Surface displacement detection using object-based image analysis, Tashkent region, Uzbekistan

Abstract

Landslides can be listed as a major natural hazard for the Bostanlik district, Uzbekistan characterized by its mountain terrain. Currently, a monitoring system is not in place, which can mitigate the numerous negative effects of landslides. The current study presents the first Earth Observation-based landslide inventory for Uzbekistan. We applied a random forest Object-Based Image Analysis (OBIA) on very high-resolution GeoEye-1 Earth observation data to detect surface displacement. While performing 10-fold cross-validation to assess the classification accuracy. Our results indicate very high overall accuracy (0.93) and user’s (0.87) and producer’s (0.91) accuracy for the surface displacement class. We determined that 5.5% of the study area was classified as surface displacement. The obtained results are highly valuable for local authorities for the management of landslides, hazard prevention, and land use planning.