Detection of diseased rubber plantations using satellite remote sensing

The study evaluates the potential of satellite remote sensing technology for detection, mapping and monitoring of diseased rubber plantation affected by Corynespora and Gloeosporium fungi, which causes leaf spot and leaf fall. Multi-date satellite data of IRS-1C have been analyzed adopting enhancement and classification techniques to identify and extract information on the spatial extent and distribution of healthy and diseased rubber plants with an accuracy of 90%. The diseased rubber plantations have shown considerable reduction in the near-infrared reflectance followed by a rise in the reflectance in red and short wave infrared. Vegetation index images generated for different periods have shown the progress of disease incidence, severity and recovery of rubber plantations after fungicidal spraying. The study has demonstrated the use of remote sensing technology in identifying and delineating diseased rubber plantations. Early detection of the disease would be of immense value for taking up necessary control measures and minimize the loss.