Paper
6 October 2011 Relationships between high resolution RapidEye based fPAR and MODIS vegetation indices in a heterogeneous agricultural region
Sebastian Fritsch, Miriam Machwitz, Christopher Conrad, Stefan Dech
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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.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sebastian Fritsch, Miriam Machwitz, Christopher Conrad, and Stefan Dech "Relationships between high resolution RapidEye based fPAR and MODIS vegetation indices in a heterogeneous agricultural region", Proc. SPIE 8174, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII, 81740N (6 October 2011); https://doi.org/10.1117/12.898333
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KEYWORDS
MODIS

Vegetation

Agriculture

Composites

Statistical analysis

Reflectivity

Remote sensing

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