Vol.:(0123456789) 1 3 Environmental Earth Sciences (2019) 78:42 https://doi.org/10.1007/s12665-018-8042-x ORIGINAL ARTICLE Detecting and monitoring of landslides using persistent scattering synthetic aperture radar interferometry Kourosh Shirani 1  · Mehrdad Pasandi 2 Received: 25 April 2018 / Accepted: 31 December 2018 © Springer-Verlag GmbH Germany, part of Springer Nature 2019 Abstract Persistent scatterer synthetic aperture radar interferometry (PSInSAR) is an applied time series technique to overcome limitations of InSAR (temporal and geometrical decorrelation and atmospheric delay anomalies) for monitoring of ground surface deformations. This method only monitors displacements on pixels with nearly constant temporal backscattering characteristics. In this study, datasets of ascending ALOS PALSAR (L-band) images recorded from 2006 to 2010 and descending ENVISAT ASAR (C-band) images acquisitioned between 2003 and 2010 were processed to detect and moni- tor the landslide occurred in the Noghol area, Iran. Application of the PSInSAR technique on both PALSAR and ASAR images has signifcantly improved monitoring of the Noghol landslide. However, the determination of vertical displacement of the landslide by the ASAR images processing is more correct compared to results of the PALSAR processing due to the descending orbital motion of ASAR. The ASAR images also overwhelm PALSAR images for determination of the landslide extent because of detection of more persistent scatterer points. The landslide displacement and aspect obtained by the Global Navigation Satellite System (GNSS) and PSInSAR techniques are in agreement (about 1.2–1.5 m westward in the period of 2003–2010). Particularly, processing results of the ASAR images are more similar to the GNSS measurements. Furthermore, assessment of the landslide type, mechanism and its displacement direction were possible by integration of the PALSAR and ASAR radar images with ascending and descending orbital motions, respectively. Keywords ASAR · PALSAR · Interferometry · Persistent scatterer Introduction Landslide is one of the most hazardous natural disasters threatening human life and urban structures, causing social and economic damages in many regions of the world (Bhat- tacharya et al. 2015; Bianchini et al. 2015; Jordan et al. 2017). Landslide is the gradual movement of surfcial ground layers which mostly occurs in mountainous areas. This geohazard may result in diferent environmental impacts dependent on its spatial extent and displacement intensity (García-Davalillo et al. 2014). Determination of potential areas for slope failure and estimation of their displacement and activity are highly crucial for hazard assessment (Galve et al. 2015; Piacentini et al. 2015; Dong et al. 2018a). Occur- rence of landslides in active mountainous areas may cause severe land surface erosion. Accordingly, location, extent and displacement of landslides should be accurately esti- mated by different techniques to implement prevention and mitigation strategies. The appropriate assessment of geomorphological phenomena such as landslides requires analysis of spatial and temporal patterns of displacements. Landslide monitoring is performed through comparison of landslide characteristics such as aerial extent, displacement rate, topography and soil moisture in diferent time peri- ods to evaluate landslide activity (Mantovani et al. 1996). Measurement of displacements caused by slope failure is frequently considered the most efective method to study landslides and it also makes possible monitoring of response to the triggers and evaluating efectiveness of the risk reduc- tion measures (Farina et al. 2006). Conventional monitoring techniques including extensometers, inclinometers, Global Positioning System (GPS) receivers, diferential leveling, * Kourosh Shirani k.shirani@areeo.ac.ir 1 Soil Conservation and Watershed Management Research Department, Isfahan Agricultural and Natural Resources Research and Education Center, AREEO, Isfahan, Iran 2 Department of Geology, Faculty of Science, University of Isfahan, Isfahan, Iran