroscopic Techniques and Instrumentation for Atmospheric and Space Research III, SPIE.","DOI":"10.1117\/12.366388"},{"key":"ref_51","first-page":"16","article-title":"Atmospheric correction of APEX hyperspectral data","volume":"20","author":"Sterckx","year":"2016","journal-title":"Misc. Geogr."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"12837","DOI":"10.3390\/rs61212837","article-title":"A versatile, production-oriented approach to high-resolution tree-canopy mapping in urban and suburban landscapes using GEOBIA and data fusion","volume":"6","author":"MacFaden","year":"2014","journal-title":"Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Zhao, Y., Hao, Y., Zhen, Z., and Quan, Y. (2017). A Region-Based Hierarchical Cross-Section Analysis for Individual Tree Crown Delineation Using ALS Data. Remote Sens., 9.","DOI":"10.3390\/rs9101084"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.rse.2018.10.005","article-title":"Species-related single dead tree detection using multi-temporal ALS data and CIR imagery","volume":"219","author":"Lisiewicz","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"3097","DOI":"10.1080\/01431160500217277","article-title":"Radiometric correction in laser scanning","volume":"27","author":"Coren","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/S0924-2716(99)00015-5","article-title":"Airborne laser scanning: Basic relations and formulas","volume":"54","author":"Baltsavias","year":"1999","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"816","DOI":"10.1016\/j.rse.2009.11.021","article-title":"Estimating biomass carbon stocks for a Mediterranean forest in central Spain using LiDAR height and intensity data","volume":"114","author":"Chuvieco","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1148","DOI":"10.1016\/j.rse.2009.02.010","article-title":"Capturing tree crown formation through implicit surface reconstruction using airborne lidar data","volume":"113","author":"Kato","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"S99","DOI":"10.5589\/m13-027","article-title":"Predicting live and dead tree basal area of bark beetle affected forests from discrete-return lidar","volume":"39","author":"Bright","year":"2013","journal-title":"Can. J. Remote. Sens."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1575","DOI":"10.1016\/j.rse.2009.03.017","article-title":"Tree species differentiation using intensity data derived from leaf-on and leaf-off airborne laser scanner data","volume":"113","author":"Kim","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/S0034-4257(00)00113-9","article-title":"Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance","volume":"74","author":"Daughtry","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1093\/treephys\/23.1.23","article-title":"Chlorophyll content in eucalypt vegetation at the leaf and canopy scales as derived from high resolution spectral data","volume":"23","author":"Coops","year":"2003","journal-title":"Tree Physiol."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"416","DOI":"10.1016\/S0034-4257(02)00018-4","article-title":"Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture","volume":"84","author":"Haboudane","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/0034-4257(95)00132-K","article-title":"Comparison of broad-band and narrow-band red and near-infrared vegetation indices","volume":"54","author":"Elvidge","year":"1995","journal-title":"Remote Sens. Environ."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"2691","DOI":"10.1080\/014311697217558","article-title":"Signature analysis of leaf reflectance spectra: Algorithm development for remote sensing of chlorophyll","volume":"18","author":"Gitelson","year":"1997","journal-title":"Int. J. Remote Sens."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"5403","DOI":"10.1080\/0143116042000274015","article-title":"The MERIS terrestrial chlorophyll index","volume":"25","author":"Dash","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_67","first-page":"165","article-title":"Estimating chlorophyll content of crops from hyperspectral data using a normalized area over reflectance curve (NAOC)","volume":"12","author":"Delegido","year":"2010","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_68","unstructured":"Barnes, E.M., Clarke, T.R., Richards, S.E., Colaizzi, P.D., Haberl, J., Kostrzewski, M., Waller, P., Choi, C., Riley, E., and Thompson, T. (2000, January 16\u201319). Coincident detection of crop water stress, nitrogen status and canopy density using ground based multispectral data. Proceedings of the Fifth International Conference on Precision Agriculture, Bloomington, IN, USA."},{"key":"ref_69","unstructured":"Rouse, J.W., Hass, R.H., Schell, J.A., and Deering, D.W. (1973, January 10\u201314). Monitoring vegetation systems in the Great Plains with ERTS. Proceedings of the Third Earth Resources Technology Satellite-1 Symposium, Washington, DC, USA."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1080\/014311698215919","article-title":"Spectral indices for estimating photosynthetic pigment concentrations: A test using senescent tree leaves","volume":"19","author":"Blackburn","year":"1998","journal-title":"Int. J. Remote Sens."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/S0034-4257(98)00046-7","article-title":"Remote sensing of chlorophyll a, chlorophyll b, chlorophyll a+b, and total carotenoid content in eucalyptus leaves","volume":"66","author":"Datt","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"1563","DOI":"10.1080\/01431169308953986","article-title":"Red edge spectral measurements from sugar maple leaves","volume":"14","author":"Vogelmann","year":"1993","journal-title":"Int. J. Remote Sens."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"1491","DOI":"10.1109\/36.934080","article-title":"Scaling-up and model inversion methods with narrowband optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data","volume":"39","author":"Miller","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1080\/01431168308948546","article-title":"The red edge of plant leaf reflectance","volume":"4","author":"Horler","year":"1983","journal-title":"Int. J. Remote Sens."},{"key":"ref_75","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_76","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1080\/01431169308904370","article-title":"In vivo spectroscopy and internal optics of leaves as a basis for remote sensing of vegetation","volume":"14","author":"Buschman","year":"1993","journal-title":"Int. J. Remote Sens."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/0034-4257(95)00186-7","article-title":"Optimization of soil-adjusted vegetation indices","volume":"55","author":"Rondeaux","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1034\/j.1399-3054.1999.106119.x","article-title":"Non-destructive optical detection of pigment changes during leaf senescence and fruit ripening","volume":"106","author":"Merzlyak","year":"1999","journal-title":"Physiol. Plant."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"L11402","DOI":"10.1029\/2006GL026457","article-title":"Three-band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves","volume":"33","author":"Gitelson","year":"2006","journal-title":"Geophys. Res. Lett."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/0034-4257(92)90089-3","article-title":"Ratio analysis of reflectance spectra (RARS): An algorithm for the remote estimation of the concentrations of chlorophyll a, chlorophyll b, and carotenoids in soybean leaves","volume":"39","author":"Chappelle","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1562\/0031-8655(2002)075<0272:ACCIPL>2.0.CO;2","article-title":"Assessing carotenoid content in plant leaves with reflectance spectroscopy","volume":"75","author":"Gitelson","year":"2002","journal-title":"Photochem. Photobiol."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1562\/0031-8655(2001)074<0038:OPANEO>2.0.CO;2","article-title":"Optical properties and nondestructive estimation of anthocyanin content in plant leaves","volume":"74","author":"Gitelson","year":"2001","journal-title":"Photochem. Photobiol."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/0034-4257(92)90059-S","article-title":"A narrow-wave band spectral index that tracks diurnal changes in photosynthetic efficiency","volume":"41","author":"Gamon","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"2360","DOI":"10.1016\/j.rse.2011.04.036","article-title":"Assessing structural effects on PRI for stress detection in conifer forests","volume":"115","author":"Morales","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/0034-4257(89)90046-1","article-title":"Detection of changes in leaf water-content using near infrared and middle-infrared reflectances","volume":"30","author":"Hunt","year":"1989","journal-title":"Remote Sens. Environ."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1023\/A:1007033503276","article-title":"Reflectance indices indicative of changes in water and pigment contents of peanut and wheat leaves","volume":"36","author":"Inoue","year":"1999","journal-title":"Photosynthetica"},{"key":"ref_87","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_88","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_89","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1109\/36.134076","article-title":"Atmospherically resistant vegetation index (ARVI) for EOS-MODIS","volume":"30","author":"Kaufman","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1016\/S0034-4257(96)00112-5","article-title":"A comparison of vegetation indices over a global set of TM images for EO -MODIS","volume":"59","author":"Huete","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/S0034-4257(01)00289-9","article-title":"Novel algorithms for remote estimation of vegetation fraction","volume":"80","author":"Gitelson","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"3762","DOI":"10.1016\/j.rse.2008.05.003","article-title":"A near-infrared narrow-waveband ratio to determine leaf area index in orch-ards","volume":"112","author":"Delalieux","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_93","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":"Rougean","year":"1995","journal-title":"Remote Sens. Environ."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1080\/07038992.1996.10855178","article-title":"Evaluation of vegetation indices and modified simple ratio for boreal applications","volume":"22","author":"Chen","year":"1996","journal-title":"Can. J. Remote Sens."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/0034-4257(94)90134-1","article-title":"A modified soil adjusted vegetation index","volume":"48","author":"Qi","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_96","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_97","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1016\/S0176-1617(96)80081-2","article-title":"Detection of vegetation stress via a new high resolution fluorescence imaging system","volume":"148","author":"Lichtenhaler","year":"1996","journal-title":"J. Plant. Physiol."},{"key":"ref_98","first-page":"121","article-title":"Remote estimation of phytoplankton density in productive waters","volume":"55","author":"Gitelson","year":"2000","journal-title":"Arch. Hydrobiol."},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/j.rse.2013.07.031","article-title":"High-resolution airborne hyperspectral and thermal imagery for early detection of Verticillium wilt of olive using fluorescence, temperature and narrow-band spectral indices","volume":"139","author":"Lucena","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1016\/j.rse.2005.09.002","article-title":"Assessing vineyard condition with hyperspectral indices: Leaf and canopy reflectance simulation in a row-structured discontinuous canopy","volume":"99","author":"Miller","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/0034-4257(94)90079-5","article-title":"Early detection of plant stress by digital imaging within narrow stress-sensitive wavebands","volume":"50","author":"Carter","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.rse.2012.09.019","article-title":"Development of spectral indices for detecting and identifying plant diseases","volume":"128","author":"Mahlein","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_103","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_104","doi-asserted-by":"crossref","unstructured":"Zhang, Y., and Lin, Y. (2013, January 25\u201326). The classification of environmental audio with ensemble learning. Proceedings of the 2013 International Conference on Advanced Computer Science and Electronics Information (ICACSEI 2013), Beijing, China.","DOI":"10.2991\/icacsei.2013.93"},{"key":"ref_105","doi-asserted-by":"crossref","unstructured":"D\u00edaz-Uriarte, R., and Alvarez de Andr\u00e9s, S. (2006). Gene selection and classification of microarray data using random forest. BMC Bioinform., 7.","DOI":"10.1186\/1471-2105-7-3"},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"1202","DOI":"10.1038\/nbt.2877","article-title":"A community effort to assess and improve drug sensitivity prediction algorithms","volume":"32","author":"Costello","year":"2014","journal-title":"Nat. Biotechnol."},{"key":"ref_107","unstructured":"Chen, C., Liaw, A., and Breiman, L. (2004). Using Random Forest to Learn Imbalanced Data, Department of Statistics, University of California."},{"key":"ref_108","doi-asserted-by":"crossref","first-page":"825","DOI":"10.1016\/j.eswa.2006.10.022","article-title":"Comparison of classification accuracy using Cohen\u2019s Weighted Kappa","volume":"34","year":"2008","journal-title":"Expert Syst. Appl."},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2017.07.007","article-title":"Assessing very high resolution UAV imagery for monitoring forest health during a simulated disease outbreak","volume":"131","author":"Dash","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"4407","DOI":"10.1080\/01431161.2011.552923","article-title":"Death to kappa: Birth of quantity disagreement and allocation disagreement for accuracy assessment","volume":"32","author":"Pontius","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"11630","DOI":"10.1016\/j.rse.2019.111630","article-title":"Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification","volume":"239","author":"Foody","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"2838","DOI":"10.3390\/rs5062838","article-title":"The performance of random forests in an operational setting for large area sclerophyll forest classification","volume":"5","author":"Mellor","year":"2013","journal-title":"Remote Sens."},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"2249","DOI":"10.1016\/j.csda.2007.08.015","article-title":"Empirical characterization of random forest variable importance measures","volume":"52","author":"Archer","year":"2008","journal-title":"Comput. Stat. Data Anal."},{"key":"ref_114","doi-asserted-by":"crossref","first-page":"2999","DOI":"10.1016\/j.rse.2008.02.011","article-title":"Evaluation of Random Forest and Adaboost tree-based ensemble classification and spectral band selection for ecotope mapping using airborne hyperspectral imagery","volume":"112","author":"Chan","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1109\/TSMCB.2006.883267","article-title":"Wrapper\u2013filter feature selection algorithm using a memetic framework","volume":"37","author":"Zhu","year":"2007","journal-title":"IEEE Trans. Syst. Man Cybern. B Cybern."},{"key":"ref_116","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/S0004-3702(97)00043-X","article-title":"Wrappers for feature subset selection","volume":"97","author":"Kohavi","year":"1997","journal-title":"Artif. Intell."},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"497","DOI":"10.5589\/m10-005","article-title":"Assessing differences in tree and stand structure following beetle infestation using lidar data","volume":"35","author":"Coops","year":"2009","journal-title":"Can. J. Remote. Sens."},{"key":"ref_118","doi-asserted-by":"crossref","first-page":"065004","DOI":"10.1088\/1748-9326\/aa6ade","article-title":"Patterns of Canopy and Surface Layer Consumption in a Boreal Forest Fire from Repeat Airborne Lidar","volume":"12","author":"Alonzo","year":"2017","journal-title":"Environ. Res. Lett."},{"key":"ref_119","unstructured":"Yao, W., Krzystek, P., and Heurich, M. (September, January 25). Identifying standing dead trees in forest areas based on 3D single tree detection from full waveform Lidar data. Proceedings of the ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Melbourne, Australia."},{"key":"ref_120","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/j.isprsjprs.2018.01.017","article-title":"Understanding the temporal dimension of the red-edge spectral region for forest decline detection using high-resolution hyperspectral and Sentinel-2a imagery","volume":"137","author":"Hornero","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_121","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.rse.2014.03.018","article-title":"Urban tree species mapping using hyperspectral and lidar data fusion","volume":"148","author":"Alonzo","year":"2014","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/15\/2435\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:52:39Z","timestamp":1760176359000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/15\/2435"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,29]]},"references-count":121,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2020,8]]}},"alternative-id":["rs12152435"],"URL":"https:\/\/doi.org\/10.3390\/rs12152435","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,7,29]]}}}