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Title: Effects of image spatial and radiometric resolutions on the detection of cotton plants

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

Submitted to: National Cotton Council Beltwide Cotton Conference
Publication Type: Proceedings
Publication Acceptance Date: 1/18/2013
Publication Date: 6/5/2013
Citation: Yang, C., Westbrook, J.K., Suh, C.P., Lan, Y., Eyster, R.S. 2013. Effects of image spatial and radiometric resolutions on the detection of cotton plants. National Cotton Council Beltwide Cotton Conference. pp. 500-506.

Interpretive Summary: Regrowth of cotton plants and germination of cotton seeds (volunteer cotton) following harvest create a potential habitat for boll weevils, and threaten continued progress toward boll weevil eradication in the U.S. Consequently, new techniques are needed for accurate and timely detection of volunteer and regrowth cotton plants. This study evaluated how spatial resolution (pixel size) and radiometric resolution (gray scale) of airborne images affect the detection of cotton plants. Spatial resolution had a significant effect on plant identification and canopy cover estimation, while radiometric resolution had little effect on cotton canopy estimation. These preliminary findings will aid in the development of techniques for remote detection and classification of volunteer and regrowth cotton plants, and lead to subsequent management or removal of potential boll weevil habitats.

Technical Abstract: Accurate and timely detection of volunteer and regrowth cotton plants is important for the eradication of boll weevils in south Texas. Airborne remote sensing imagery has the potential to identify volunteer and regrowth cotton plants over large geographic regions. The objective of this study was to determine how image spatial and radiometric resolutions affect the detection of cotton plants. Airborne four-band, 16-bit images with five pixel sizes (0.1, 0.2, 0.3, 0.4, and 0.5 m) acquired from a cotton field in south Texas were used in this study. Each 16-bit image was converted to four images with reduced radiometric resolutions (8, 10, 12, and 14 bits). The images with 25 different combinations of spatial and spectral resolutions were classified to detect cotton plants using four classifiers. Results showed that spatial resolution had a significant effect on plant identification and canopy cover estimation, while radiometric resolution reduced from 16 bits to 8 bits had little effect on cotton canopy estimation within the cotton field. The four classifiers produced similar image classification results. These preliminary findings will be useful for determining the appropriate spatial and radiometric resolutions and classification methods for identifying volunteer and regrowth cotton plants.