This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).
A Remote Sensing–based Intensity-Duration Curve, Faifa Mountains, Saudi Arabia
Sita Karki1,Mohamed Sultan1,Saleh A. Al-Sefry2,Hassan M. Alharbi2,Mustafa Kemal Emil1,Racha Elkadiri3,and Emad Abu Alfadail2Sita Karki et al. Sita Karki1,Mohamed Sultan1,Saleh A. Al-Sefry2,Hassan M. Alharbi2,Mustafa Kemal Emil1,Racha Elkadiri3,and Emad Abu Alfadail2
1Department of Geological and Environmental Sciences, Western Michigan University, Kalamazoo, MI, USA
2Saudi Geological Survey, Jeddah, Kingdom of Saudi Arabia
3Department of Geosciences, Middle Tennessee State University, Murfreesboro, TN, USA
1Department of Geological and Environmental Sciences, Western Michigan University, Kalamazoo, MI, USA
2Saudi Geological Survey, Jeddah, Kingdom of Saudi Arabia
3Department of Geosciences, Middle Tennessee State University, Murfreesboro, TN, USA
Received: 03 Oct 2018 – Accepted for review: 15 Nov 2018 – Discussion started: 26 Nov 2018
Abstract. Construction of intensity-duration (ID) curves and early warning systems for landslides (EWSL) are hampered by the paucity of temporal and spatial archival data. We developed methodologies that could be used for the construction of an ID curve that could be used for the construction of an EWSL over the Faifa Mountains in the Red Sea Hills. The developed methodologies relies on temporal, readily available, archival Google Earth and Sentinel-1 imagery, precipitation measurements, and limited field data. These methodologies accurately distinguished landslide-producing storms from non–landslide producing ones and identified the locations of these landslides with an accuracy of 60 %.