Satellite Soil Moisture Retrieval

Techniques and Applications

Prashant K. Srivastava, George P. Petropoulos, Y.H. Kerr

• Publisher: Elsevier
• Year: 2016
• Print ISBN: 9780128033883
• eBook ISBN: 9780128033890
• Topic: Biological Sciences
• Subtopic: Environmental Science
• Index: Biological Sciences

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

Section III

Microwave Soil Moisture Retrieval Techniques

Chapter 7

Soil Moisture Retrieved From a Combined Optical and Passive Microwave Approach

Theory and Applications

C. Mattar*; A. Santamaría-Artigas*; J.A. Sobrino^†; J.C. Jiménez-Muñoz^{† *} University of Chile, Santiago, RM, Chile
^† Universitat de València, Valencia, Spain

Abstract

With the current remote sensing technology developments, and in particular those at L-band (1.2–1.4 GHz) frequencies such as the Soil Moisture and Ocean Salinity and the Soil Moisture Active and Passive missions, new approaches concerning passive microwave and its combination with existing optical technologies have become of special interest for the estimation of surface soil moisture. One of these new approaches is the combination of optical and passive microwave data based on a semiempirical approach derived from the general radiative transfer equation. The objective of this chapter is to present some applications of the combined optical-passive microwave approaches over several spatial scales and land cover types. Additionally, the influences of vegetation indexes such as the leaf area index or the normalized difference vegetation index are also described. Finally, as a future perspective of the possible use of thermal infrared information such as land surface temperature or land surface emissivity rather than vegetation indexes is also commented on.

Keywords

Soil Moisture; Optical-Passive Microwave; SMOS; MODIS; NDVI

Acknowledgments

The authors would like to thank the projects Fondecyt-Initial (CONICYT/ref.: 11130359) and the Ministerio de Ciencia e Innovación (CEOS-Spain, AYA2011-29334-C02-01).

1 Introduction

Surface soil moisture (SM) retrieved from new L-band remote sensing satellites such as the Soil Moisture and Ocean Salinity (SMOS) and the Soil Moisture Active and Passive (SMAP) missions generate a new scenario in the current trends to analysis of the global water cycle. In the case of SMOS, an explorer mission of the European Space Agency (ESA), the 5 years of L-band radiometry information (Kerr et al., 2001, 2012) create a challenge to develop and adapt combined approaches for the better estimation of SM at regional and global scales. The combined optical-passive microwave method is one of these approaches, which consist of the adaptation of the tau-omega model (Ulaby et al., 1986) to estimate the surface SM.

The tau-omega model estimates the surface’s brightness temperature by assuming two emission layers related to the soil and vegetation. This model was adapted for several land cover types gathered in the L-band microwave emission of the biosphere (L-MEB) model, which is the core of the SMOS mission for the retrieval of SM values (Wigneron et al., 2007). Several new approaches to improve the estimates generated from the SMOS mission have been published, and the combined optical-passive microwave approach is one of them.

The use of the synergic optical-passive microwave approach at regional scales could generate interesting consequences for the improvement of surface SM retrievals used for hydrological and forecast modeling. However, the theoretical concepts of the combined approach need to be analyzed in its assumptions and the possible application to different land cover types at global scale. Thus, the objective of this chapter is to describe the theoretical optical-passive microwave approach, its application at in situ and regional levels, and provide further perspective to adapt thermal infrared (TIR) information for the synergistic approach.

2 Radiative Transfer Equation

The basis of radiative transfer in the passive microwave has a relation to the Rayleigh-Jens approximation, in which the brightness temperature is equivalent to the land leaving radiance emitted in the microwave domain. The contribution of different brightness temperature totalizes the brightness temperature observed by a remote sensor (TB_p). These terms can be summarized in the general radiative equation proposed by K...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• Dedication
• List of Contributors
• Author Biographies
• Preface
• Section I: Introduction
• Section II: Optical and Infrared Techniques & Synergies Between them
• Section III: Microwave Soil Moisture Retrieval Techniques
• Section IV: Advanced Applications of Soil Moisture
• Section V: Future Challenges in Soil Moisture Retrieval and Applications
• Index