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Automatic retrieval of crop characteristics: an example for hyperspectral AHS data from the AgriSAR campaign.

Dorigo, Wouter und Gerighausen, Heike (2007) Automatic retrieval of crop characteristics: an example for hyperspectral AHS data from the AgriSAR campaign. In: Proc. on AGRISAR and EAGLE Campaigns Final Workshop, Seiten 1-9. AGRISAR and EAGLE Campaigns Final Workshop, 2007-10-15 - 2007-10-16, ESA/ESTEC, Noordwijk, The Netherlands.

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Kurzfassung

This paper presents the results of automated extraction of crop characteristics from hyperspectral earth observation data. The data was acquired with an airborne AHS imaging spectrometer in the framework of the joint European AgriSAR 2006 campaign. The AgriSAR campaign was directed by the ESA and took place at the DEMMIN test site in northeast Germany, an agricultural area dominated by large monocultures. An important objective of this campaign was to establish to what degree novel radar and optical technologies are able to provide accurate agro-meteorological parameters for precision farming purposes. Parameter retrieval in this study was performed with the CRASh approach, a software module based on the inversion of radiative transfer models. CRASh was developed at DLR as part of an automated operative processing chain for future hyperspectral missions. Validation of the model inversion results was performed with field measurements of leaf area index and leaf chlorophyll content which were carried out for winter wheat, winter barley, winter rape, maize, and sugar beet at two time steps during the 2006 growing season. Although spatial patterns of the model results generally coincide with the trends observed in the field, absolute accuracy of the fully automatically extracted variables appeared insufficient for precision agriculture purposes. The unsatisfying results are ascribed to a combination of causes, including angular anisotropy across the swath-width of the flight lines, the configuration of the applied bands, and the large number of model inversion solutions inherent to an automated environment in which little additional information on the observed canopy is present. Employing the airborne version of CRASh and incorporating a priori information on land cover and variable distributions is expected to drastically increase the retrieval performance.

elib-URL des Eintrags:https://elib.dlr.de/53964/
Dokumentart:Konferenzbeitrag (Vortrag, Paper)
Titel:Automatic retrieval of crop characteristics: an example for hyperspectral AHS data from the AgriSAR campaign.
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Dorigo, WouterInstitute of Photogrammetry and Remote Sensing (I.P.F.), Vienna University of TechnologyNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Gerighausen, HeikeHeike.Gerighausen (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:2007
Erschienen in:Proc. on AGRISAR and EAGLE Campaigns Final Workshop
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Nein
In ISI Web of Science:Nein
Seitenbereich:Seiten 1-9
Status:veröffentlicht
Stichwörter:Hyperspectral, AHS, imaging spectroscopy, radiative transfer model inversion, CRASh, PROSPECT, SAILh, LAI, chlorophyll, AgriSAR, DEMMIN
Veranstaltungstitel:AGRISAR and EAGLE Campaigns Final Workshop
Veranstaltungsort:ESA/ESTEC, Noordwijk, The Netherlands
Veranstaltungsart:Andere
Veranstaltungsbeginn:15 Oktober 2007
Veranstaltungsende:16 Oktober 2007
Veranstalter :ESA
HGF - Forschungsbereich:Verkehr und Weltraum (alt)
HGF - Programm:Weltraum (alt)
HGF - Programmthema:W EO - Erdbeobachtung
DLR - Schwerpunkt:Weltraum
DLR - Forschungsgebiet:W EO - Erdbeobachtung
DLR - Teilgebiet (Projekt, Vorhaben):W - Vorhaben Spektrometrische Verfahren und Konzepte der Fernerkundung (alt)
Standort: Neustrelitz
Institute & Einrichtungen:Deutsches Fernerkundungsdatenzentrum > Nationales Bodensegment
Hinterlegt von: Gerighausen, Heike
Hinterlegt am:11 Jun 2008
Letzte Änderung:24 Apr 2024 19:17

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