Remote sensing data fusion to detect Illicit crops and unauthorized airstrips

Abstract

Remote sensing data fusion has been playing a more and more important role in crop planting area monitoring, especially for crop area information acquisition. multi-temporal data and multi-spectral time series are two major aspects for improving crop identification accuracy. Remote sensing fusion provides high quality multi-spectral and panchromatic images in terms of spectral and spatial information, respectively. In this paper, we take one step further and prove the application of remote sensing data fusion in detecting illicit crop through LSMM, GOBIA, and MCE analyzing of strategic information. This methodology emerges as a complementary and effective strategy to control and eradicate illicit crops.