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ARS Home » Research » Publications at this Location » Publication #68921
Title: COMBINING MULTI-FREQUENCY MICROWAVE AND OPTICAL DATA FOR FARM MANAGEMENT

Author
item Moran, Mary
item VIDAL, A - CEMAGREF MONTPELLIER FR
item TROUFLEAU, D - NIAES LAB TSUKUBA JAPAN
item Qi, Jiaguo
item Clarke, Thomas
item Pinter Jr, Paul
item Mitchell, Thomas
item INOUE, Y - NIAES LAB TSUKUBA JAPAN
item NEALE, C - U OF UTAH

Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/21/1996
Publication Date: N/A
Citation: N/A

Interpretive Summary: For more than twenty-five years, scientists have been using spectral images acquired by sensors aboard airplanes and orbiting satellites to monitor crop and soil conditions. This work has focused on the relation between surface reflectance and temperature (termed optical data) and such parameters as crop growth, crop vigor and soil moisture. However, this work has been limited by the problems associated with measuring surface reflectance and temperature, such as cloudy weather, effects of varying solar illumination, and atmospheric interference. Recently, several new satellites have been launched that measure the surface "backscatter" (termed microwave data). Microwave data have the advantages of cloud and atmosphere penetration, and day/night acquisitions. For most conditions, we found that both microwave and optical data were related to similar surface parameters: crop biomass and soil moisture. These findings could lead to a greater use of orbiting satellites for monitoring crop and soil conditions for farm management applications, which will eventually benefit all food and fiber consumers.

Technical Abstract: The potential for the combined use of microwave and optical data for farm management was explored based on images acquired in the visible, near-infrared, and thermal spectrum, and the synthetic aperture radar (SAR) wavelengths in the Ku (14.85 Fhz) and C (5.3 Ghz) bands. The images were obtained during June 1994, and covered an agricultural site composed of large fields of partial-cover cotton, near-full-cover alfalfa and bare soil fields of varying roughness. Results showed that the SAR Ku backscatter coefficient was sensitive to soil roughness and insensitive to soil moisture conditions when vegetation was present. When soil roughness conditions were relatively similar (e.g., for cotton fields of similar row direction and for all alfalfa fields), the SAR Ku backscatter coefficient was sensitive to the fraction of the surface covered by vegetation. Under these conditions, the SAR Ku backscatter coefficient and the optical normalized difference vegetation index (NDVI) were generally correlated. The SAR C backscatter coefficient was found to be sensitive to soil moisture conditions for cotton fields with green leaf area index (GLAI) less than 1.0 and alfalfa fields with GLAI nearly 2.0. For both low-GLAI cotton and high-GLAI alfalfa, the SAR C backscatter coefficient was significantly correlated with measurements of surface temperature. Based on the findings of correlations between SAR Ku backscatter coefficient and NDVI and between the SAR C backscatter coefficient and surface temperature, some combined optical/radar approaches were suggested for farm management applications.