Research on key technologies for geologic hazard risk assessment based on remote sensing and geographic information system (GIS)

In order to improve the accuracy and efficiency of geohazard risk assessment, a combination of remote sensing technology and geographic information system (GIS) is used for the study. Through the acquisition and processing of multi-source remote sensing data, a dedicated GIS database for geohazard risk assessment is constructed, and a model for disaster identification, spatio-temporal dynamic analysis and risk assessment is developed based on deep learning and GIS analysis techniques. The experimental results show that the method has significant advantages in the accuracy of disaster point identification and assessment efficiency, especially in the high slope area. The study also proposes techniques such as adaptive wavelet transform and terrain-constrained spatial autocorrelation model, which further improves the accuracy of disaster prediction. The assessment framework provides effective support for decision-making on geohazard prevention and control.