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Title: REMOTE SENSING USING RADIO-CONTROLLED MODEL AIRCRAFT AND AIRBORNE SENSORS FOR NUTRIENT MANAGEMENT

Author
item Hunt Jr, Earle
item Daughtry, Craig
item Walthall, Charles
item McMurtrey Iii, James
item Dulaney, Wayne

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 7/30/2002
Publication Date: 12/23/2003
Citation: Hunt, E.R., Daughtry, C.S., Walthall, C.L., McMurtrey, J.E., Dulaney, W.P. 2003. Agricultural remote sensing using radio-controlled model aircraft. In: Van Toai, T., Major, D., McDonald, M., Schepers, J., and Tarpley, L. editors. Digital Imaging and Spectral Techniques: Applications to Precision Agriculture and Crop Physiology. ASA Special Publication 66. Madison, WI: ASA-CSSA-SSSA. p. 191-199.

Interpretive Summary: Remote sensing uses different platforms which provide a variety of spatial scales and repeat capabilities. For nutrient management, most users want very high spatial resolution and high repeat frequency. Airborne sensors from color infrared photography to digital imaging can provide these requirements but have the highest cost per area. We examined the use of radio-controlled model aircraft (RCMA), which are readily available from hobby stores, as a low cost alternative for acquiring airborne data. These aircraft must be located visually, so only single fields can be monitored. Color infrared photographs from RCMA were good at determining plant density but not good at determining nutrient requirements, because the spectral resolution of the film was low. More work is necessary to determine if radio-controlled model aircraft are useful for agricultural monitoring.

Technical Abstract: Radio-controlled model aircraft presents a platform for remote sensing that may reduce the costs for nutrient management of individual fields. As a test of concept, an automatic camera with color infrared film was mounted on a fixed wing model aircraft. The Normalized Difference Vegetation Index (NDVI) was calculated from the data for plots of corn with various levels of applied nitrogen. NDVI was linearly related to NDVI obtained by the AISA sensor, onboard a conventional remote sensing aircraft, but NDVI from either sensor were not related to the level of applied nitrogen. The Modified Chlorophyll Absorption Reflectance Index (MCARI) from the AISA data was related to nitrogen level late in the season, but not early in the season. So the lack of a relationship between NDVI and nitrogen level may be due to NDVI is more related to plant density rather than chlorophyll levels in the canopy. Thus, more work is necessary to determine if radio-controlled model aircraft are useful in agriculture.