Application of Remote Sensing in Integrated Pest Management

摘要: Cotton insect control has been weakened by historical blanket applications of pesticides over large groups fields at similar times, which contributed to landscape-level patterns resistance, dramatic increases in production costs, and environmental concerns. Classified remotely-sensed imagery facilitates a way change these trends. To improve use remote-sensing-based sampling methodologies for control, an extant simulation model was reconfigured investigate how assessment pest dispersion would vary with changes sample unit size density, based on assumption that the is randomly dispersed within particular simulated habitat class. Lloyd’s index patchiness statistic used compare outcomes from trials. Index estimates closer zero suggest regular patterns, while those nearer one indicate random dispersion, values increasingly larger than aggregation. Using this framework knowledge, cotton scouts can appropriately classified remote sensing imagery, subset sprayer characteristics, set boundaries classes geo-spatially define units create information network implementing site-specific management decisions.