A landslide change detection sample enhancement method considering terrain factors
By mosaicking landslide patches onto slope areas under the guidance of topographic factors, landslide change detection samples with obvious visual and morphological differences are generated, which solves the problem of sample scarcity in landslide change detection and enables full training and regional transfer applications of complex models.
Patent Information
- Application Number
- CN202511118875.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-11
- Publication Date
- 2026-04-21
- Estimated Expiration
- 2045-08-11
AI Technical Summary
Existing technologies lack large-scale labeled samples in landslide change detection, making it difficult to train cutting-edge intelligent models. Furthermore, existing sample augmentation methods generate samples with insufficient feature differences, affecting model training effectiveness and prediction performance.
By mosaicking landslide patches onto slope areas that differ significantly from them, and combining topographical factors such as slope and aspect, landslide change detection samples with obvious visual and morphological differences are generated, ensuring the rationality of the spatial location of the samples.
It can quickly generate a large number of landslide change detection samples with obvious visual and morphological differences, solving the problems of difficult model training and poor regional transferability under small sample conditions, and promoting the application and improvement of cutting-edge artificial intelligence models in landslide change detection tasks.