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

¹ “Tashkent Institute of Irrigation and Agricultural Mechanization Engineers” National Research University, Kory Niyoziy str., 39, 100000 Tashkent, Uzbekistan
² Turin Polytechnic University in Tashkent, Little Ring Road Street 17, 100095 Tashkent, Uzbekistan
³ Earth Observation Data Centre (EODC) for Water Resources Monitoring GmbH, Franz-Grill-Straße 9, 1030 Vienna, Austria
⁴ Indian Institute of Engineering Science and Technology, Shibpur-711103 India
⁵ Tashkent State Technical University, University street 2, 100095 Tashkent, Uzbekistan
⁶ National University of Uzbekistan, University street 4, 100174 Tashkent, Uzbekistan
⁷ Karshi engineering economics institute, Mustakillik street 225, 180100 Karshi, Uzbekistan

^* Corresponding author: mukhiddinjuliev@gmail.com

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.