04798nam 22007215 450 991029943470332120200706092610.03-662-45931-010.1007/978-3-662-45931-7(CKB)3710000000342603(EBL)1966939(SSID)ssj0001424319(PQKBManifestationID)11801981(PQKBTitleCode)TC0001424319(PQKBWorkID)11362949(PQKB)10393771(DE-He213)978-3-662-45931-7(MiAaPQ)EBC1966939(PPN)183519523(EXLCZ)99371000000034260320150123d2015 u| 0engur|n|---|||||txtccrModern Technologies for Landslide Monitoring and Prediction /edited by Marco Scaioni1st ed. 2015.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2015.1 online resource (251 p.)Springer Natural Hazards,2365-0656Description based upon print version of record.3-662-45930-2 Includes bibliographical references at the end of each chapters.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’.Springer Natural Hazards,2365-0656Natural disastersGeotechnical engineeringRemote sensingElectrical engineeringNatural Hazardshttps://scigraph.springernature.com/ontologies/product-market-codes/G32000Geotechnical Engineering & Applied Earth Scienceshttps://scigraph.springernature.com/ontologies/product-market-codes/G37010Remote Sensing/Photogrammetryhttps://scigraph.springernature.com/ontologies/product-market-codes/J13010Communications Engineering, Networkshttps://scigraph.springernature.com/ontologies/product-market-codes/T24035Natural disasters.Geotechnical engineering.Remote sensing.Electrical engineering.Natural Hazards.Geotechnical Engineering & Applied Earth Sciences.Remote Sensing/Photogrammetry.Communications Engineering, Networks.55551621.382624.151910.285Scaioni Marcoedthttp://id.loc.gov/vocabulary/relators/edtBOOK9910299434703321Modern Technologies for Landslide Monitoring and Prediction2530877UNINA