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United States Department of Agriculture

Agricultural Research Service

Research Project: QUANTIFYING LANDSCAPE FACTORS INFLUENCING SOIL PRODUCTIVITY AND THE ENVIRONMENT Title: Estimating crop production in Iowa from Advanced Wide Field Sensor (AWiFS) data

Authors
item Hunt, Earle
item Serbin, Guy
item Daughtry, Craig
item Doraiswamy, Paul
item Prueger, John
item Hatfield, Jerry

Submitted to: American Society for Photogrammetry and Remote Sensing Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: October 14, 2008
Publication Date: March 9, 2009
Citation: Hunt, E.R., Serbin, G., Daughtry, C.S., Doraiswamy, P.C., Prueger, J.H., Hatfield, J.L. 2009. Estimating crop production in Iowa from advanced wide field sensor (AWiFS) data [abstract]. American Society for Photogrammetry and Remote Sensing Proceedings. 2009 CDROM.

Technical Abstract: Indian National Remote Sensing Agency ResourceSat-1 Advanced Wide Field Sensor (AWiFS) data for the USA is being provided online by the USDA Foreign Agricultural Service (FAS) and Arctic Slope Regional Corporation – Management Services (ASRC-MS). Because of the frequent revisit time and pixel sizes from 50 to 70 m, AWiFS data may be better for estimating agricultural production than MODIS or VIIRS. The specific objective of this study was to calculate light use efficiency from daily net CO2 flux and the amount of daily absorbed photosynthetically active radiation (PAR). The Soil Moisture Experiment 2005 (SMEX’05) was conducted in Walnut Creek Watershed near Ames IA, during which eddy-correlation flux towers were used to measure daily net CO2 fluxes over various fields of corn and soybean. Imagery from AWiFS and NASA sensors were combined to estimate of the fraction of absorbed PAR over the growing season for each field. The slope between the net CO2 flux and absorbed PAR is the estimated light use efficiency. The differences in light use efficiency between corn (C4 photosynthesis) and soybean (C3 photosynthesis) indicate that land-cover classification is an important input for estimation of agricultural production.

Last Modified: 9/10/2014
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