Microwave remote sensing based small baseline subset technique for estimation of slope movement in Nainital area, India

Abstract

Landslides are very common in the Indian Himalayas especially during monsoon season. Existence of large number of faults and lineaments make the region geologically very fragile and prone to landslides at any scale. Landslides may be divided into two types: progressive and sporadic. Sporadic landslides, from which large deformations generally result in a short period, are difficult to measure. However, small progressive slides are often likely to occur prior to a sporadic slip. Therefore, progressive slides are investigated in order to enhance disaster prevention capabilities. Remote sensing and GIS based techniques have already been used extensively for landslide mapping and monitoring applications worldwide. Although, the availability of high resolution optical sensors has provided enormous thrust to the landslide research, yet atmospheric conditions like clouds and fog and restrictions on time of imaging sometimes make it difficult to fully exploit these sensors. To overcome these difficulties microwave radar remote sensing, which allow mapping irrespective of meteorological conditions both day and night, has gained its importance. Among them DInSAR technique appears to be most attractive for detecting small to large mass movements. The aim of this research is to investigate the potential of advanced DInSAR technique, Small Baseline Subset (SBAS) to estimate the temporal behaviour of slope movement in the landslide prone Nainital town of the Kumaon Himalaya. The outcomes demonstrated that SBAS technique can be effectively used to identify and estimate slope movement. It also provides the early warning support for slope instability. © 2017 IEEE.