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United States Department of Agriculture

Agricultural Research Service

Title: MODIS DERIVED LAI FOR REGIONAL CROP YIELD ASSESSMENT

Authors
item Doraiswamy, Paul
item Akhmedov, Bakhyt - SSAI

Submitted to: American Society for Photogrammetry and Remote Sensing Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: December 16, 2004
Publication Date: March 7, 2005
Citation: Doraiswamy, P.C., Akhmedov, B. 2005. MODIS derived LAI for regional crop yield assesment [abstract]. American Society for Photogrammetric and Remote Sensing. 2005 CDROM.

Technical Abstract: Integration of operational satellites data with crop growth models allows assessing crop condition and yield at regional scale. NOAA AVHRR has been used extensively for monitoring vegetation condition and changes at regional scales. Daily coverage of MODIS imagery at 250 m. resolution from the Terra Satellite potentially offers an opportunity for operational assessment of the crop condition and yield in field and regional scale. The primary objective of this research was to evaluate the quality of the MODIS-250m resolution data for retrieval of crop biophysical parameters that could be integrated in crop yield simulation models. Several field studies were conducted in Illinois and Iowa to validate MODIS LAI product and the USDA derived LAI from MODIS 8-day, 250 m resolution composite reflectance product. Ground-based canopy and leaf reflectance and leaf area index (LAI) measurements were used to calibrate a radiative transfer model to create a look up tables (LUT) that was used to simulate LAI. The seasonal trend of MODIS derived LAI were used to define crop model parameters by adjusting the LAI simulated from the climate-based crop yield model. Other intermediate products such as crop phonological events were adjusted from the LAI seasonal profile. Corn and soybean yields simulations were conducted at 1.6 x 1.6 km2 spatial resolution grid and the results integrated to the county level. The results were within 15 % of county yields reported by the USDA National Agricultural Statistics Service (NASS).

Last Modified: 9/1/2014
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