Submitted to: NASA Commercial Remote Sensing Verification and Validation Symposium
Publication Type: Proceedings
Publication Acceptance Date: 8/15/1998
Publication Date: N/A
Citation: Interpretive Summary: Images acquired with sensors aboard aircrafts and orbiting satellites have great potential for providing information for agricultural management. However, it is imperative that the image information be timely, accurate, and at a suitable scale for agricultural application. Scientists at USDA- ARS and the NASA Stennis Space Center designed an experiment to investigate ethe suitability of the NASA ATLAS airborne sensor for farm management. Preliminary results showed that the ATLAS image products met the stringent image acquisition and resolution requirements for crop and soil management. Further work is being conducted to improve the image contrast and rectification to allow more precise and automated image interpretation by the farm manager. With these refinements, important farm information could be derived from the ATLAS imagery to help farm managers make thoughtful, timely decisions about such practices as irrigation, chemical application, and crop cultivation.
Technical Abstract: A Space Act Agreement was signed between the USDA-ARS and NASA Stennis Space Center to investigate the use of the 14-band ATLAS spectral imagery for farm management applications. Through this agreement, Stennis provided ATLAS imagery of the Maricopa Agricultural Center on six dates corresponding with the cotton and sorghum growing seasons. ARS scientists agreed to provide a critical review of ATLAS image products, provide on- the-job training for SSC personnel in precision agriculture and ground data collection, and present results at the Verification and Validation Symposium at SSC. Preliminary results showed that the ATLAS image products have radiometric accuracy, turnaround times, and spatial resolution suitable for farm management applications. However, the ATLAS geometric integrity was poor, and the sensor was often set with inappropriate gains and offsets resulting in image saturation over agricultural targets. The latter two limitations are being resolved through further study and image post-processing.