
Proceedings Paper
Relationships between high resolution RapidEye based fPAR and MODIS vegetation indices in a heterogeneous agricultural regionFormat | Member Price | Non-Member Price |
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Paper Abstract
The Moderate Imaging Spectroradiometer (MODIS) provides operational products of the Normalized Difference
Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), and the fraction of photosynthetic active radiation
(fPAR). FPAR can be used in productivity models, but agricultural applications depend on sub-pixel heterogeneity.
Examples for heterogeneous areas are the irrigation systems of the inner Aral Sea Basin, where the 1 km fPAR product
proved less suited. An alternative can be to upscale fPAR to the 250 m scale, but there are few studies evaluating this
approach. In this study, the use of MODIS 250 m NDVI and EVI for this approach was investigated in an irrigation
system in western Uzbekistan. The analysis was based on high resolution fPAR maps and a crop map for the growing
season 2009, derived from ground measurements and multitemporal RapidEye data. The data was used to explore
statistical relationships between RapidEye fPAR and MODIS NDVI/EVI with respect to spatial heterogeneity. The
correlations varied between products (daily NDVI, 8-day NDVI, 16-day NDVI/EVI), with results suggesting that 8-day
NDVI performed best. The analyses and the compiled fPAR maps show that, compared to 1 km MODIS fPAR, the 250 m
scale is more homogeneous, allows for crop-specific analyses, and better captures the spatial patterns in the study region.
Paper Details
Date Published: 6 October 2011
PDF: 11 pages
Proc. SPIE 8174, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII, 81740N (6 October 2011); doi: 10.1117/12.898333
Published in SPIE Proceedings Vol. 8174:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII
Christopher M. U. Neale; Antonino Maltese, Editor(s)
PDF: 11 pages
Proc. SPIE 8174, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII, 81740N (6 October 2011); doi: 10.1117/12.898333
Show Author Affiliations
Sebastian Fritsch, Univ. of Würzburg (Germany)
Ctr. for Development Research (Germany)
Miriam Machwitz, Univ. of Würzburg (Germany)
Ctr. for Development Research (Germany)
Miriam Machwitz, Univ. of Würzburg (Germany)
Christopher Conrad, Univ. of Würzburg (Germany)
Stefan Dech, Deutsches Zentrum für Luft- und Raumfahrt e.V. (Germany)
Stefan Dech, Deutsches Zentrum für Luft- und Raumfahrt e.V. (Germany)
Published in SPIE Proceedings Vol. 8174:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII
Christopher M. U. Neale; Antonino Maltese, Editor(s)
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