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E-grāmata: GNSS Remote Sensing: Theory, Methods and Applications

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The versatile and available GNSS signals can detect the Earth’s surface environments as a new, highly precise, continuous, all-weather and near-real-time remote sensing tool. This book presents the theory and methods of GNSS remote sensing as well as its applications in the atmosphere, oceans, land and hydrology. Ground-based atmospheric sensing, space-borne atmospheric sensing, reflectometry, ocean remote sensing, hydrology sensing as well as cryosphere sensing with the GNSS will be discussed per chapter in the book.

This book presents the theory and methods of GNSS remote sensing as well as its applications in the atmosphere, oceans, land and hydrology. It contains detailed theory and study cases to help the reader put the material into practice.

Recenzijas

From the book reviews:

The book shows the possibility of using GNSS technology for multidisciplinary research, which is addressed here to a wide audience, representing the community of GNSS, meteorologists, hydrologists and others, from the area of earth sciences. I highly recommend this book to students and researchers who wish to learn about how to think about new possibilities of using GNSS technology in monitoring of the earth. (Jaroslaw Bosy, Pure and Applied Geophysics, Vol. 172, 2015)

Part I GNSS Theory and Delays
1 Introduction to GNSS
3(14)
1.1 GNSS History
3(5)
1.1.1 GPS
3(2)
1.1.2 GLONASS
5(1)
1.1.3 GALILEO
6(1)
1.1.4 Beidou/COMPASS
7(1)
1.1.5 Other Regional Systems
7(1)
1.2 GNSS Systems and Signals
8(3)
1.2.1 GNSS Segments
8(2)
1.2.2 GNSS Signals
10(1)
1.3 GNSS Theory and Errors
11(2)
1.3.1 GNSS Principle
12(1)
1.3.2 GNSS Error Sources
12(1)
1.4 GNSS Observations and Applications
13(4)
1.4.1 GNSS Observation Network
13(1)
1.4.2 GNSS Applications
14(2)
References
16(1)
2 GNSS Atmospheric and Multipath Delays
17(16)
2.1 Atmospheric Refractivity
17(1)
2.2 GNSS Atmospheric Delays
18(2)
2.2.1 Neutral Atmospheric Delays
18(1)
2.2.2 Empirical Tropospheric Models
19(1)
2.3 GNSS Ionospheric Delay
20(5)
2.3.1 The Ionosphere
20(1)
2.3.2 GNSS Ionospheric Delay
21(3)
2.3.3 Empirical Ionospheric Models
24(1)
2.4 GNSS Multipath Delay
25(8)
2.4.1 Multipath Effects
25(2)
2.4.2 Multipath Variations
27(2)
2.4.3 Surface Reflection Characteristics
29(1)
References
30(3)
Part II GNSS Atmospheric Sensing and Applications
3 Ground GNSS Atmospheric Sensing
33(28)
3.1 Introduction
33(1)
3.2 Theory and Methods
34(3)
3.2.1 Estimates of GNSS ZTD
34(1)
3.2.2 Mapping Functions
35(2)
3.3 ZTD Estimate and Variations
37(14)
3.3.1 ZTD Estimates from IGS Observations
37(3)
3.3.2 Multi-Scale ZTD Variations
40(11)
3.4 GNSS Precipitable Water Vapor
51(6)
3.4.1 GNSS PWV Estimate
51(1)
3.4.2 Comparison with Independent Observations
52(1)
3.4.3 Mean PWV Characteristics
53(2)
3.4.4 Seasonal PWV Variations
55(2)
3.4.5 Diurnal PWV Variations
57(1)
3.5 3-D Water Vapor Topography
57(1)
3.6 Summary
58(3)
References
58(3)
4 Ground GNSS Ionosphere Sounding
61(32)
4.1 History
61(2)
4.2 GNSS Ionospheric Sounding
63(8)
4.2.1 DCB Determination
65(5)
4.2.2 TEC Estimate
70(1)
4.3 2-D Ionopspheric Mapping
71(8)
4.3.1 Method of 2-D Ionospheric Mapping
71(3)
4.3.2 Applications of 2-D GNSS TEC
74(5)
4.4 3-D GNSS Ionospheric Mapping
79(14)
4.4.1 3-D Ionospheric Topography
79(2)
4.4.2 Validation of GNSS Ionospheric Tomography
81(1)
4.4.3 Assessment of IRI-2001 Using GNSS Tomography
82(3)
4.4.4 Ionospheric Slab Thickness
85(3)
4.4.5 3-D ionospheric Behaviours to Storms
88(2)
References
90(3)
5 Theory of GNSS Radio Occultation
93(28)
5.1 Introduction
93(5)
5.1.1 Radio Occultation in Planetary Sciences
93(1)
5.1.2 GNSS Radio Occultation in Earth Sciences
94(4)
5.2 Principle of GNSS Radio Occultation
98(6)
5.2.1 Atmospheric Refraction
99(1)
5.2.2 Geometric Optics Approximation
100(1)
5.2.3 Spherically Symmetric Atmosphere Assumption
101(1)
5.2.4 Bending Angle and Refractive Index
102(2)
5.3 GNSS Radio Occultation Processing
104(17)
5.3.1 Calibrating and Extracting GNSS RO Observables
104(6)
5.3.2 Bending Angle Retrieval
110(3)
5.3.3 Ionosphere Retrieval
113(2)
5.3.4 Neutral Atmosphere Retrieval
115(2)
References
117(4)
6 Atmospheric Sensing Using GNSS RO
121(38)
6.1 GNSS RO Atmospheric Sounding
121(3)
6.1.1 Parameters Retrieval from GNSS RO
121(1)
6.1.2 Dry Atmosphere Retrieval (Density, Pressure and Temperature)
122(1)
6.1.3 Moist Atmosphere Retrieval
123(1)
6.1.4 1D-Var (Variational Method)
124(1)
6.2 Characteristics of GNSS RO Observations
124(12)
6.2.1 Spatial Resolution (Vertical and Horizontal Resolution)
126(1)
6.2.2 Accuracy and Precision Analysis
126(1)
6.2.3 Measurement Errors
127(2)
6.2.4 Calibration Errors
129(1)
6.2.5 Retrieval Errors
130(5)
6.2.6 Experimental Validation of RO Accuracy and Precision
135(1)
6.3 Dynamic Processes Studies with GNSS RO
136(5)
6.3.1 Tropopause and Stratospheric Waves
137(1)
6.3.2 Tropical Tidal Waves
138(1)
6.3.3 Weather Front
138(1)
6.3.4 Tropical Cyclones (TC)
139(1)
6.3.5 Atmospheric Boundary Layer (ABL)
140(1)
6.4 Weather Prediction Applications
141(2)
6.4.1 GNSS RO Data Assimilation
141(1)
6.4.2 Operational Assimilation of GNSS RO in NWP Models
142(1)
6.5 Climate Applications
143(3)
6.6 Future Application of Radio Occultation
146(13)
6.6.1 Future GNSS and GNSS RO Missions
146(1)
6.6.2 Airborne and Mountain-Top GNSS RO
146(3)
6.6.3 LEO-to-LEO Occultation
149(1)
References
150(9)
7 Ionospheric Sounding Using GNSS-RO
159(16)
7.1 Introduction
159(1)
7.2 Ionospheric Inversion
159(7)
7.2.1 Ionosphere Inversion Based on Doppler
161(2)
7.2.2 Ionosphere Inversion Based on TEC
163(1)
7.2.3 Recursive Inversion of TEC
164(1)
7.2.4 Amplitude Inversion
165(1)
7.3 Error Analysis
166(1)
7.3.1 Measurement Errors
166(1)
7.3.2 Data Processing Errors
167(1)
7.4 Ionospheric Products
167(1)
7.5 GNSS-RO Ionospheric Applications
168(7)
7.5.1 Establishing Ionospheric Models
168(1)
7.5.2 Ionospheric Tomography
168(1)
7.5.3 Monitoring Ionospheric Anomalies
169(1)
7.5.4 Ionospheric Scintillation
170(1)
References
170(5)
Part III GNSS Reflectometry and Remote Sensing
8 Theory of GNSS Reflectometry
175(40)
8.1 Introduction
175(2)
8.2 Multi-static System: Geometry and Coverage
177(1)
8.3 Specular and Diffuse Scattering
178(6)
8.4 Delay and Doppler
184(4)
8.5 Reflectivity Levels and Polarization Issues
188(4)
8.6 Scattering Theories
192(11)
8.6.1 Kirchhoff or Tangent Plane Approximation (KA)
194(4)
8.6.2 Summary of Other Methods
198(1)
8.6.3 Received GNSS Scattered Fields
199(2)
8.6.4 The Bi-static Radar Equation for GNSS Modulated Signals
201(2)
8.7 Noise and Coherence Issues
203(2)
8.8 Systematic Errors
205(1)
8.9 PARIS Interferometric Technique (PIT)
206(2)
8.10 Observables
208(7)
References
211(4)
9 Ocean Remote Sensing Using GNSS-R
215(26)
9.1 Altimetry
215(12)
9.1.1 Group Delay Altimetry
221(3)
9.1.2 Atmospheric Corrections
224(1)
9.1.3 GNSS-R Ocean Altimetric Performance
225(2)
9.2 Ocean Surface Roughness
227(14)
9.2.1 Surface Modelling
228(6)
9.2.2 Retrieval Approaches
234(2)
References
236(5)
10 Hydrology and Vegetation Remote Sensing
241(10)
10.1 Introduction
241(1)
10.2 Hydrology GNSS-Reflectometry
242(1)
10.3 Hydrology Sensing from GNSS-R
243(5)
10.3.1 Waveform Correlation
243(1)
10.3.2 Interference Pattern Technique (IPT)
244(1)
10.3.3 Hydrology Sensing from GNSS
245(1)
10.3.4 GNSS-R Scattering Properties
246(1)
10.3.5 GNSS-R Polarization
247(1)
10.4 GNSS-R Forest Biomass Monitoring
248(1)
10.5 Summary
249(2)
References
249(2)
11 Cryospheric Sensing Using GNSS-R
251(10)
11.1 Dry Snow Monitoring
251(6)
11.1.1 Dry Snow Reflection Model: Multiple-Ray Single-Reflection
252(3)
11.1.2 Dry Snow Observable: Lag-Hologram
255(2)
11.2 Wet Snow Monitoring
257(2)
11.2.1 Observations from Space-Borne GNSS-R
257(1)
11.2.2 Observations from Ground GNSS-R
258(1)
11.3 Sounding the Sea Ice Conditions
259(2)
References
259(2)
12 Summary and Future Chances
261(10)
12.1 Status of GNSS Remote Sensing
261(2)
12.1.1 Atmospheric Sensing
261(1)
12.1.2 Ocean Sensing
262(1)
12.1.3 Hydrology Sensing
262(1)
12.1.4 Cryosphere Mapping
263(1)
12.2 Future Developments and Chances
263(4)
12.2.1 More GNSS Networks and Constellations
263(1)
12.2.2 Advanced GNSS Receivers
263(2)
12.2.3 New Missions and Systems
265(1)
12.2.4 New and Emerging Applications
266(1)
12.3 Summary
267(4)
References
268(3)
Index 271
Prof. Dr. Shuanggen Jin is employed at the Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai, China. He obtained his Ph.D. in GNSS and remote sensing in 2003 at the Chinese Academy of Sciences. His areas of expertise include satellite navigation and positioning, remote sensing and climate change and space/planetary sensing and dynamics. As of July 2011, he is a Fellow of the International Association of Geodesy (IAG). He works as an editor for a lot of journals, and acts as the Editor-in-Chief for International Journal of Geosciences.