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Article: Extraction of red edge optical parameters from hyperion data for estimation of forest leaf area index

TitleExtraction of red edge optical parameters from hyperion data for estimation of forest leaf area index
Authors
KeywordsHyperion
Leaf area index
Red well position
Red edge position
Issue Date2003
Citation
IEEE Transactions on Geoscience and Remote Sensing, 2003, v. 41, n. 4 PART II, p. 916-921 How to Cite?
AbstractA correlation analysis was conducted between forest leaf area index (LAI) and two red edge parameters: red edge position (REP) and red well position (RWP), extracted from reflectance image retrieved from Hyperion data. Field spectrometer data and LAI measurements were collected within two days after the Earth Observing One satellite passed over the study site in the Patagonia region of Argentina. The two red edge parameters were extracted with four approaches: four-point interpolation, polynomial fitting, Lagrangian technique, and inverted-Gaussian (IG) modeling. Experimental results indicate that the four-point approach is the most practical and suitable method for extracting the two red edge parameters from Hyperion data because only four bands and a simple interpolation computation are needed. The polynomial fitting approach is a direct method and has its practical value if hyperspectral data are available. However, it requires more computation time. The Lagrangian method is applicable only if the first derivative spectra are available; thus, it is not suitable to multispectral remote sensing. The IG approach needs further testing and refinement for Hyperion data.
Persistent Identifierhttp://hdl.handle.net/10722/296544
ISSN
2023 Impact Factor: 7.5
2023 SCImago Journal Rankings: 2.403
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorPu, Ruiliang-
dc.contributor.authorGong, Peng-
dc.contributor.authorBiging, Greg S.-
dc.contributor.authorLarrieu, Mirta Rosa-
dc.date.accessioned2021-02-25T15:16:07Z-
dc.date.available2021-02-25T15:16:07Z-
dc.date.issued2003-
dc.identifier.citationIEEE Transactions on Geoscience and Remote Sensing, 2003, v. 41, n. 4 PART II, p. 916-921-
dc.identifier.issn0196-2892-
dc.identifier.urihttp://hdl.handle.net/10722/296544-
dc.description.abstractA correlation analysis was conducted between forest leaf area index (LAI) and two red edge parameters: red edge position (REP) and red well position (RWP), extracted from reflectance image retrieved from Hyperion data. Field spectrometer data and LAI measurements were collected within two days after the Earth Observing One satellite passed over the study site in the Patagonia region of Argentina. The two red edge parameters were extracted with four approaches: four-point interpolation, polynomial fitting, Lagrangian technique, and inverted-Gaussian (IG) modeling. Experimental results indicate that the four-point approach is the most practical and suitable method for extracting the two red edge parameters from Hyperion data because only four bands and a simple interpolation computation are needed. The polynomial fitting approach is a direct method and has its practical value if hyperspectral data are available. However, it requires more computation time. The Lagrangian method is applicable only if the first derivative spectra are available; thus, it is not suitable to multispectral remote sensing. The IG approach needs further testing and refinement for Hyperion data.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Geoscience and Remote Sensing-
dc.subjectHyperion-
dc.subjectLeaf area index-
dc.subjectRed well position-
dc.subjectRed edge position-
dc.titleExtraction of red edge optical parameters from hyperion data for estimation of forest leaf area index-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TGRS.2003.813555-
dc.identifier.scopuseid_2-s2.0-0038575032-
dc.identifier.volume41-
dc.identifier.issue4 PART II-
dc.identifier.spage916-
dc.identifier.epage921-
dc.identifier.isiWOS:000183412900005-
dc.identifier.issnl0196-2892-

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