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http://dx.doi.org/10.7780/kjrs.2017.33.5.2.13

Estimating Corn and Soybean Yield Using MODIS NDVI and Meteorological Data in Illinois and Iowa, USA  

Lee, Kyung-Do (National Institute of Agricultural Science, Rural Development Administration)
Na, Sang-Il (National Institute of Agricultural Science, Rural Development Administration)
Hong, Suk-Young (National Institute of Agricultural Science, Rural Development Administration)
Park, Chan-Won (National Institute of Agricultural Science, Rural Development Administration)
So, Kyu-Ho (National Institute of Agricultural Science, Rural Development Administration)
Park, Jae-Moon (National Institute of Agricultural Science, Rural Development Administration)
Publication Information
Korean Journal of Remote Sensing / v.33, no.5_2, 2017 , pp. 741-750 More about this Journal
Abstract
The objective of this study was to estimate corn and soybean yield in Illinois and Iowa in USA using satellite and meteorological data. MODIS products for NDVI were downloaded from a NASA website. Each layer was processed to convert projection and extract layers for NDVI. Relations of NDVI from 2002 to 2012 with corn and soybean yield were investigated to find informative days for rice yield estimation. Weather data for the county of study state duration from 2002 to 2012 to correlate crop yield. Multiple regression models based on MODIS NDVI and rainfall were made to estimate corn and soybean yields in study site. Corn yields estimated for 2013 were $10.17ton\;ha^{-1}$ in Illinois, $10.21ton\;ha^{-1}$ in Iowa and soybean yields estimated were $3.11ton\;ha^{-1}$ in Illinois, $2.58ton\;ha^{-1}$ in Iowa, respectively. Corn and Soybean yield distributions in 2013 were mapped to show spatial variability of crop yields of the Illinois and Iowa state.
Keywords
remote sensing; crop yield estimation; MODIS NDVI;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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