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ARS Home » Research » Publications at this Location » Publication #91021
Title: REMOTE SENSING TECHNIQUES FOR THE INTEGRATION OF CROP MODELS WITH GIS

Author
item Barnes, Edward
item Pinter Jr, Paul
item Moran, Mary
item Clarke, Thomas

Submitted to: Agronomy Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 10/31/1997
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: High spatial resolution multispectral data collected from airborne sensors over a Maricopa, Arizona, study site were used to develop several data layers that have potential use with crop models. Variations in the brightness of bare soils in the visible part of the spectrum showed a high degree of correlation with percent sand and clay in the surface soil layer. Relative canopy density was mapped throughout the cotton growing season using plant response in the red and near-infrared (NIR) part of the spectrum. This spectral response, combined with limited ground-based data, was used to create maps of leaf area index (LAI) for cotton. Comparisons of red and NIR reflectances for the same location on different dates were also used to inter relative canopy development rates. Thermal images combined with meteorological observations provided estimates of actual crop evapotranspiration (ET). In a geographic information system (GIS), these remotely sensed estimates of LAI and ET can be compared to crop model predictions or used as direct inputs to the model.