|Elliott, Norman - Norm|
Submitted to: Biennial Workshop on Aerial Photography, Videography, and High Resolution Digital Imagery for Resource Assessment Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 9/15/2005
Publication Date: 11/1/2005
Citation: Elliott, N.C., Mirik, M., Yang, Z., Dvorak, T., Rao, M., Michels, J., Catana, V., Phoofolo, M., Giles, K., Royer, T. 2005. Airborne multi-spectral remote sensing for Russian wheat aphid infestations. In: Proceedings of the 20th Biennial Workshop on Aerial Photography, Videography, and High Resolution Digital Imagery for Resource Assessment, October 4-6, 2005, Weslaco, TX. 2005 CDROM.
Interpretive Summary: The Russian wheat aphid (RWA) is a severe pest of wheat in the High Plains region of the United States. Remote sensing may be effective for detecting RWA damage to wheat for pest management decision-making, but has not yet been tested to determine if it will work for that purpose. We evaluated remote sensing based on reflected sunlight (multi-spectral remote sensing) for its ability to detect injury caused by the RWA to winter wheat in production fields. Two study fields were located in southeastern Colorado, and two fields were located in far western Oklahoma. In each field, plant damage was determined and multi-spectral imagery was obtained from a Cessna 172 aircraft equipped with a digital camera capable of taking multi-spectral images. We found that damage to wheat plants was easily detected in the imagery. The results indicate that it is feasible to use remote sensing to identify and monitor RWA infested wheat fields. However, a great deal of work still needs to be done to develop remote sensing as an accurate tool for that purpose.
Technical Abstract: The Russian wheat aphid (RWA) is a severe pest of wheat in the High Plains region of the United States. Remote sensing could be effective for detecting RWA infestations for pest management decision-making. We evaluated an airborne multi-spectral remote sensing system for its ability to differentiate varying levels of injury caused by RWA infestation in winter wheat fields. Two study fields were located in southeastern Colorado in spring 2004, and two fields were located in far western Oklahoma in spring 2005. In each field, RWA density and plant damage were determined for 20-24 3x3 m plots with varying levels of RWA damage. Prior to sampling plots, multi-spectral imagery was obtained using an SSTCRIS® multi-spectral imaging system mounted NADIR in a Cessna 172 aircraft. The multi-spectral data were used to compare with RWA infestation level for each plot. Correlations between vegetation indices and the proportion of RWA damaged wheat tillers per plot were negative for all vegetation indices calculated. Normalized differenced vegetation index (NDVI) and vegetation index (VI) were most consistently correlated with the proportion of RWA damaged tillers. Regressions of NDVI versus the proportion of RWA damaged wheat tillers per plot were significant and had negative slopes. However, slopes and intercepts of regressions differed significantly among fields. Any one or a combination of differences in time of day, atmospheric conditions, edaphic factors (e.g. soil type and soil moisture), and possibly unknown factors could have caused the differences observed in regressions among fields.