Landslide Monitoring and the Inventory Map Validation by Ensemble DInSAR Processing of ASAR and PALSAR Images (Case Study: Doab-Samsami Basin in Chaharmahal and Bakhtiari Province, Iran)

Abstract

Applications of Synthetic Aperture Sensors (SAR) and particularly Differential Interferometric Synthetic Aperture Radar (DInSAR) have provided new opportunities for detecting and monitoring of slow and even fast land deformations such as landslides and also updating their inventory maps. Employing this technique has made possible continuous detection and monitoring of small land movements with high precision over a wide spread area. In this study, two image series including 12 radar images with descending orbit acquired by ASAR sensor of ENVISAT satellite and 10 radar images with ascending orbit collected by PALAR sensor of ALOS satellite were selected and processed by the DInSAR method in order to detect landslides in the Doab-Samsami basin in Chaharmahal and Bakhtiari province, Iran. Landslides detected in the study area cover over 5959 hec according to the processing of ASAR and PALSAR images collected between 2003 and 2011, whereas landslides detected by field studies cover over 5056 hec. Based on the results of the radar processing technique for detecting and mapping of landslides, the ASAR images can provide more details of slides due to their shorter wavelengths but the PALSAR images have comparatively greater penetration and lower incoherence due to the longer wavelengths. Results of the receiver operator characteristic (ROC) method show a well agreement between the landslides map provided by the DInSAR approach and field study. The area under the curve of receiver operator characteristic (ROC) curve was estimated to be 0.95 with a standard deviation of 0.02 at 95% confidence level. The Cohen’s Kappa of 0.61 indicate relatively good conformity between classification of the detected landslide distribution in the study area based on the DInSAR method and field survey.