Application of MODIS-derived parameters for regional yield assessment

Paul Doraiswamy; Steven Hollinger; Thomas R. Sinclair; Alan Stern; Bakhyt Akhmedov; John Prueger

doi:10.1117/12.454181

28 January 2002 Application of MODIS-derived parameters for regional yield assessment

Paul Doraiswamy, Steven Hollinger, Thomas R. Sinclair, Alan Stern, Bakhyt Akhmedov, John Prueger

Author Affiliations +

Proceedings Volume 4542, Remote Sensing for Agriculture, Ecosystems, and Hydrology III; (2002) https://doi.org/10.1117/12.454181
Event: International Symposium on Remote Sensing, 2001, Toulouse, France

Abstract

Monitoring regional agricultural crop condition has traditionally been accomplished using NOAA AVHRR (1 km) data. New methods are developed for assessing crop yields by retrieving biophysical parameters from remotely sensed imagery and integrating with crop simulation models. The MODIS imagery with its 250 m resolution and a potentially daily coverage offers an opportunity for operational applications. The objective of this research was to assess the potential application of MODIS data for operational crop condition and yield estimates. A field study was conducted during the 2000 crop season in McLean county Illinois (IL), USA. Twenty corn and soybean fields were monitored with measurements for crop reflectance, Leaf area Index (LAI) and other crop growth parameters. A radiative transfer model was used to independently develop the LAI from the MODIS 250-m data. Crop growth parameters retrieved from the imagery were integrated in a crop yield simulation model. The magnitude and spatial variability of estimated LAI and the NASA product was partly due to differences in the classification of crop type and the pixel resolutions. A comparison with the NASA derived MODIS vegetation parameters and independently derived parameters are presented.

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Paul Doraiswamy, Steven Hollinger, Thomas R. Sinclair, Alan Stern, Bakhyt Akhmedov, and John Prueger "Application of MODIS-derived parameters for regional yield assessment", Proc. SPIE 4542, Remote Sensing for Agriculture, Ecosystems, and Hydrology III, (28 January 2002); https://doi.org/10.1117/12.454181

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