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United States Department of Agriculture

Agricultural Research Service


item Moran, Mary - Susan
item Hymer, Daniel
item Qi, Jiaguo
item Kerr, Vann

Submitted to: International Conference on Precision Agriculture Abstracts & Proceedings
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/15/1999
Publication Date: N/A
Citation: N/A

Interpretive Summary: Precision farm management is designed to allow the right amount of chemical and water to be applied at the right time to the right location in each field. To accomplish this goal, it is necessary to have accurate information about soil and plant conditions within each field. It may be possible to use images obtained from orbiting sensors to acquire such information. In this study, we investigated the sensitivity of images from an orbiting radar sensor to variations in field roughness, surface soil moisture, and vegetation density. Preliminary results showed that the radar data were related directly to within-field differences in tillage, irrigation, and crop vigor. With such radar images of an entire farm, in the future it may be possible to implement precision farm management at low expense with high precision.

Technical Abstract: Studies over the past 25 years have shown that measurements of surface reflectance and temperature (termed optical remote sensing) are useful for monitoring crop and soil conditions. Far less attention has been given to the use of radar imagery, even though Synthetic Aperture Radar (SAR) systems have the advantages of cloud penetration, all-weather coverage, high spatial resolution, day/night acquisitions, and signal independence of the solar illumination angle. In this study, we obtained coincidental optical and SAR images of an agricultural area to investigate the use of SAR imagery for precision farm management. Results showed that SAR imagery was sensitive to variations in field tillage, surface soil moisture, and vegetation density. The coincidental optical images proved useful in interpreting the response of SAR backscatter to soil and plant conditions.

Last Modified: 06/24/2017
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