FUSION OF SENSED DATA FROM AIRBORNE AND GROUND-BASED SENSORS FOR COTTON REGROWTH
H Zhang, Yubin Lan, C Suh, J Westbrook, C Hoffmann, R Lacey
Contact: Yubin Lan
Aerial Application Technology
2771 F&B Road
College Station, TX 77845
Summary: The need to minimize populations of overwintering boll weevils, Anthonomus grandis Boheman, is widely recognized by eradication programs. One tactic to reduce overwintering survival of boll weevils is timely post-harvest crop destruction. Even where cotton plants, Gossypium hirsutum L., are destroyed after harvest, regrowth from stalks or growth of volunteer plants from un-harvested seed can occur when environmental conditions permit. Timely detection and remediation of volunteer cotton plants in both cultivated and non-cultivated habitats is critical for completing boll weevil eradication in Central and South Texas. The study investigates the use of aerial imagery and ground-based remotely sensed data for the discrimination of different crop species and timely detection of cotton plants over large areas. Airborne multispectral imagery and handheld hyperspectral data were acquired at multiple times over two large agricultural farms in Brazos County in Texas during the 2010 growing season. The performances of imagery data and handheld data for the discrimination were examined individually; then multisensor data fusion technique was applied on both aerial and ground datasets in order to improve the accuracy of the discrimination. The overall results indicate the potential of multisensor data fusion of remotely sensed data from different sensors as an effective tool for cotton regrowth studies.