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Statistical derivation of fPAR and LAI for irrigated cotton and rice in arid Uzbekistan by combining multi-temporal RapidEye data and ground measurements

Ehammer, Andrea and Fritsch, Sebastian and Conrad, Christopher and Lamers, John and Dech, Stefan (2010) Statistical derivation of fPAR and LAI for irrigated cotton and rice in arid Uzbekistan by combining multi-temporal RapidEye data and ground measurements. In: Remote Sensing for Agriculture, Ecosystems, and Hydrology XII, 7824, pp. 1-10. SPIE. SPIE remote sensing symposium 2010, 20. - 23. September, Toulouse. ISBN 9780819483416

Full text not available from this repository.

Official URL: http://spie.org/x648.html?product_id=864796

Abstract

Land surface biophysical parameters such as the fraction of photosynthetic active radiation (fPAR) and leaf area index (LAI) are keys for monitoring vegetation dynamics and in particular for biomass and carbon flux simulation. This study aimed at deriving accurate regression equations from the newly available RapidEye satellite sensor to be able to map regional fPAR and LAI which could be used as inputs for crop growth simulations. Therefore, multi-temporal geo- and atmospherically corrected RapidEye scenes were segmented to derive homogeneous patches within the experimental fields. Various vegetation indices (VI) were calculated for each patch focusing on indices that include RapidEye's red edge band and further correlated with in situ measured fPAR and LAI values of cotton and rice. Resulting coefficients of determination ranged from 0.55 to 0.95 depending on the indices analysed, object scale, crop type and regression function type. The general relationships between VI and fPAR were found to be linear. Nonlinear models gave a better fit for VI-LAI relation. VIs derived from the red edge channel did not prove to be generally superior to other VIs.

Item URL in elib:https://elib.dlr.de/67218/
Document Type:Conference or Workshop Item (Speech, Paper)
Title:Statistical derivation of fPAR and LAI for irrigated cotton and rice in arid Uzbekistan by combining multi-temporal RapidEye data and ground measurements
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Ehammer, AndreaUniversität InnsbruckUNSPECIFIED
Fritsch, Sebastiansebastian.fritsch (at) uni-wuerzburg.deUNSPECIFIED
Conrad, Christopherchristopher.conrad (at) uni-wuerzburg.deUNSPECIFIED
Lamers, JohnZentrum für Entwicklungsforschung (ZEF)UNSPECIFIED
Dech, Stefan DFDUNSPECIFIED
Date:2010
Journal or Publication Title:Remote Sensing for Agriculture, Ecosystems, and Hydrology XII
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Volume:7824
Page Range:pp. 1-10
Editors:
EditorsEmail
Neale, Christopher M. U.Utah State University
Maltese , AntonioUniv degli Studi di Palermo
Publisher:SPIE
Series Name:Proceedings of SPIE
ISBN:9780819483416
Status:Published
Keywords:biophysical parameters, vegetation indices, upscaling, irrigated agriculture, Central Asia
Event Title:SPIE remote sensing symposium 2010
Event Location:Toulouse
Event Type:international Conference
Event Dates:20. - 23. September
Organizer:SPIE
HGF - Research field:Aeronautics, Space and Transport (old)
HGF - Program:Space (old)
HGF - Program Themes:W EO - Erdbeobachtung
DLR - Research area:Space
DLR - Program:W EO - Erdbeobachtung
DLR - Research theme (Project):W - Vorhaben Geowissenschaftl. Fernerkundungs- und GIS-Verfahren (old)
Location: other , Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center
Deposited By: Zeidler, Julian
Deposited On:10 Feb 2011 10:15
Last Modified:10 Feb 2011 10:15

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