Paper
22 December 2003 Remote sensing and implications for variable-rate application using agricultural aircraft
Steven J. Thomson, Lowrey A. Smith, Jeffrey D. Ray, Paul V. Zimba
Author Affiliations +
Abstract
Aircraft routinely used for agricultural spray application are finding utility for remote sensing. Data obtained from remote sensing can be used for prescription application of pesticides, fertilizers, cotton growth regulators, and water (the latter with the assistance of hyperspectral indices and thermal imaging). Digital video was used to detect weeds in early cotton, and preliminary data were obtained to see if nitrogen status could be detected in early soybeans. Weeds were differentiable from early cotton at very low altitudes (65-m), with the aid of supervised classification algorithms in the ENVI image analysis software. The camera was flown at very low altitude for acceptable pixel resolution. Nitrogen status was not detectable by statistical analysis of digital numbers (DNs) obtained from images, but soybean cultivar differences were statistically discernable (F=26, p=0.01). Spectroradiometer data are being analyzed to identify narrow spectral bands that might aid in selecting camera filters for determination of plant nitrogen status. Multiple camera configurations are proposed to allow vegetative indices to be developed more readily. Both remotely sensed field images and ground data are to be used for decision-making in a proposed variable-rate application system for agricultural aircraft. For this system, prescriptions generated from digital imagery and data will be coupled with GPS-based swath guidance and programmable flow control.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Steven J. Thomson, Lowrey A. Smith, Jeffrey D. Ray, and Paul V. Zimba "Remote sensing and implications for variable-rate application using agricultural aircraft", Proc. SPIE 5153, Ecosystems' Dynamics, Agricultural Remote Sensing and Modeling, and Site-Specific Agriculture, (22 December 2003); https://doi.org/10.1117/12.506053
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KEYWORDS
Cameras

Nitrogen

Agriculture

Imaging systems

Image analysis

Remote sensing

Video

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