Semi-Automatic Detection of Ground Displacement from Multi-Temporal Sentinel-1 Synthetic Aperture Radar Interferometry Analysis and Density-Based Spatial Clustering of Applications with Noise in Xining City, China

The China Loess Plateau (CLP) is the world’s most extensive and thickest region of loess deposits. The inherently loose structure of loess makes the CLP particularly vulnerable to geohazards such as landslides, collapses, and subsidence, resulting in substantial geological and environmental challeng...

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Vydáno v:	Remote sensing (Basel, Switzerland) Ročník 16; číslo 16; s. 3066
Hlavní autoři:	Chen, Dianqiang, Wu, Qichen, Sun, Zhongjin, Shi, Xuguo, Zhang, Shaocheng, Zhang, Yi, Wu, Yunlong
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 01.08.2024
Témata:	Acceleration Algorithms Anthropogenic factors Automation China Clustering data collection Datasets DBSCAN Deep learning Density Earthquakes Extreme weather Geological hazards Geology Ground motion Hazard identification High speed rail Human influences humans Image processing InSAR Interferometric synthetic aperture radar Interferometry Kinematics Land reclamation land subsidence landslide Landslides Landslides & mudslides Loess Noise measurement Plateaus Precipitation Radar Radar detection Radar geology railroads rain Rainfall Seismic engineering Slope stability Slopes Soil erosion Spatial analysis Subsidence synthetic aperture radar Time series time series analysis Topography Tibetan Plateau Qinghai China China Loess Plateau
ISSN:	2072-4292, 2072-4292
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