Submitted to: Remote Sensing for Agriculture Ecosystems and Hydrology
Publication Type: Abstract Only
Publication Acceptance Date: 7/25/2001
Publication Date: 11/17/2001
Citation: N/A Interpretive Summary: Regional monitoring of agricultural crop condition has traditionally been accomplished using NOAA AVHRR (1 km) data. The assessment of crop yields using the 1 Km AVHRR data have been investigated with reasonable success for areas in the US Midwest where the crops are primarily corn and soybean and the fields are relatively large. Recently NASA launched a suite of satellites such as MODIS on the TERRA platform. The objective of this research is to investigate the potential applications of MODIS data for USDA's operational programs. Two of the MODIS sensors provide spectral coverage in the visible and near infrared at 250m ground resolution. The coverage is daily and in this research, the MODIS data was used to monitor the crop growth and development of the corn and soybean crop. The study was conducted during summer 2000 in McLean County, Illinois. The investigations include ground measurements of leaf area index, biomass and crop yields at selected farms. The remote sensing data from MODIS was integrated in crop yield simulation models by techniques that were tested earlier with the AVHRR data. The crop yield for the corn and soybeans for the entire county were mapped. The model simulations compared very well with the farmer reported yields at the study sites. The new MODIS sensor has shown great potential for future operation programs within USDA.
Technical Abstract: Regional assessment of crop condition and yields are important to operational agencies within the U.S. Department of Agriculture. This research describes new methods for assessing crop yields are by integrating biophysical parameters retrieved from remotely sensed imagery with crop simulation models. The 1-km NOAA AVHRR imagery is unsuitable for retrieval of field level parameter and the Landsat data is not frequent enough for monitoring changes during the critical period of crop growth. The new MODIS satellite imagery offers an opportunity for a better resolution and a daily coverage required for operational applications. The objective of this research is to assess the application of MODIS data for operation crop condition and yields. Additionally, to compare MODIS products, LAI and fPAR with independently derived LAI/fPAR parameters from MODIS reflectance data. Both sets of parameters are input to crop simulation models for mapping regional crop yields. A Field study was conducted in McLean county Illinois, USA. Twenty corn and soybean fields were monitored for crop reflectance, LAI and other growth parameters. A radiative transfer model was used to develop the LAI and fPAR parameters for the entire county from the MODIS 250-m data. The magnitude and spatial variability of crop yield estimates from model simulations compared very well with the farmer reported yields at the study sites. Recommendations to improve MODIS derived operational parameter are presented.