Use of LiDAR-derived DEM and a stream length-gradient index approach to investigation of landslides in Zagros Mountains, Iran

Abstract

This paper presents an approach to stream length-gradient index analysis to identify tectonic signatures. The graded profile of the Dez River in Zagros Mountains, Iran, indicates that the area has been tectonically disturbed, and it triggers landslide hazards. The high-gradient index shows that a steeper gradient could be potentially a signature for landslides identification. The digital surface models acquired by airborne LiDAR were used in this study to generate the HRDEM. Our result shows a great potential for improving landslide investigations by implementing stream length-gradient index derived from the HRDEM in conjunction with the landslide inventories data-set in the GIS environment. We also identified a correlation between the stream length-gradient index and the graded topographic profile with slopes and landslides. This empirical approach was verified by geodata analytics and landslide inventories data-set in conjunction with field observations. This study has identified the locations of high-gradient indices with susceptible to landslides.

Keywords:

• LiDAR
• HRDEM
• tectonic signature
• stream length-gradient index
• GIS

Acknowledgements

We identified features that can provide us insights for landslide assessments. The high stream length-gradient indices in the study areas are determined in conjunction with field observations and landslide inventories available dataset. Remote sensing data such as an HRDEM is a remarkable element for extraction of the stream length-gradient index to assess landslides. Authors have used an empirical approach with geodata analytics in the GIS environment to estimate the landslide susceptible areas. This article is a part of the Ph.D. thesis that delivers an empirical approach in conjunction with the GIS analysis for landslides investigations from LiDAR point clouds.