Sample-free reservoir area landslide susceptibility prediction method based on domain adaptive transfer learning

The invention relates to a sample-free reservoir area landslide susceptibility prediction method based on domain adaptive transfer learning. Comprising the following steps: S1, collecting multi-source data, determining a source region of a sufficient sample, selecting a universality evaluation index suitable for thematic susceptibility analysis, and performing index analysis; s2, non-labeled samples of a target domain are determined, it is guaranteed that the selected samples have certain representativeness, a clustering method is adopted for classification, and the same number of samples are extracted from different classes; s3, adjusting an adaptive factor by adopting a feature-based domain adaptive method, and performing feature alignment on the source domain data and the target domain unmarked data; s4, selecting a proper machine learning model, taking a source domain labeled sample as a training set, predicting a susceptibility result of a target domain, and partitioning a susceptibility index by using a