Record Display for the EPA National Library Catalog


OLS Field Name OLS Field Data
Main Title Modern Technologies for Landslide Monitoring and Prediction [electronic resource] /
Other Authors
Author Title of a Work
Scaioni, Marco.
Publisher Springer Berlin Heidelberg : Imprint: Springer,
Year Published 2015
Call Number GB5000-5030
ISBN 9783662459317
Subjects Geography. ; Remote sensing. ; Geology. ; Telecommunication.
Internet Access
Description Access URL
Collation XII, 249 p. 84 illus., 78 illus. in color. online resource.
Due to license restrictions, this resource is available to EPA employees and authorized contractors only
Contents Notes
Close-Range Photogrammetric Techniques for Deformation Measurement: Applications to Landslides -- A Fixed Terrestrial Photogrammetric System for Landslide Monitoring -- A New Approach Based on Terrestrial Remote Sensing Techniques for Rock Fall Hazard Assessment -- Multi-Temporal Terrestrial Laser Scanning Survey of a Landslide -- Micro-Scale Landslide Displacements Detection Using Bayesian Methods Applied to GNSS Data -- Analysis of Microseismic Activity within Unstable Rock Slopes -- The State of the Art of SPH Modelling for Flow-Slide Propagation -- Predictability of A Physically-based Model for Rainfall-induced Shallow Landslides: Model Development and Case Studies -- Monitoring Landslide Activities in the Three Gorges Area with Multi-Frequency Satellite SAR Datasets -- Radar Technologies for Landslide Detection, Monitoring, Early Warning and Emergency Management -- A new Approach to Satellite Time Series Co-registration for Landslide Monitoring. Modern Technologies for Landslide Investigation and Prediction presents eleven contributed chapters from Chinese and Italian authors, as a follow-up of a bilateral workshop held in Shanghai on September 2013. Chapters are organized in three main parts: ground-based monitoring techniques (photogrammetry, terrestrial laser scanning, ground-based InSAR, infrared thermography, and GNSS networks), geophysical (passive seismic sensor networks) and geotechnical methods (SPH and SLIDE), and satellite remote-sensing techniques (InSAR and optical images). Authors of these contributes are internationally-recognized experts in their respective research fields. Marco Scaioni works in the college of Surveying and Geo-Informatics at Tongji University, Shanghai (P.R. China). His research fields are mainly Close-range Photogrammetry, Terrestrial Laser Scanning, and other ground-based sensors for metrological and deformation monitoring applications to structural engineering and geosciences. In the period 2012-2016 he is chairman of the Working Group V/3 in the International Society for Photogrammetry and Remote Sensing, focusing on 'Terrestrial 3D Imaging and Sensors'.