Paper
14 May 2019 Plant-by-plant level classifications of cotton root rot by UAV remote sensing
Author Affiliations +
Abstract
The fungus Phymatotrichpsis omnivora, also called cotton root rot (CRR), is one of the most deadly cotton diseases in the Southwest U.S. Once the cotton is infected by CRR it is very unlikely for it to be cured. Previous research indicates that the CRR will reoccur at a similar area as previous years. A fungicide known as Topguard Terra was proven efficient in CRR prevention. Therefore, knowing the historical CRR-infested area is helpful to prevent CRR from appearing again in the future. The CRR-infested plants can be detected by using aerial remote sensing. When an unmanned aerial vehicle (UAV) was introduced to a remote sensing research field, the spatial and temporal resolution of imagery data increased significantly and higher precision CRR classification was made possible. A plant-by-plant (PBP) level classification based on the Superpixel concept was developed to identify CRR-infested and healthy cotton plants in the field at the single plant level. The PBP classification algorithm was improved to achieve fewer misclassifications.
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T. Wang and J. A. Thomasson "Plant-by-plant level classifications of cotton root rot by UAV remote sensing", Proc. SPIE 11008, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping IV, 110080N (14 May 2019); https://doi.org/10.1117/12.2519394
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KEYWORDS
Remote sensing

Unmanned aerial vehicles

Image resolution

Multispectral imaging

Image segmentation

Sensors

Image classification

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