Application of MODIS derived parameters for regional crop yield assessment
Doraiswamy, P.C. , Sinclair, T.R., Hollinger, S., Akhmedov, B., Stern, A., Prueger, J. Application of MODIS derived parameters for regional crop yield assessment. Remote Sensing of Environment Volume 97, Issue 2, 30 July 2005, Pages 192-202
Doraiswamy, P.C. , Sinclair, T.R., Hollinger, S., Akhmedov, B.,
Stern, A., Prueger, J. Application of MODIS derived parameters for
regional crop yield assessment. Remote Sensing of Environment
Volume 97, Issue 2, 30 July 2005, Pages 192-202
Abstract - NOAA AVHRR has been used extensively for monitoring
vegetation condition and changes across the United States.
Integration of crop growth models with MODIS imagery at 250 m
resolution from the Terra Satellite potentially offers an
opportunity for operational assessment of the crop condition and
yield at both field and regional scales. The primary objective of
this research was to evaluate the quality of the MODIS 250 m
resolution data for retrieval of crop biophysical parameters that
could be integrated in crop yield simulation models. A secondary
objective was evaluating the potential use of MODIS 250 m
resolution data for crop classification. A field study (24 fields)
was conducted during the 2000 crop season in McLean County,
Illinois, in the U.S. Midwest to evaluate the applicability of the
MODIS 8-day, 250 m resolution composite imagery (version 4) for
operational assessment of crop condition and yields. 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 table (LUT) that was used to simulate LAI. The seasonal trend of
MODIS derived LAI was used to find crop model parameters by
adjusting the LAI simulated from the climate-based crop yield
model. Other intermediate products such as crop phenological events
were adjusted from the LAI seasonal profile. Corn (Zea mays L.) and
soybean (Glycine max (L.) Merr.) yield simulations were conducted
on a 1.6 × 1.6 km2 spatial resolution grid and the results
integrated to the county level. The results were within 10% of
county yields reported by the USDA National Agricultural Statistics
Service (NASS).



