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Title: Mapping cotton root rot infestations over a 10-year interval with airborne multispectral imagery

Author
item Yang, Chenghai
item ODVODY, GARY - Texas Agrilife Research
item FERNANDEZ, CARLOS - Texas Agrilife Research
item LANDIVAR, JUAN - Texas Agrilife Research
item NICHOLS, ROBERT - Cotton, Inc

Submitted to: ASABE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: 8/25/2011
Publication Date: 8/30/2011
Citation: Yang, C., Odvody, G.N., Fernandez, C.J., Landivar, J.A., Nichols, R.L. 2011. Mapping cotton root rot infestations over a 10-year interval with airborne multispectral imagery. ASABE Paper No. 1110930. St. Joseph, Mich.:ASABE.

Interpretive Summary: Cotton root rot is a serious and destructive disease that affects cotton production in the southwestern United States. This study used airborne multispectral imagery to detect the change of cotton root rot infestations in a 102-ha center-pivot irrigated cotton field near Edroy, TX, between 2001 and 2011. Image analysis showed that airborne multispectral images were effective to distinguish root rot-infected areas from non-infected areas. Preliminary results indicate that the recurring spatial patterns of the disease were similar over the 10-year interval, though there were variations in infestation patterns over the years. These results will be useful for monitoring the progression of the disease over a longer time period and for the development of site-specific treatment plans for the disease.

Technical Abstract: Cotton root rot, caused by the pathogen Phymatotrichopsis omnivora, is a very serious and destructive disease of cotton grown in the southwestern and south central U.S. Accurate information regarding temporal changes of cotton root rot infestations within fields is important for the management and control of the disease. The objective of this study was to detect the change in cotton root rot infestations within cotton fields in south Texas over a 10-year interval. An airborne three-band image and an airborne four-band imager were collected from a cotton field in 2001 and 2011, respectively. The images were georeferenced, resampled to the same pixel size and then classified into root rot-infested and non-infected classes using unsupervised image classification techniques. Both images were effective to distinguish root rot-infected areas from non-infected areas. The infested areas within each field were determined and compared between the two imaging years. Preliminary results indicate that the recurring spatial patterns of the disease were similar over the 10-year interval, though there were variations in infestation patterns over the years. These results will be useful for monitoring the progression of the disease over a longer time period and for the management and control of the disease.