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ARS Home » Southeast Area » Florence, South Carolina » Coastal Plain Soil, Water and Plant Conservation Research » Research » Publications at this Location » Publication #113660
Title: USING REMOTE SENSING AND MODELING TO MEASURE CROP BIOPHYSICAL VARIABILITY

Author
item LOCKE, C - UNIV. OF SC, COLUMBIA, SC
item CARBONE, G - UNIV. OF SC, COLUMBIA, SC
item FILIPPI, A - UNIV. OF SC, COLUMBIA, SC
item Sadler, Edward
item Gerwig, Betsy
item Evans, Dean

Submitted to: International Conference on Precision Agriculture Abstracts & Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 7/16/2000
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: This study integrates field collection, crop modeling, and remote sensing to assess spatial variability of biophysical properties. These tools are used to describe and predict leaf area index (LAI), intercepted photosynthetically active radiation (PAR), biomass, and yield for the 1998 growing season for a soybean field at the USDA-ARS Coastal Plains Soil, Water, and Plant Research Center. LAI and yield data collected in the field are compared with LAI, PAR, biomass, and yield modeled with CROPGRO-Soybean. Field and modeled data are then compared to six dates of SPOT 4 satellite imagery and associated vegetation indices (NDVI, SR, SAVI, and TSAVI). The vegetation indices captured the spatial variability of observed LAI and simulated LAI, PAR, and biomass when aggregated over the growing season. Individual dates of imagery were less successful, possibly due to the coarse spatial resolution of the SPOT imagery, or due to shortcomings in the index calculations. SPOT imagery did not capture the spatial variability of observed yield.