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Satellite Soil Moisture Retrieval

  • ID: 3612357
  • Book
  • 440 Pages
  • Elsevier Science and Technology
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Satellite Soil Moisture Retrieval: Techniques and Applications offers readers a better understanding of the scientific underpinnings, development, and application of soil moisture retrieval techniques and their applications for environmental modeling and management, bringing together a collection of recent developments and rigorous applications of soil moisture retrieval techniques from optical and infrared datasets, such as the universal triangle method, vegetation indices based approaches, empirical models, and microwave techniques, particularly by utilizing earth observation datasets such as IRS III, MODIS, Landsat7, Landsat8, SMOS, AMSR-e, AMSR2 and the upcoming SMAP.

Through its coverage of a wide variety of soil moisture retrieval applications, including drought, flood, irrigation scheduling, weather forecasting, climate change, precipitation forecasting, and several others, this is the first book to promote synergistic and multidisciplinary activities among scientists and users working in the hydrometeorological sciences.

  • Demystifies soil moisture retrieval and prediction
  • Links soil moisture retrieval techniques with new satellite missions for earth and environmental science oriented problems
  • Written to be accessible to a wider range of professionals with a common interest in geo-spatial techniques, remote sensing, sustainable water resource development, and earth and environmental issues
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Section I


1. Soil Moisture from Space: Techniques and Limitations

Y.H. Kerr, J.-P. Wigneron, A. Al Bitar, A. Mialon and P.K. Srivastava

2. Available Data Sets and Satellites for Terrestrial Soil

Moisture Estimation

P.K. Srivastava, V. Pandey, S. Suman, M. Gupta and T. Islam

Section II

Optical and Infrared Techniques & Synergies

Between them

3. Soil Moisture Retrievals Using Optical/TIR Methods

P. Rahimzadeh-Bajgiran and A. Berg

4. Optical/Thermal-Based Techniques for Subsurface

Soil Moisture Estimation

M. Holzman and R. Rivas

5. Spatiotemporal Estimates of Surface Soil Moisture

from Space Using the Ts/VI Feature Space

G.P. Petropoulos, G. Ireland, H. Griffiths, T. Islam, D. Kalivas,

V. Anagnostopoulos, C. Hodges and P.K. Srivastava

6. Spatial Downscaling of Passive Microwave Data With

Visible-to-Infrared Information for High-Resolution

Soil Moisture Mapping

M. Piles and N. Sánchez

7. Soil Moisture Retrieved From a Combined Optical and

Passive Microwave Approach: Theory and Applications

C. Mattar, A. Santamaría-Artigas1, J. A. Sobrino, J.C. Jiménez

Section III

Microwave Soil Moisture Retrieval Techniques

8. Nonparametric Model for the Retrieval of Soil

Moisture by Microwave Remote Sensing

D.K. Gupta, R. Prasad, P.K. Srivastava and T. Islam

9. Temperature-Dependent Spectroscopic Dielectric

Model at 0.05-16 GHz for a Thawed and Frozen

Alaskan Organic Soil

V. Mironov and I. Savin

10. Active and Passive Microwave Remote Sensing

Synergy for Soil Moisture Estimation

R. Akbar, N. Das, D. Entekhabi and M. Moghaddam

11. Intercomparison of Soil Moisture Retrievals From In

Situ, ASAR, and ECV SM Data Sets Over Different

European Sites

B. Barrett, C. Pratola, A. Gruber and E. Dwyer

Section IV

Advanced Applications of Soil Moisture

12. Use of Satellite Soil Moisture Products for the

Operational Mitigation of Landslides Risk in

Central Italy

13. Remotely Sensed Soil Moisture as a Key Variable in

Wildfires Prevention Services: Towards New Prediction

Tools Using SMOS and SMAP Data

D. Chaparro, M. Piles and M. Vall-llossera

14. Integrative Use of Near-Surface Satellite Soil Moisture

and Precipitation for Estimation of Improved

Irrigation Scheduling Parameters

M. Gupta, P.K. Srivastava and T. Islam

15. A Comparative Study on SMOS and NLDAS-2 Soil

Moistures Over a Hydrological Basin-With

Continental Climate

16. Continental Scale Monitoring of Subdaily and Daily

Evapotranspiration Enhanced by the Assimilation of

Surface Soil Moisture Derived from Thermal Infrared

Geostationary Data

17. Soil Moisture Deficit Estimation Through SMOS Soil

Moisture and MODIS Land Surface Temperature

P.K. Srivastava, T. Islam, S.K. Singh, M. Gupta, George P. Petropoulos,

D.K. Gupta, W.Z. Wan Jaafar and R. Prasad

Section V

Future Challenges in Soil Moisture Retrieval and


18. Soil Moisture Retrievals Based on Active and

Passive Microwave Data: State-of-the-Art and

Operational Applications

J. Munõz-Sabater, A. Al Bitar and L. Brocca

19. Emerging and Potential Future Applications of

Satellite-Based Soil Moisture Products

E. Tebbs, F. Gerard, A. Petrie and E. De Witte
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Srivastava, Prashant K.
Dr. Srivastava is working in Hydrological Sciences, NASA Goddard Space Flight Center on SMAP satellite soil moisture retrieval algorithm development, instrumentation and simulation for various applications, and affiliated with IESD, Banaras Hindu University as a faculty. He received his PhD degree from Department of Civil Engineering, University of Bristol, Bristol, UK. He has published 100+ papers in peer-reviewed journals, published 4 books with reputed publishing houses and authored several book chapters and conference papers.
Petropoulos, George
Dr. Petropoulos' research work focuses on exploiting Earth Observation (EO) data alone or synergistically with land surface process models in deriving regional estimates of key state variables of the Earth's energy and water budget, including energy fluxes and soil surface moisture. He is also conducting research on the use of remote sensing technology in obtaining information about the land cover and if changes occurred from either anthropogenic activities (e.g. urbanization, mining activity) or natural hazards (mainly floods and fires). In this framework, he is researching and optimizing new image processing techniques to recently launched EO satellites, with a large part of his work focusing on the development and enhancement of EO-based operational products. As part of this research he is also conducting all-inclusive benchmarking studies to EO products or land surface models, including advanced sensitivity analysis techniques.
Kerr, Y.H.
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