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GNSS monitoring of the terrestrial environment : earthquakes, volcanoes and climate change /

This book, edited by Yosuke Aoki and Corné Kreemer, explores the use of Global Navigation Satellite Systems (GNSS) for monitoring the terrestrial environment, specifically focusing on earthquakes, volcanoes, and climate change. It discusses the technical aspects of GNSS data processing, applications...

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Bibliographic Details
Corporate Author: ScienceDirect (Online service)
Other Authors: Aoki, Yōsuke, 1982- (Editor), Kreemer, Corné (Editor)
Format: eBook
Language:English
Published: Amsterdam ; Cambridge, MA : Elsevier, [2024]
Subjects:
Global Positioning System.
Geology > Remote sensing.
GPS.
Géologie > Télédétection.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Intro
  • GNSS Monitoring of the Terrestrial Environment: Earthquakes, Volcanoes and Climate Change
  • Copyright
  • Contents
  • Contributors
  • Foreword
  • Chapter 1: Introduction
  • 1. History
  • 2. Measuring Earths deformation onshore
  • 3. Measuring Earths deformation offshore
  • 4. Unconventional use of GNSS
  • 5. GNSS and climate change
  • 5.1. Deformation in response to long- and short-term climate change
  • 5.2. Measuring glacier motions
  • 5.3. Earthquakes and volcanism triggered by climate change
  • 6. Future of GNSS
  • References
  • Chapter 2: Technical aspects of GNSS data processing
  • 1. GNSS measurements
  • 1.1. GNSS observation equations
  • 1.1.1. Pseudorange measurements
  • 1.1.2. Carrier-phase measurements
  • 1.1.3. Linear combination observables
  • Wide-lane- and narrow-lane combinations
  • Ionosphere-free combination
  • Geometry-free combination
  • 1.2. GNSS error sources (Fig. 2.1)
  • 1.2.1. Satellite-related errors
  • Satellite orbit error
  • Satellite clock offset
  • Satellite antenna PCO/PCV
  • Relativistic effect
  • Earth rotation effect (Sagnac effect)
  • Phase wind-up effect
  • Satellite hardware delay
  • 1.2.2. Signal propagation-related errors
  • Ionospheric delay
  • Tropospheric delay
  • Multipath effects
  • 1.2.3. Receiver-related errors
  • Receiver clock offset
  • Receiver antenna PCO and PCV
  • Receiver hardware delay
  • Receiver observation noise
  • 1.2.4. Other errors
  • Reference frame misalignment
  • Tide displacement
  • 2. GNSS positioning
  • 2.1. Precise point positioning (PPP)
  • 2.1.1. Basics of precise point positioning
  • 2.1.2. PPP ambiguity resolution (PPP-AR)
  • 2.1.3. Multiconstellation and multifrequency GNSS positioning
  • 2.2. Carrier-phase-based relative positioning
  • 2.2.1. Basics of relative positioning
  • 2.2.2. Comparison between relative positioning and PPP
  • 2.3. Real-time GNSS.
  • 2.3.1. IGS real-time products
  • 2.3.2. Real-time PPP
  • 2.3.3. Convergences of real-time PPP
  • 3. Atmosphere sounding
  • 3.1. Ground-based troposphere sounding
  • 3.1.1. GNSS tropospheric delay
  • 3.1.2. Water vapor content
  • 3.1.3. GNSS troposphere tomography
  • 3.2. Ground-based ionosphere sounding
  • 3.2.1. GNSS ionosphere delay
  • 3.2.2. Vertical ionosphere delays and global ionosphere map
  • 3.2.3. Slant ionosphere delays and their spatiotemporal variations
  • 3.3. GNSS radio occultation (GNSS-RO)
  • 3.3.1. The physical principle of GNSS-RO
  • 3.3.2. GNSS-RO data processing
  • 3.3.3. The advantages of GNSS-RO
  • 4. GNSS reflectometry
  • 4.1. GNSS interferometric reflectometry based on single antennas
  • 4.2. GNSS reflectometry based on dual antennas
  • References
  • Part I: Monitoring earthquakes and volcanoes with GNSS
  • Chapter 3: On the use of GNSS-inferred crustal strain accumulation in evaluating seismic potential
  • 1. Introduction
  • 2. Estimation of geodetic strain and moment rates
  • 2.1. From velocities to strain rates
  • 2.2. From strain rate to moment rate
  • 3. Seismic moment distribution
  • 4. Seismic-to-geodetic moment ratio
  • 4.1. Background
  • 4.2. Approach
  • 5. Geodetic potency versus earthquake numbers
  • 5.1. Background
  • 5.2. Approach
  • 6. Data
  • 7. Results
  • 8. Discussion
  • Appendix: Approximating cumulative seismic moment distribution
  • A.1. Existence of two regimes
  • A.2. Analytic results for each of the regimes
  • A.3. Approximation equations
  • References
  • Chapter 4: GNSS applications for earthquake deformation
  • 1. Introduction
  • 2. Observation of the static displacement induced by earthquakes from GNSS
  • 3. Observation of the coseismic static displacement using other techniques
  • 4. Modeling of GNSS static coseismic displacement for imaging earthquake slip distribution.
  • 5. Dynamic displacement induced by earthquakes
  • 6. Kinematic inversion: Imaging slip history during earthquake
  • 7. High-rate GNSS as small aperture seismic array
  • 8. Some earthquake properties and perspectives
  • 9. Future issues and opportunities
  • 10. Summary points
  • References
  • Chapter 5: GNSS observations of transient deformation in plate boundary zones
  • 1. Introduction
  • 2. Episodic slow slip and creep events
  • 2.1. Slow slip events at subduction zones
  • 2.1.1. Deep SSEs at subduction zones
  • 2.1.2. Shallow SSEs at subduction zones
  • 2.2. Slow slip and creep events in other settings
  • 2.3. Interplay between slow slip events and earthquakes
  • 2.4. The ubiquity of slow slip events
  • 3. Postseismic deformation and contributions from GNSS
  • 3.1. Viscoelastic relaxation
  • 3.2. Afterslip
  • 3.3. Poroelastic rebound
  • 3.4. Toward a holistic understanding of postseismic deformation
  • 4. Conclusions and future directions
  • References
  • Chapter 6: Earthquake and tsunami early warning with GNSS data
  • 1. Introduction
  • 2. Real-time GNSS positioning from a historical perspective
  • 3. Peak ground displacement
  • 4. Coseismic-based methods
  • 5. Algorithm development
  • 6. Future directions
  • 7. Final thoughts
  • References
  • Chapter 7: Measuring volcano deformation with GNSS
  • 1. Introduction
  • 2. Relating observed deformation to subsurface processes
  • 2.1. Governing equations
  • 2.2. Analytical modeling
  • 2.2.1. Spherical source
  • 2.2.2. Ellipsoidal source
  • 2.2.3. Dike and sill
  • 2.2.4. Closed cylinder
  • 2.2.5. Open cylinder
  • 2.3. Shear on the conduit
  • 2.4. Adding material complexities
  • 2.4.1. Effect of vertical and lateral heterogeneities
  • 2.4.2. Effect of viscoelasticity
  • 2.4.3. Effect of topography
  • 2.5. Some caveats
  • 2.5.1. Vertical and horizontal displacements
  • 2.5.2. Magma compressibility.
  • 2.5.3. Effect of multiple sources
  • 2.5.4. Transcrustal magma reservoir
  • 3. Observation of volcano deformation
  • 3.1. Deformation during unrest
  • 3.1.1. Magma accumulation
  • 3.1.2. Vertical magma transport
  • 3.1.3. Horizontal magma transport
  • 3.2. Coeruptive deformation
  • 3.3. Posteruptive deformation
  • 4. Observations of volcanic plumes by GNSS
  • 4.1. Atmospheric disturbance by volcanic plumes
  • 4.2. GNSS signal decay by volcanic plumes
  • 5. Recommendations
  • 5.1. Continuing observations
  • 5.2. Denser observations
  • 5.3. Modeling
  • References
  • Chapter 8: GNSS applications for ionospheric seismology and volcanology
  • 1. Introduction and observation history
  • 2. GNSS-TEC observations
  • 2.1. Phase difference and TEC
  • 2.2. From STEC to VTEC
  • 2.3. Finding signals related to earthquakes and volcanic eruptions
  • 2.4. Multi-GNSS
  • 3. Ionospheric seismology
  • 3.1. Three different atmospheric waves
  • 3.2. Discriminating the three different waves
  • 3.3. Direct acoustic waves from epicenter
  • 3.4. Knowing Mw from amplitudes of disturbances
  • 3.5. Internal gravity wave signatures
  • 4. Ionospheric volcanology
  • 4.1. Two types of ionospheric disturbances by volcanic eruptions
  • 4.2. Type 1 disturbance
  • 4.3. Type 2 disturbance
  • References
  • Part II: Monitoring climate change with GNSS
  • Chapter 9: GNSS applications for measuring sea level changes
  • 1. Introduction
  • 2. GNSS at traditional tide gauges
  • 3. Reflected GNSS signals
  • 4. Coastal GNSS-R with two or more antennas
  • 5. Coastal GNSS-IR with single antennas
  • 6. Sensing sea level variability with GNSS
  • 7. Selected highlights
  • 8. Conclusions and outlook
  • References
  • Chapter 10: GNSS application for weather and climate change monitoring
  • 1. Introduction
  • 2. Data and methods
  • 2.1. Tropospheric delay
  • 2.2. Water vapor retrieval.
  • 3. Extreme weather events
  • 4. Diurnal cycle
  • 5. Annual cycle
  • 6. Interannual variations
  • 7. Long-term trends and climate change
  • 8. Summary and outlook
  • References
  • Chapter 11: Monitoring of extreme weather: GNSS remote sensing of flood inundation and hurricane wind speed
  • 1. GNSS remote sensing for flood inundation mapping
  • 1.1. Amplitude metrics
  • 1.2. Coherency metrics
  • 1.3. Current issues
  • 2. GNSS remote sensing for hurricane wind speed retrieval
  • References
  • Chapter 12: GNSS and the cryosphere
  • 1. Introduction
  • 2. Elastic surface displacements
  • 2.1. Theory
  • 2.2. Half-space loading models
  • 2.3. Glacier dynamics
  • 2.4. Geodynamic processes in cryospheric regions
  • 3. The viscoelastic response of the Earth to cryospheric change
  • 3.1. GIA: Three pieces to the puzzle
  • 3.2. Using GNSS to measure the viscoelastic response to cryospheric change
  • 3.3. Horizontal deformation
  • 3.4. Regions of interest
  • 3.4.1. Glacial isostatic adjustment in deglaciated regions
  • 3.4.2. The global-scale response to past cryospheric change
  • 3.4.3. Viscoelastic deformation in ice-covered areas
  • 3.5. Polar case studies for GIA
  • 3.5.1. Antarctica
  • 3.5.2. Greenland
  • 4. GNSS interferometric reflectometry for the cryosphere
  • 4.1. Introduction
  • 4.2. Principles and methodology of GNSS-IR
  • 4.3. Snow depth
  • 4.4. Ice mass balance
  • 4.5. Freeze and thaw movements in permafrost areas
  • 4.6. Summary
  • Appendix
  • References
  • Chapter 13: The role of GNSS monitoring in landslide research
  • 1. Introduction
  • 2. Landslide motion and landslide types
  • 3. GNSS landslide equipment and data processing
  • 4. Case studies
  • 4.1. Åknes, Norway
  • 4.2. Almenningar, Iceland
  • 4.3. El Yunque, Puerto Rico
  • 4.4. Cà Lita, Italy
  • 5. Perspective of GNSS and other landslide deformation methods
  • References.