A country-wide assessment of Iran's land subsidence susceptibility using satellite-based InSAR and machine learning

Author:

Panahi Mahdi12,Khosravi Khabat34,Golkarian Ali3,Roostaei Mahsa5,Barzegar Rahim67,Omidvar Ebrahim8,Rezaie Fatemeh29,Saco Patricia M.10,Sharifi Alireza11,Jun Changhyun12,Bateni Sayed M.13,Lee Chang-Wook1,Lee Saro29ORCID

Affiliation:

1. Division of Science Education, Kangwon National University, Chuncheon-si, Gangwon-do, Republic of Korea

2. Geoscience Data Center, Korea Institute of Geoscience and Mineral Resources (KIGAM), Yuseong-gu, Daejeon, Republic of Korea

3. Department of Watershed Management Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

4. Department of Earth and Environment, Florida International University, Miami, USA

5. Remote Sensing Group, Geological Survey of Iran (G.S.I), Tehran, Iran

6. Department of Bioresource Engineering, McGill University, Montreal, Canada

7. Department of Geography & Environmental Studies, Wilfrid Laurier University, Waterloo, Canada

8. Department of Watershed Management Engineering, University of Kashan, Kashan, Iran

9. Department of Geophysical Exploration, Korea University of Science and Technology, Daejeon, Republic of Korea

10. Centre for Water Security and Environmental Sustainability and School of Engineering, The University of Newcastle, Callaghan, NSW, Australia

11. Department of Surveying Engineering, Faculty of Civil Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran

12. Department of Civil and Environmental Engineering, College of Engineering, Chung-Ang University, Seoul, Korea

13. Department of Civil and Environmental Engineering and Water Resources Research Center, University of Hawaii at Manoa, Honolulu, HI, USA

Funder

Ministry of Science and ICT

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

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