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Geodetic Monitoring for Land Deformation
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This reprint focuses on original research articles on the use of geodetic measurement techniques for land deformation identification, monitoring, and impact assessment. The development and application of modern surveying techniques for understanding land deformation is of particular interest. There is a special focus on examining the current and advanced geodetic measurement techniques, including radar interferometry (InSAR), global navigation satellite systems (GNSS), light detection and ranging (LiDAR), close-range photogrammetry (CRP), Robotic Total Station (RTS), digital levelling etc., to detect and monitor land deformation.

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Keywords

  • AHP-TOPSIS
  • amplitude
  • Aniangzhai landslide
  • annual amplitude and phase
  • annual phase difference
  • Danba County
  • deformation monitoring
  • deformation prediction
  • environmental loading
  • GB-InSAR
  • geocoding
  • GNSS
  • GPS
  • GPS height time series
  • grâce
  • ground fissure extraction
  • ground-based SAR
  • hazard chain
  • hazard identification
  • highway
  • hydrological loading
  • ice rigidity inversion
  • ice velocity field
  • independent component analysis
  • InSAR
  • landslide evolution pattern
  • landslide monitoring
  • LDCmgm90
  • leveling
  • loading deformation
  • loess landform
  • long-term coordinate series
  • LSTM model
  • mining area
  • mining subsidence
  • missing data recovering
  • modified MF-FDOG algorithm
  • monument types
  • Msplit estimation
  • multi-hazard chain
  • n/a
  • noise model
  • optical image analysis
  • preference model
  • real-time processing
  • RF algorithm
  • RMS reduction rate
  • Sentinel-1 images
  • Sichuan–Yunnan region
  • soft clay
  • solution space search
  • surface mass loading
  • terrain profiles
  • thermal expansion effect
  • time-series InSAR
  • time-variable gravity
  • TLS measurements
  • UAV aerial photogrammetry
  • UAV image
  • velocity
  • vertical deformation
  • vertical displacements
  • “space-sky-ground” collaborative monitoring framework

Links

DOI: 10.3390/books978-3-0365-6443-2

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