1 May 2010 Vegetation water content mapping in a diverse agricultural landscape: National Airborne Field Experiment 2006
Michael H. Cosh, Jing Tao, Thomas J. Jackson, Lynn McKee, Peggy E. O'Neill
Author Affiliations +
Abstract
Mapping land cover and vegetation characteristics on a regional scale is critical to soil moisture retrieval using microwave remote sensing. In aircraft-based experiments such as the National Airborne Field Experiment 2006 (NAFE'06), it is challenging to provide accurate high resolution vegetation information, especially on a daily basis. A technique proposed in previous studies was adapted here to the heterogenous conditions encountered in NAFE'06, which included a hydrologically complex landscape consisting of both irrigated and dryland agriculture. Using field vegetation sampling and ground-based reflectance measurements, the knowledge base for relating the Normalized Difference Water Index (NDWI) and the vegetation water content was extended to a greater diversity of agricultural crops, which included dryland and irrigated wheat, alfalfa, and canola. Critical to the generation of vegetation water content maps, the land cover for this region was determined from satellite visible/infrared imagery and ground surveys with an accuracy of 95.5% and a kappa coefficient of 0.95. The vegetation water content was estimated with a root mean square error of 0.33 kg/m2. The results of this investigation contribute to a more robust database of global vegetation water content observations and demonstrate that the approach can be applied with high accuracy.
Michael H. Cosh, Jing Tao, Thomas J. Jackson, Lynn McKee, and Peggy E. O'Neill "Vegetation water content mapping in a diverse agricultural landscape: National Airborne Field Experiment 2006," Journal of Applied Remote Sensing 4(1), 043532 (1 May 2010). https://doi.org/10.1117/1.3449090
Published: 1 May 2010
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CITATIONS
Cited by 12 scholarly publications.
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KEYWORDS
Vegetation

Reflectivity

Satellites

Agriculture

Earth observing sensors

Soil science

Landsat

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