Year-end Sale % OFF 
Abstract
Persistent Scatterer Interferometry (PSI) has been widely used for landslide studies in recent years. This paper investigated the spatial patterns of PSI point targets and landslide occurrences in the Arno River basin in Central Italy. The main purpose is to analyze whether spatial patterns of Persistent Scatterers (PS) can be recognized as indicators of landslide occurrences throughout the whole basin. The bivariate K-function was employed to assess spatial relationships between PS and landslides. The PSI point targets were acquired from almost 4 years (from March 2003 to January 2007) of RADARSAT-1 images. The landslide inventory was collected from 15 years (from 1992–2007) of surveying and mapping data, mainly including remote sensing data, topographic maps and field investigations. The proposed approach is able to assess spatial patterns between a variety of PS and landslides, in particular, to understand if PSI point targets are spatially clustered (spatial attraction) or randomly distributed (spatial independency) on various types of landslides across the basin. Additionally, the degree and scale distances of PS clustering on a variety of landslides can be characterized. The results rejected the null hypothesis that PSI point targets appear to cluster similarly on four types of landslides (slides, flows, falls and creeps) in the Arno River basin. Significant influence of PS velocities and acquisition orbits can be noticed on detecting landslides with different states of activities. Despite that the assessment may be influenced by the quality of landslide inventory and Synthetic Aperture Radar (SAR) images, the proposed approach is expected to provide guidelines for studies trying to detect and investigate landslide occurrences at a regional scale through spatial statistical analysis of PS, for which an advanced understanding of the impact of scale distances on landslide clustering is fundamentally needed.
Highlights
Landslides are a major type of natural hazards around the world
In order to fulfill this concept, the bivariate K-function analysis was utilized in this study, providing a practical tool for analyzing spatial patterns between two groups of point datasets: Persistent Scatterer Interferometry (PSI) point targets acquired and processed from RADARSAT-1 images and landslide occurrences mapped in the inventory across the
The primary purpose is to investigate the spatial patterns between different PSI point targets and landslide occurrences, so as to understand if PSI benchmarks are spatially clustered or randomly distributed with reference to different types of landslides across the basin
Summary
Landslides are a major type of natural hazards around the world. They may pose a great threat to human beings and to infrastructure objects, leading to enormous losses in lives and economics. Is a country very susceptible to landslide hazards. 5831 deaths and the homelessness of more than 700,000 people in Italy [1,2]. Landslides can generate direct economic losses of 1–2 billion Euros, representing 0.15% of the national gross domestic production (GDP) [3]. Persistent Scatterer Interferometry (PSI) is an Interferometric Synthetic Aperture Radar (InSAR)
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
