Land surface remote sensing in continental hydrology

목차 (Table of Contents)

• CONTENTS
• Foreword = xiii
• Acronyms = xvii
• Introduction = xli
• Chapter 1 Characterization of Soil Surface Properties Using Radar Remote Sensing / Nicolas Baghdadi ; Mehrez Zribi = 1
• 1.1 Thematic introduction = 1
• 1.2 Description of soil parameters = 3
• 1.2.1 Soil roughness = 3
• 1.2.2 Soil surface moisture = 7
• 1.3 Radar signal sensitivity to soil parameters = 9
• 1.3.1 Sensitivity of radar signal to soil roughness = 9
• 1.3.2 Sensitivity of the radar signal to soil moisture = 11
• 1.3.3 Soil salinity = 13
• 1.3.4 Soil texture composition = 14
• 1.4 Modeling of radar backscattering on bare soil = 15
• 1.4.1 Description of the IEM = 16
• 1.4.2 Description of the Dubois model = 18
• 1.4.3 Description of the Oh model = 19
• 1.4.4 Numerical modeling = 19
• 1.5 Estimation of soil parameters at plot scale based on high and very high spatial resolution data = 21
• 1.5.1 Case of bare soil = 21
• 1.5.2 Case of soil with vegetation cover = 29
• 1.6 Estimation of soil parameters with medium spatial resolution = 30
• 1.7 Prospects = 31
• 1.8 Key points = 33
• 1.9 Bibliography = 34
• Chapter 2 Estimation of Soil Water Conditions Using Passive Microwave Remote Sensing / Ramata Magagi ; Yann Kerr ; Jean-Pierre Wigneron = 41
• 2.1 General introduction = 41
• 2.2 Principle of passive microwave soil moisture estimation = 43
• 2.2.1 Effect of surface roughness on the brightness temperature of bare soil = 44
• 2.2.2 Effect of vegetation on the brightness temperature of vegetation-covered soil = 44
• 2.2.3 Effect of soil moisture on the signal's sensitivity to surface roughness and vegetation = 46
• 2.2.4 Penetration depth of the signal = 46
• 2.3 Methods for surface soil moisture estimation = 48
• 2.3.1 Inversion of direct models : 1-P, 2-P, and N-P inversion of the L-MEB model = 49
• 2.3.2 Statistical approaches = 51
• 2.3.3 Explicit inversions = 52
• 2.3.4 Inversion problems = 53
• 2.4 Soil moisture products derived from passive microwave space-borne observations = 55
• 2.4.1 Spatial passive microwave remote sensing evolution for soil moisture estimation = 55
• 2.4.2 Validation and representativeness of the large scale AMSR-E, SMOS, and SMAP SM retrievals = 57
• 2.4.3 Example of SMOS soil moisture evaluation over the agricultural sites of CanEx-SM10 and SMAPVEX12 = 58
• 2.4.4 Qualitative analysis of the soil moisture values estimated by SMOS and AMSR-E over the agricultural and forest sites of CanEx-SM10 = 59
• 2.5 Methods for disaggregating satellite soil moisture products derived from passive microwave observations = 61
• 2.6 Other moisture products derived from passive microwave observations = 64
• 2.6.1 Moisture index = 64
• 2.6.2 Root zone moisture = 65
• 2.7 Principal applications = 66
• 2.7.1 Applications in meteorology (NWP), climate modeling, drought = 66
• 2.7.2 Applications in hydrology, flood risks, agriculture, forestry, etc. = 67
• 2.7.3 Applications in Nordic environments = 67
• 2.8 Conclusion = 67
• 2.9 Key points = 68
• 2.10 Acknowledgments = 69
• 2.11 Bibliography = 69
• Chapter 3 Using Satellite Scatterometers to Monitor Continental Surfaces / Pierre-Louis Frison ; Lionel Jarlan ; Eric Mougin = 79
• 3.1 Introduction = 79
• 3.2 Principle of acquisition for scatterometers = 80
• 3.3 The main scatterometers = 85
• 3.3.1 Fixed antenna scatterometers = 85
• 3.3.2 Rotating antennae scatterometers : SeaWinds = 88
• 3.4 Thematic applications = 89
• 3.4.1 Surface-water hydrology = 92
• 3.4.2 Monitoring vegetation = 98
• 3.5 Conclusions and prospects = 105
• 3.6 Key points = 106
• 3.7 Bibliography = 107
• Chapter 4 Optical Remote Sensing of Snow Cover / Marie Dumont ; Simon Gascoin = 115
• 4.1 Introduction: the importance of snow cover = 115
• 4.2 Optical properties of snow = 116
• 4.3 Properties of snow cover observable by optical remote sensing = 119
• 4.3.1 The presence of snow = 119
• 4.3.2 Albedo and optical radius, light-absorbing impurities = 124
• 4.4 The use of data produced from snow-covered surfaces in hydrology = 126
• 4.4.1 What can be done about clouds? = 126
• 4.4.2 Generating hydro-climatic indicators = 128
• 4.4.3 Hydrological modeling = 129
• 4.5 Possibilities = 130
• 4.6 Key points = 132
• 4.7 Bibliography = 132
• Chapter 5 Snow Characterization Using Radar Imaging / Monique Bernier ; Jean-Pierre Dedieu ; Yannick Duguay = 139
• 5.1 Introduction = 139
• 5.2 Radar interaction and snow cover = 140
• 5.2.1 Physical characterization of snow = 140
• 5.2.2 Electromagnetic modeling of radar signals = 146
• 5.2.3 The polarimetric study of snow = 153
• 5.3 Mapping snow cover = 158
• 5.3.1 Mapping the extent of snow coverage = 158
• 5.3.2 Mapping snow-water equivalent = 160
• 5.3.3 Specific environments = 166
• 5.4 Current users and future prospects = 174
• 5.5 Key points = 175
• 5.6 Bibliography = 176
• Chapter 6 Spatial Altimetry and Continental Waters / Jean-Francois Cretaux ; Stephane Calmant = 183
• 6.1 Introduction = 183
• 6.2 Some generalities concerning the use of satellite altimetry for hydrology = 187
• 6.3 Case studies using radar and laser altimetry = 191
• 6.3.1 Lakes in East Africa = 191
• 6.3.2 Tibetan lakes = 195
• 6.4 Using altimetry to estimate river flow = 204
• 6.5 Impact of adjustments and uses of altimetry = 210
• 6.5.1 The context and the role of spatial altimetry = 210
• 6.5.2 Case studies with radar altimetry = 212
• 6.6 Conclusion and prospects = 217
• 6.7 Key points = 222
• 6.8 Bibliography = 222
• Chapter 7 Radar Altimetry for Monitoring the Antarctic Ice Sheet / Frederique Remy = 231
• 7.1 Introduction = 231
• 7.2 Antarctica = 232
• 7.2.1 The continent of superlatives = 232
• 7.2.2 The Antarctic machine = 234
• 7.2.3 What and how to observe? = 235
• 7.3 Polar altimetry = 237
• 7.3.1 Some specifics of altimetry on polar ice caps = 237
• 7.3.2 Methodology of evaluating a time series for measuring height = 239
• 7.4 Contribution to climatology = 240
• 7.5 Antarctica in a stationary state = 243
• 7.5.1 Surface topography = 243
• 7.5.2 Constraints of the models = 245
• 7.6 Temporal variations = 246
• 7.6.1 Very different times and signals = 246
• 7.6.2 Lake draining = 247
• 7.6.3 Global mass balance = 249
• 7.6.4 Acceleration of outlet glaciers : can they bolt? = 250
• 7.7 Summary and perspective = 251
• 7.8 Key points = 252
• 7.9 Bibliography = 252
• Chapter 8 Monitoring Water Mass Redistributions on Land and Polar Ice Sheets using the GRACE Gravimetry from Space Mission / Frederic Frappart ; Guillaume Ramillien ; Lucia Seoane = 255
• 8.1 Introduction = 255
• 8.2 Post-processing techniques for global solutions = 256
• 8.2.1 Empirical methods = 257
• 8.2.2 Statistical methods = 259
• 8.2.3 The inverse methods = 262
• 8.3 Regional approaches = 263
• 8.3.1 Mascons = 263
• 8.3.2 The regional method = 264
• 8.4 Applications = 265
• 8.4.1 Applications in land hydrology = 265
• 8.4.2 Applications in glaciology = 272
• 8.5 Perspectives = 275
• 8.6 Key points = 276
• 8.7 Bibliography = 276
• Chapter 9 Applications of GNSS-R in Continental Hydrology / Erwan Motte ; Alejandro Egido ; Nicolas Roussel ; Karen Boniface ; Frederic Frappart = 281
• 9.1 Introduction = 281
• 9.1.1 History = 281
• 9.1.2 Chapter outline = 282
• 9.2 Background on measurement and GNSS-R observable techniques = 283
• 9.2.1 GNSS-R by waveform analysis = 284
• 9.2.2 GNSS-R by analysis of changes in the signal-to-noise ratio = 289
• 9.3 Altimetry = 291
• 9.3.1 Measuring the snowpack = 292
• 9.3.2 Measuring the water level = 296
• 9.4 Soil moisture = 302
• 9.4.1 cGNSS-R methodology (bistatic scatter) = 303
• 9.4.2 Example of monitoring the moisture level of an agricultural plot using cGNSS-R = 307
• 9.4.3 Monitoring soil moisture by IPT : methodology = 308
• 9.4.4 Example of monitoring the moisture level of an agricultural field by IPT = 310
• 9.5 Vegetation cover = 312
• 9.5.1 Biomass estimation by cGNSS-R : theoretical aspects = 312
• 9.5.2 Example of forest biomass estimation by cGNSS-R = 314
• 9.5.3 Monitoring vegetation growth using IPT = 315
• 9.6 Conclusions and perspectives = 315
• 9.6.1 IPT network = 315
• 9.6.2 Aerial/balloon measurements = 316
• 9.6.3 Spaceborne measurements = 316
• 9.7 Key points = 317
• 9.8 Bibliography = 318
• Chapter 10 Energy Balance of Continental Surfaces and the Use of Surface Temperature / Jean-Pierre Lagouarde ; Gilles Boulet = 323
• 10.1 Introduction = 323
• 10.2 Energy budget and surface temperature = 324
• 10.2.1 Radiative budget = 325
• 10.2.2 Convective fluxes = 326
• 10.2.3 Soil conductive flux = 328
• 10.2.4 Energy budget equation = 329
• 10.2.5 Significance of surface temperature = 330
• 10.3 Surface temperature data = 331
• 10.3.1 Directional effects in thermal infrared = 332
• 10.3.2 Impact of atmospheric turbulence on measurement uncertainty = 334
• 10.3.3 Current data and their limitations : a need for new missions in the TIR domain = 336
• 10.4 Estimating evapotranspiration = 337
• 10.4.1 Residual methods = 338
• 10.4.2 Contextual methods = 341
• 10.4.3 Assimilation of TIR data = 343
• 10.4.4 Operational methods adapted to the availability of satellite data = 344
• 10.5 Other applications = 345
• 10.5.1 Agriculture and forestry = 346
• 10.5.2 Climate monitoring and health of ecosystems = 350
• 10.5.3 Biogeochemical cycles and soil pollution = 351
• 10.5.4 Hydrology = 351
• 10.6 Prospects = 353
• 10.7 Key points = 353
• 10.8 Bibliography = 354
• Chapter 11 Remote Sensing Data Assimilation : Applications to Catchment Hydrology / Delphine Leroux ; Thierry Pellarin = 363
• 11.1 Introduction = 363
• 11.2 Hydrological models = 364
• 11.3 Satellite data available for assimilation = 365
• 11.4 Description of data assimilation = 367
• 11.5 Examples of assimilation in hydrological models = 373
• 11.5.1 Assimilation of surface soil moisture = 373
• 11.5.2 Assimilation of river water level = 378
• 11.5.3 Soil water storage assimilation = 381
• 11.6 Application example : assimilation of SMOS's soil moisture in the DHSVM hydrological model, on the Oueme catchment, Benin = 384
• 11.6.1 Study area and hydrological model = 384
• 11.6.2 Assimilation of SMOS surface soil moisture in the hydrological model = 387
• 11.7 A favorable future to assimilation in hydrology = 393
• 11.8 Key points = 394
• 11.9 Bibliography = 394
• Chapter 12 Satellite Data Assimilation: Application to the Water and Carbon Cycles / Jean-Christophe Calvet ; Patricia De Rosnay ; Alina L. Barbu ; Souhail Boussetta = 401
• 12.1 Assimilation: what is the purpose? = 401
• 12.2 Analyses of the vegetation and soil moisture for numerical weather prediction = 405
• 12.3 Water : from the soil to the river = 413
• 12.4 Natural sinks and sources of CO₂ = 419
• 12.5 Conclusions and perspectives = 422
• 12.6 Key points = 422
• 12.7 Bibliography = 423
• Glossary = 429
• List of Authors = 449
• Index = 453
• Scientific Committee = 457