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ARS Home » Plains Area » College Station, Texas » Southern Plains Agricultural Research Center » Insect Control and Cotton Disease Research » Research » Publications at this Location » Publication #289978
Title: Remote identification of potential boll weevil host plants: Airborne multispectral detection of regrowth cotton

Author
item Westbrook, John
item Suh, Charles
item Yang, Chenghai
item Lan, Yubin
item Eyster, Ritchie

Submitted to: National Cotton Council Beltwide Cotton Conference
Publication Type: Proceedings
Publication Acceptance Date: 1/15/2013
Publication Date: 6/5/2013
Citation: Westbrook, J.K., Suh, C.P., Yang, C., Lan, Y., Eyster, R.S. 2013. Remote identification of potential boll weevil host plants: Airborne multispectral detection of regrowth cotton. National Cotton Council Beltwide Cotton Conference. pp. 1178-1184.

Interpretive Summary: Cotton plants can regrow if the stalks are not destroyed after harvest, and can provide food and egg-laying sites for boll weevils between cotton production seasons. Effective methods for timely detection of these host plants are critically needed to expedite eradication in south Texas. We acquired airborne multispectral images of regrowth cotton fields that contained cotton plants of various sizes. Airborne multispectral and ground-based hyperspectral reflectance measurements of cotton plants and soil were analyzed using a technique known as linear spectral unmixing to quantify the relative contributions of cotton and soil to each image pixel. The capability to accurately detect cotton plants from medium- or high-resolution images could result in earlier detection and subsequent management of regrowth cotton plants over large areas.

Technical Abstract: Regrowth cotton plants can serve as potential hosts for boll weevils during and beyond the production season. Effective methods for timely areawide detection of these host plants are critically needed to expedite eradication in south Texas. We acquired airborne multispectral images of experimental regrowth cotton fields that contained various developmental stages, sizes, and densities of cotton plants. Airborne multispectral and ground-based hyperspectral reflectance measurements of cotton plants and soil were analyzed using the linear spectral unmixing technique to identify ‘pure’ image pixels of cotton and ‘fuzzy’ image pixels of cotton mixed with soil. The capability to accurately detect cotton plants from medium- or high-resolution images could result in earlier detection and subsequent management of regrowth cotton plants on an areawide basis.