Open Access
Urban and Rural Landslide Hazard and Exposure Mapping Using Landsat and Corona Satellite Imagery for Tehran and the Alborz Mountains, Iran
Author(s) -
Alexander Fekete
Publication year - 2017
Publication title -
aims geosciences
Language(s) - English
Resource type - Journals
ISSN - 2471-2132
DOI - 10.3934/geosci.2017.1.37
Subject(s) - landslide , urban sprawl , digital elevation model , human settlement , hazard , satellite imagery , geographic information system , remote sensing , natural hazard , cartography , geology , geography , physical geography , land use , geomorphology , meteorology , civil engineering , chemistry , archaeology , organic chemistry , engineering
Tehran, Karaj, Quazvin and nearby rural areas in the Alborz Mountains, Iran are prone to earthquake and landslide hazards. Risks for settlement areas, transport infrastructure and pastoralist areas exist due to a combination of natural as well as man-made factors. This study analyses data derived from satellite and airborne sensors, specifically, Landsat and declassified Corona data to identify landslide occurrence and urban sprawl. In a Geographic Information System, other data such as geology, topography, road network and river flows were integrated from various sources. A digital elevation model (DEM) was computed based on contour lines that were extracted from topographic maps. The DEM allows for mapping topographic factors such as slope angle and aspect. Finally, change detection analysis has documented urban sprawl in massive dimensions since the 1970s. A multi-criteria landslide hazard and exposure zonation map was developed for a small rural area where several settlements and segments of roads were affected by landslides. The estimated risk areas were then overlaid with real landslide occurrences. The match of hypothetical and real event occurrence areas demonstrated the feasibility of this approach. The main contribution of this paper is to inform about recent landslide risks in Iran and how certain factors can be derived from spatial information