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

Mukhiddin JulievTurin Polytechnic University in Tashkent, Little Ring Road Street 17, 100095 Tashkent, UzbekistanW. NgIsmail MondalIndian Institute of Engineering Science and Technology, Shibpur-711103 IndiaD. BegimkulovTashkent State Technical University, University street 2, 100095 Tashkent, UzbekistanLazizakhon GafurovaNational University of Uzbekistan, University street 4, 100174 Tashkent, UzbekistanM. HakimovaKarshi engineering economics institute, Mustakillik street 225, 180100 Karshi, UzbekistanOlimaxon ErgashevaNational University of Uzbekistan, University street 4, 100174 Tashkent, UzbekistanM. SaidovaTashkent State Technical University, University street 2, 100095 Tashkent, Uzbekistan
E3S Web of Conferencesjournal2023en
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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.

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