Remote Sensing for Agricultural Areas

The implementation of advanced remote sensing technologies provides a high-precision framework for identifying target host populations and monitoring the spread of invasive pests like Popillia japonica across expansive agricultural landscapes. By utilizing a multi-sensor data fusion approach—integrating high-frequency satellite data from Sentinel-2 with granular aerial and UAV imagery—this methodology enables the accurate mapping of host plant connectivity and the detection of pre-symptomatic physiological stress. These technologies leverage sophisticated vegetation indices, such as NDVI and NDRE, to identify early chlorophyll decline and canopy anomalies before damage is visible to the human eye, shifting the surveillance paradigm from reactive observation to proactive risk management. Furthermore, the integration of these geospatial insights into a risk-based framework allows for the subdivision of territory into homogeneous epidemiological units, effectively optimizing the allocation of resources and increasing the statistical sensitivity of field inspections