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dc.contributorSmith, Ronald Ben_US
dc.contributorDe Pauw, Eddyen_US
dc.creatorThenkabail, Prasaden_US
dc.date.accessioned2021-07-28T23:35:46Z
dc.date.available2021-07-28T23:35:46Z
dc.identifierhttps://www.asprs.org/wp-content/uploads/pers/2002journal/june/2002_jun_607-621.pdfen_US
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/3da94a6c521e345e3b79f708b4c13752en_US
dc.identifier.citationPrasad Thenkabail, Ronald B Smith, Eddy De Pauw. (1/6/2002). Evaluation of Narrowband and Broadband Vegetation Indeces for Determining Optimal Hyperspectral Wavebands for Agricultural Crop Characterization. Photogrammetric Engineering and Remote Sensing, 68 (6), pp. 607-621.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/13535
dc.description.abstractThe main goal of the study was to determine optimal waveband centers and widths required to best estimate agricultural crop characteristics. The hyperspectral narrowband data was acquired over 395 to 1020 nanometers using a 1.43-nanometerwide, 430 bands, hand-held spectroradiometer. Broadband data were derived using a Landsat-5 Thematic Mapper image acquired to correspond with field spectroradiometer and ground-truth measurements. Spectral and biophysical data were obtained from 196 sample locations, including farms and rangelands. Six representative crops grown during the main cropping season were selected: barley, wheat, lentil, cumin, chickpea, and vetch. Biophysical variables consisted of leaf area index, wet biomass, dry biomass, plant height, plant nitrogen, and canopy cover. Narrowband and broadband vegetation indices were computed and their relationship with quantitative crop characteristics were established and compared. The simple narrowband two-band vegetation indices [TBVI) and the optimum multiple-band vegetation indices [OMBVI) models provided the best results. The narrowband TBW and OMBvI models are compared with six other categories of narrow and broadband indices. Compared to the best broadband TM indices, TBW explained up to 24 percent greater variability and OMBVI explained up to 27 percent greater variability in estimating different crop variables. A Predominant proportion of crop characteristics are best estimated using data from four narrowbands, in order of importance, centered around 675 nanometers [red absorption maxima), 905 nm (near-infrared reflection peak), 720 nm [mid portion of the red-edge), and 550 nm [green reflectance maxima). The study determined 12 spectral bands and their bandwidths [Table 5) that provide optimal agricultural crop characteristics in the visible and near-infrared portion of the spectrum.en_US
dc.languageenen_US
dc.publisherAmerican Society for Photogrammetry and Remote Sensing - ASPRSen_US
dc.rightsCopyrighted; Non-commercial educational use onlyen_US
dc.sourcePhotogrammetric Engineering and Remote Sensing;68,(2002) Pagination 607-621en_US
dc.subjectspectral reflectanceen_US
dc.subjectcornen_US
dc.subjectleaf-area indexen_US
dc.subjectbenchmark research areaen_US
dc.subjectpigment concentrationsen_US
dc.titleEvaluation of Narrowband and Broadband Vegetation Indeces for Determining Optimal Hyperspectral Wavebands for Agricultural Crop Characterizationen_US
dc.typeJournal Articleen_US
dcterms.available2002-06-01en_US
dcterms.extent607-621en_US
cg.subject.agrovoclandscapeen_US
cg.subject.agrovocforestsen_US
cg.subject.agrovocindicatorsen_US
cg.subject.agrovocleavesen_US
cg.subject.agrovoccanopyen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerYale Universityen_US
cg.contributor.funderInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.projectCommunication and Documentation Information Services (CODIS)en_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contactprasad.thenkabail@yale.eduen_US
cg.isijournalISI Journalen_US
dc.identifier.statusOpen accessen_US
mel.impact-factor1.083en_US
cg.issn0099-1112en_US
cg.journalPhotogrammetric Engineering and Remote Sensingen_US
cg.issue6en_US
cg.volume68en_US


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