Weighted mapping of contaminated areas based on satellite

Excessive electrical fouling can lead to the failure of insulation devices and affect the reliable operation of the grid. Wide-area measurements using field sampling and online monitoring methods suffer from high acquisition costs, while their assessment results are also highly subjective. In this paper, a study of satellite remote sensing-based mapping of pollution areas is carried out in Yunnan Province, China, as an example. A remote sensing-based map of the entire Yunnan province is obtained using a machine learning approach, taking into account various air pollution data, emission inventories and meteorological data. The remote sensing-based map and the manual measurement-based map were combined with corresponding weights to obtain a weighted map of the polluted area.