{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T16:13:07Z","timestamp":1775664787189,"version":"3.50.1"},"reference-count":76,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2018,11,30]],"date-time":"2018-11-30T00:00:00Z","timestamp":1543536000000},"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>Quantitative equivalent water thickness on canopy level (EWTcanopy) is an important land surface variable and retrieving EWTcanopy from remote sensing has been targeted by many studies. However, the effect of radiative penetration into the canopy has not been fully understood. Therefore, in this study the Beer-Lambert law is applied to inversely determine water content information in the 930 to 1060 nm range of canopy reflectance from measured winter wheat and corn spectra collected in 2015, 2017, and 2018. The spectral model was calibrated using a look-up-table (LUT) of 50,000 PROSPECT spectra. Internal model validation was performed using two leaf optical properties datasets (LOPEX93 and ANGERS). Destructive in-situ measurements of water content were collected separately for leaves, stalks, and fruits. Correlation between measured and modelled water content was most promising for leaves and ears in case of wheat, reaching coefficients of determination (R2) up to 0.72 and relative RMSE (rRMSE) of 26% and in case of corn for the leaf fraction only (R2 = 0.86, rRMSE = 23%). These findings indicate that, depending on the crop type and its structure, different parts of the canopy are observed by optical sensors. The results from the Munich-North-Isar test sites indicated that plant compartment specific EWTcanopy allows us to deduce more information about the physical meaning of model results than from equivalent water thickness on leaf level (EWT) which is upscaled to canopy water content (CWC) by multiplication of the leaf area index (LAI). Therefore, it is suggested to collect EWTcanopy data and corresponding reflectance for different crop types over the entire growing cycle. Nevertheless, the calibrated model proved to be transferable in time and space and thus can be applied for fast and effective retrieval of EWTcanopy in the scope of future hyperspectral satellite missions.<\/jats:p>","DOI":"10.3390\/rs10121924","type":"journal-article","created":{"date-parts":[[2018,11,30]],"date-time":"2018-11-30T12:13:17Z","timestamp":1543579997000},"page":"1924","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":58,"title":["Physically-Based Retrieval of Canopy Equivalent Water Thickness Using Hyperspectral Data"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7180-2356","authenticated-orcid":false,"given":"Matthias","family":"Wocher","sequence":"first","affiliation":[{"name":"Department of Geography, Ludwig-Maximilians-University Munich, Luisenstra\u00dfe 37, 80333 Munich, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0784-7717","authenticated-orcid":false,"given":"Katja","family":"Berger","sequence":"additional","affiliation":[{"name":"Department of Geography, Ludwig-Maximilians-University Munich, Luisenstra\u00dfe 37, 80333 Munich, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8911-9064","authenticated-orcid":false,"given":"Martin","family":"Danner","sequence":"additional","affiliation":[{"name":"Department of Geography, Ludwig-Maximilians-University Munich, Luisenstra\u00dfe 37, 80333 Munich, Germany"}]},{"given":"Wolfram","family":"Mauser","sequence":"additional","affiliation":[{"name":"Department of Geography, Ludwig-Maximilians-University Munich, Luisenstra\u00dfe 37, 80333 Munich, Germany"}]},{"given":"Tobias","family":"Hank","sequence":"additional","affiliation":[{"name":"Department of Geography, Ludwig-Maximilians-University Munich, Luisenstra\u00dfe 37, 80333 Munich, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2018,11,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1093\/treephys\/9.1-2.147","article-title":"Forest-BGC, a general model of forest ecosystem processes for regional applications. Ii. Dynamic carbon allocation and nitrogen budgets","volume":"9","author":"Running","year":"1991","journal-title":"Tree Physiol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1007\/BF00151173","article-title":"Regional hydrologic and carbon balance responses of forests resulting from potential climate change","volume":"19","author":"Running","year":"1991","journal-title":"Clim. Chang."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"023520","DOI":"10.1117\/1.2937937","article-title":"Using imaging and non-imaging spectroradiometer data for the remote detection of vegetation water content","volume":"2","author":"Vohland","year":"2008","journal-title":"J. Appl. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"3934","DOI":"10.3390\/rs70403934","article-title":"Using a remote sensing-supported hydro-agroecological model for field-scale simulation of heterogeneous crop growth and yield: Application for wheat in central Europe","volume":"7","author":"Hank","year":"2015","journal-title":"Remote Sens."},{"key":"ref_5","first-page":"119","article-title":"Estimating canopy water content using hyperspectral remote sensing data","volume":"12","author":"Clevers","year":"2010","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1887","DOI":"10.1080\/01431169308954010","article-title":"The reflectance at the 950\u2013970 nm region as an indicator of plant water status","volume":"14","author":"Filella","year":"1993","journal-title":"Int. J. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2869","DOI":"10.1080\/014311697217396","article-title":"Estimation of plant water concentration by the reflectance water index wi (r900\/r970)","volume":"18","author":"Pinol","year":"1997","journal-title":"Int. J. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Hank, T.B., Berger, K., Bach, H., Clevers, J.G.P.W., Gitelson, A., Zarco-Tejada, P., and Mauser, W. (2018). Spaceborne imaging spectroscopy for sustainable agriculture: Contributions and challenges. Surv. Geophys.","DOI":"10.1007\/s10712-018-9492-0"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/0034-4257(80)90096-6","article-title":"Remote sensing of leaf water content in the near infrared","volume":"10","author":"Tucker","year":"1980","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1080\/01431169208904049","article-title":"High-spectral resolution data for determining leaf water content","volume":"13","author":"Danson","year":"1992","journal-title":"Int. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3531","DOI":"10.1364\/AO.32.003531","article-title":"Refractive indices of water and ice in the 0.65- to 2.5-\u03bcm spectral range","volume":"32","author":"Kou","year":"1993","journal-title":"Appl. Opt."},{"key":"ref_12","first-page":"77","article-title":"The influence of soil salinity, growth form, and leaf moisture on the spectral radiance of spartina alterniflora canopies","volume":"49","author":"Hardisky","year":"1983","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1016\/0034-4257(87)90094-0","article-title":"Measurement of leaf relative water content by infrared reflectance","volume":"22","author":"Hunt","year":"1987","journal-title":"Remote Sens. Environ."},{"key":"ref_14","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- and middle-infrared reflectances","volume":"30","author":"Hunt","year":"1989","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/S0034-4257(96)00067-3","article-title":"NDWI\u2014A normalized difference water index for remote sensing of vegetation liquid water from space","volume":"58","author":"Gao","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"909","DOI":"10.1071\/BT98042","article-title":"Remote sensing of water content in eucalyptus leaves","volume":"47","author":"Datt","year":"1999","journal-title":"Aust. J. Bot."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"S56","DOI":"10.1016\/j.rse.2008.01.026","article-title":"Prospect+SAIL models: A review of use for vegetation characterization","volume":"113","author":"Jacquemoud","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/0034-4257(82)90057-8","article-title":"Spectral reflectance of partly transmitting leaves: Laboratory measurements and mathematical modeling","volume":"12","author":"Lillesaeter","year":"1982","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1093\/oxfordjournals.aob.a084373","article-title":"The penetration of solar radiation through leaf canopies of different structure","volume":"34","author":"Newton","year":"1970","journal-title":"Ann. Bot."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/0021-8634(91)80032-A","article-title":"Wavelength selection for near-infrared reflectance moisture meters","volume":"49","author":"Bull","year":"1991","journal-title":"J. Agric. Eng. Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"526","DOI":"10.1016\/S0034-4257(02)00151-7","article-title":"Estimation of vegetation water content and photosynthetic tissue area from spectral reflectance: A comparison of indices based on liquid water and chlorophyll absorption features","volume":"84","author":"Sims","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1679","DOI":"10.1016\/j.agrformet.2008.05.020","article-title":"Estimating crop water stress with ETM+ NIR and SWIR data","volume":"148","author":"Ghulam","year":"2008","journal-title":"Agric. For. Meteorol."},{"key":"ref_23","first-page":"388","article-title":"Using spectral information from the NIR water absorption features for the retrieval of canopy water content","volume":"10","author":"Clevers","year":"2008","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Cernicharo, J., Verger, A., and Camacho, F. (2013). Empirical and physical estimation of canopy water content from CHRIS\/PROBA data. Remote Sens., 5.","DOI":"10.3390\/rs5105265"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/j.isprsjprs.2015.05.005","article-title":"Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties\u2014A review","volume":"108","author":"Verrelst","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/S0034-4257(01)00191-2","article-title":"Detecting vegetation leaf water content using reflectance in the optical domain","volume":"77","author":"Ceccato","year":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/S0034-4257(02)00197-9","article-title":"Water content estimation in vegetation with MODIS reflectance data and model inversion methods","volume":"85","author":"Rueda","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2514","DOI":"10.1016\/j.rse.2007.11.014","article-title":"Remote sensing of vegetation water content from equivalent water thickness using satellite imagery","volume":"112","author":"Yilmaz","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/0034-4257(91)90009-U","article-title":"Potentials and limits of vegetation indices for LAI and APAR assessment","volume":"35","author":"Baret","year":"1991","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.rse.2006.07.016","article-title":"Combining vegetation index and model inversion methods for the extraction of key vegetation biophysical parameters using terra and aqua MODIS reflectance data","volume":"106","author":"Houborg","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Verrelst, J., Malenovsk\u00fd, Z., Van der Tol, C., Camps-Valls, G., Gastellu-Etchegorry, J.-P., Lewis, P., North, P., and Moreno, J. (2018). Quantifying vegetation biophysical variables from imaging spectroscopy data: A review on retrieval methods. Surv. Geophys.","DOI":"10.1007\/s10712-018-9478-y"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1016\/S0034-4257(00)00139-5","article-title":"Comparison of four radiative transfer models to simulate plant canopies reflectance: Direct and inverse mode","volume":"74","author":"Jacquemoud","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.rse.2011.10.035","article-title":"Spatially constrained inversion of radiative transfer models for improved LAI mapping from future sentinel-2 imagery","volume":"120","author":"Atzberger","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1429","DOI":"10.1016\/j.actaastro.2009.03.077","article-title":"The PRISMA payload optomechanical design, a high performance instrument for a new hyperspectral mission","volume":"65","author":"Labate","year":"2009","journal-title":"Acta Astronaut."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1016\/j.rse.2015.06.012","article-title":"An introduction to the NASA hyperspectral InfraRed imager (HyspIRI) mission and preparatory activities","volume":"167","author":"Lee","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Qian, S.-E. (2015). SHALOM\u2014A commercial hyperspectral space mission. Optical Payloads for Space Missions, John Wiley & Sons.","DOI":"10.1002\/9781118945179"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Nieke, J., and Rast, M. (2018, January 22\u201327). Towards the copernicus hyperspectral imaging mission for the environment (CHIME). Proceedings of the IGGARS 2018, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8518384"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"8830","DOI":"10.3390\/rs70708830","article-title":"The enmap spaceborne imaging spectroscopy mission for earth observation","volume":"7","author":"Guanter","year":"2015","journal-title":"Remote Sens."},{"key":"ref_39","unstructured":"Green, O.R. (1991). An inversion algorithm for retrieval of atmospheric and leaf water absorption from AVIRIS radiance with compensation for atmospheric scattering. Third Airborne Visible\/Infrared Imaging Spectrometer (AVIRIS) Workshop, NASA."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Green, R.O., Conel, J.E., and Roberts, D.A. (1993, January 25\u201329). Estimation of aerosol optical depth, pressure elevation, water vapor, and calculation of apparent surface reflectance from radiance measured by the airborne visible\/infrared imaging spectrometer (AVIRIS). Proceedings of the Summaries of the 4th Annual JPL Airborne Geoscience Workshop, AVJRIS Workshop, Washington, DC, USA.","DOI":"10.1117\/12.157054"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1560\/IJPS.60.1-2.9","article-title":"Estimating canopy water content from spectroscopy","volume":"60","author":"Ustin","year":"2012","journal-title":"Isr. J. Plant Sci."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Qu, J., Powell, A., and Sivakumar, M.V.K. (2013). Remote sensing of leaf, canopy, and vegetation water contents for satellite environmental data records. Satellite-Based Applications on Climate Change, Springer.","DOI":"10.1007\/978-94-007-5872-8"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/S0034-4257(70)80021-9","article-title":"Physical and physiological basis for the reflectance of visible and near-infrared radiation from vegetation","volume":"1","author":"Knipling","year":"1970","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"916","DOI":"10.1002\/j.1537-2197.1991.tb14495.x","article-title":"Primary and secondary effects of water content on the spectral reflectance of leaves","volume":"78","author":"Carter","year":"1991","journal-title":"Am. J. Bot."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"3549","DOI":"10.1029\/JD095iD04p03549","article-title":"Column atmospheric water vapor and vegetation liquid water retrievals from airborne imaging spectrometer data","volume":"95","author":"Gao","year":"1990","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/0034-4257(95)00039-4","article-title":"Retrieval of equivalent water thickness and information related to biochemical components of vegetation canopies from AVIRIS data","volume":"52","author":"Gao","year":"1995","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Green, R.O., Painter, T.H., Roberts, D.A., and Dozier, J. (2006). Measuring the expressed abundance of the three phases of water with an imaging spectrometer over melting snow. Water Resour. Res., 42.","DOI":"10.1029\/2005WR004509"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.rse.2015.02.010","article-title":"Atmospheric correction for global mapping spectroscopy: ATREM advances for the HyspIRI preparatory campaign","volume":"167","author":"Thompson","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_49","first-page":"67","article-title":"Leaf and canopy water content estimation in cotton using hyperspectral indices and radiative transfer models","volume":"33","author":"Yi","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_50","first-page":"69","article-title":"Retrieval of canopy water content of different crop types with two new hyperspectral indices: Water absorption area index and depth water index","volume":"67","author":"Pasqualotto","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_51","unstructured":"Bach, H. (1995). Die Bestimmung Hydrologischer und Landwirtschaftlicher Oberfl\u00e4chenparameter aus Hyperspektralen Fernerkundungsdaten, Geobuch-Verlag."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1016\/S0034-4257(98)00038-8","article-title":"Estimating canopy water content of chaparral shrubs using optical methods","volume":"65","author":"Ustin","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/S0034-4257(03)00137-8","article-title":"Validation of a hyperspectral curve-fitting model for the estimation of plant water content of agricultural canopies","volume":"87","author":"Champagne","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_54","unstructured":"Meier, U. (2018). Growth Stages of Mono- and Dicotyledonous Plants: BBCH Monograph, Open Agrar Repositorium."},{"key":"ref_55","unstructured":"Hosgood, B., Jacquemoud, S., Andreoli, J., Verdebout, A., Pedrini, A., and Schmuck, G. (1995). Leaf Optical Properties Experiment 93 (LOPEX93), European Commission."},{"key":"ref_56","unstructured":"Jacquemoud, S., Bidel, C., and Pavan, F.G. (2017, November 14). Angers Leaf Optical Properties Database. Available online: http:\/\/ecosis.org."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/0034-4257(90)90100-Z","article-title":"Prospect: A model of leaf optical properties spectra","volume":"34","author":"Jacquemoud","year":"1990","journal-title":"Remote Sens. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/0034-4257(84)90057-9","article-title":"Light scattering by leaf layers with application to canopy reflectance modeling: The sail model","volume":"16","author":"Verhoef","year":"1984","journal-title":"Remote Sens. Environ."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.rse.2006.12.013","article-title":"Coupled soil\u2013leaf-canopy and atmosphere radiative transfer modeling to simulate hyperspectral multi-angular surface reflectance and TOA radiance data","volume":"109","author":"Verhoef","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"204","DOI":"10.1016\/j.rse.2017.03.004","article-title":"Prospect-D: Towards modeling leaf optical properties through a complete lifecycle","volume":"193","author":"Gitelson","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"3030","DOI":"10.1016\/j.rse.2008.02.012","article-title":"Prospect-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments","volume":"112","author":"Feret","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.cageo.2012.03.008","article-title":"Sensitivity analysis for volcanic source modeling quality assessment and model selection","volume":"44","year":"2012","journal-title":"Comput. Geosci."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.agrformet.2018.02.010","article-title":"Mapping forest canopy nitrogen content by inversion of coupled leaf-canopy radiative transfer models from airborne hyperspectral imagery","volume":"253\u2013254","author":"Wang","year":"2018","journal-title":"Agric. For. Meteorol."},{"key":"ref_64","first-page":"28","article-title":"Scattering impact analysis and correction for leaf biochemical parameter estimation using vis-NIR spectroscopy","volume":"26","author":"Zhang","year":"2011","journal-title":"Spectroscopy"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1109\/JSTARS.2011.2171181","article-title":"Improving the robustness of cotton status characterisation by radiative transfer model inversion of multi-angular CHRIS\/PROBA data","volume":"5","author":"Dorigo","year":"2012","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"6031","DOI":"10.1080\/01431161.2015.1110262","article-title":"Retrieval of leaf chlorophyll content in field crops using narrow-band indices: Effects of leaf area index and leaf mean tilt angle","volume":"36","author":"Zou","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0034-4257(02)00035-4","article-title":"Retrieval of canopy biophysical variables from bidirectional reflectance: Using prior information to solve the ill-posed inverse problem","volume":"84","author":"Combal","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Kuester, T., and Spengler, D. (2018). Structural and spectral analysis of cereal canopy reflectance and reflectance anisotropy. Remote Sens., 10.","DOI":"10.3390\/rs10111767"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"570","DOI":"10.1016\/S0034-4257(00)00147-4","article-title":"Deriving water content of chaparral vegetation from AVIRIS data","volume":"74","author":"Serrano","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.rse.2007.04.013","article-title":"Multi-temporal vegetation canopy water content retrieval and interpretation using artificial neural networks for the continental USA","volume":"112","author":"Trombetti","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"561","DOI":"10.3390\/rs4030561","article-title":"Optimal exploitation of the sentinel-2 spectral capabilities for crop leaf area index mapping","volume":"4","author":"Berger","year":"2012","journal-title":"Remote Sens."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"063557","DOI":"10.1117\/1.JRS.6.063557","article-title":"Derivation of biophysical variables from earth observation data: Validation and statistical measures","volume":"6","author":"Richter","year":"2012","journal-title":"J. Appl. Remote Sens."},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Transon, J., d\u2019Andrimont, R., Maugnard, A., and Defourny, P. (2018). Survey of hyperspectral earth observation applications from space in the sentinel-2 context. Remote Sens., 10.","DOI":"10.3390\/rs10020157"},{"key":"ref_74","first-page":"554","article-title":"Spectral band selection for vegetation properties retrieval using Gaussian processes regression","volume":"52","author":"Verrelst","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Danner, M., Berger, K., Wocher, M., Mauser, W., and Hank, T. (2017). Retrieval of biophysical crop variables from multi-angular canopy spectroscopy. Remote Sens., 9.","DOI":"10.3390\/rs9070726"},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"van der Linden, S., Rabe, A., Held, M., Jakimow, B., Leit\u00e3o, P., Okujeni, A., Schwieder, M., Suess, S., and Hostert, P. (2015). The EnMAP-Box\u2014A toolbox and application programming interface for EnMAP data processing. Remote Sens., 7.","DOI":"10.3390\/rs70911249"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/12\/1924\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:33:38Z","timestamp":1760196818000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/12\/1924"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,11,30]]},"references-count":76,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2018,12]]}},"alternative-id":["rs10121924"],"URL":"https:\/\/doi.org\/10.3390\/rs10121924","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,11,30]]}}}