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United States Department of Agriculture

Agricultural Research Service

Research Project: Aerial Application Technology for Sustainable Crop Production

Location: Aerial Application Technology Research Unit

Title: Remote sensing of vegetative cotton to assist boll weevil eradication

Authors
item Yang, Chenghai
item Suh, Charles
item Westbrook, John
item Eyster, Ritchie

Submitted to: National Cotton Council Beltwide Cotton Conference
Publication Type: Proceedings
Publication Acceptance Date: January 27, 2014
Publication Date: April 21, 2014
Citation: Yang, C., Suh, C.P., Westbrook, J.K., Eyster, R.S. 2014. Remote sensing of vegetative cotton to assist boll weevil eradication. Proceedings of Beltwide Cotton Conference. p. 766-770.

Interpretive Summary: Early identification of cotton fields is important for advancing boll weevil eradication progress in south Texas. Practical methods were developed in this study for identifying cotton fields from airborne imagery before cotton plants start to bloom. Airborne multispectral imagery in conjunction with image classification techniques was able to distinguish planted cotton from other crops. These results will help eradication program managers quickly and efficiently identify cotton fields to improve the effectiveness of eradication and reduce the risk of re-infestation.

Technical Abstract: Early identification of cotton fields is important for advancing boll weevil eradication progress in south Texas. Remote sensing has the potential for this purpose over diverse habitats and large geographic regions. The objectives of this study were to develop practical methods for identifying cotton fields from airborne imagery before cotton plants start to bloom. Airborne multispectral imagery with 0.1- and 0.2-m pixel sizes was acquired four times along a 12-km length of the Brazos Valley near College Station, TX, in 2013. Supervised classification techniques were applied to a single image and a mosaicked image, both with 0.2-m pixels, to distinguish planted cotton from other crops and cover types. The original 0.2-m, 16-bit image was degraded to images with 1- and 2-m spatial resolutions and 8-bit spatial resolution. These resolution-reduced images were almost as effective for identifying cotton fields as the original image. As an application example, a mosaicked 8-bit image with 2-m pixel size was classified to differentiate cotton fields from other cover types. These results will help eradication program managers quickly and efficiently identify cotton fields and potential areas for volunteer and regrowth cotton plants, thus improving the effectiveness of eradication and reducing the risk of re-infestation.

Last Modified: 11/20/2014
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