Land Surface Remote Sensing in Continental Hydrology

Nicolas Baghdadi, Mehrez Zribi

• Editorial: ISTE Press - Elsevier
• Año: 2016
• ISBN:
  9780081011812
• Categoría: Physical Sciences
• Categoría: Hydrology

The continental hydrological cycle is one of the least understood components of the climate system. The understanding of the different processes involved is important in the fields of hydrology and meteorology.In this volume the main applications for continental hydrology are presented, including the characterization of the states of continental surfaces (water state, snow cover, etc.) using active and passive remote sensing, monitoring the Antarctic ice sheet and land water surface heights using radar altimetry, the characterization of redistributions of water masses using the GRACE mission, the potential of GNSS-R technology in hydrology, and remote sensing data assimilation in hydrological models.This book, part of a set of six volumes, has been produced by scientists who are internationally renowned in their fields. It is addressed to students (engineers, Masters, PhD), engineers and scientists, specialists in remote sensing applied to hydrology. Through this pedagogical work, the authors contribute to breaking down the barriers that hinder the use of Earth observation data.

• Provides clear and concise descriptions of modern remote sensing methods
• Explores the most current remote sensing techniques with physical aspects of the measurement (theory) and their applications
• Provides chapters on physical principles, measurement, and data processing for each technique described
• Describes optical remote sensing technology, including a description of acquisition systems and measurement corrections to be made

1

Characterization of Soil Surface Properties Using Radar Remote Sensing

Nicolas Baghdadi; Mehrez Zribi

Abstract

Soil surface characteristics (SSC) play a key role in the understanding of different processes taking place at the soil–vegetation–atmosphere interface (runoff, infiltration, soil erosion, exchange of water and energy streams). Until the 1990s, the only observations used for the modeling of this interface were limited and often unrepresentative of the spatial scales modeled. Radar remote sensing now allows spatial parameters to be accessed for the monitoring of the soil surface and the modeling of its functioning. In fact, signals acquired by radar are strongly correlated to some physical variables that are linked to soil surface conditions, such as soil moisture and surface roughness. The assimilation of these data in functional models (hydrologic, erosion, SVAT (Soil–Vegetation–Atmosphere Transfer) etc.) has shown a clear improvement in the simulation of physical processes.

Keywords

Dubois model; Oh model; Radar backscattering; Radar Remote Sensing; Radar signal; Roughness; Salinity; Soil parameters; Surface moisture; Texture composition

1.1 Thematic introduction

Soil surface characteristics (SSC) play a key role in the understanding of different processes taking place at the soil–vegetation–atmosphere interface (runoff, infiltration, soil erosion, exchange of water and energy streams). Until the 1990s, the only observations used for the modeling of this interface were limited and often unrepresentative of the spatial scales modeled [LOU 91]. Radar remote sensing now allows spatial parameters to be accessed for the monitoring of the soil surface and the modeling of its functioning. In fact, signals acquired by radar are strongly correlated to some physical variables that are linked to soil surface conditions, such as soil moisture and surface roughness. The assimilation of these data in functional models (hydrologic, erosion, SVAT (Soil–Vegetation–Atmosphere Transfer) etc.) has shown a clear improvement in the simulation of physical processes (see Chapters 11 and 12).

Active microwave remote sensing (radar) is particularly well adapted to the characterization of soil surface conditions in agricultural fields. Contrary to optical remote sensing techniques, Synthetic Aperture Radar (SAR) allows all-weather measurements, independently of meteorological and lighting conditions (cloud cover, day/night, etc.). The disadvantage of optical techniques based on thermal infrared, connecting soil moisture to the surface temperature, is their dependence on ambient conditions. Radar uses microwave frequencies (wavelengths between 1 mm to 1 m) that are very sensitive to the geometric and dielectric properties of the measured medium, which are themselves dependent on surface parameters (roughness, soil moisture, soil composition, vegetation cover). A SAR signal also depends on different instrumental parameters, polarization, incidence angle and radar wavelength. In the presence of vegetation, the scattered radar signal is a combination of soil and vegetation contributions. The soil contribution decreases when the radar wavelength decreases.

The first studies using radar remote sensing started at the end of the 1970s with in situ or airborne scatterometers [ULA 78]. Important scientific developments started in the 1990s with satellite and airborne SAR (ERS-1/2, JERS, SIR-C, RADARSAT-1/2, PALSAR-1/2, ASAR, TerraSAR-X, COSMO-SkyMed, etc.). Most studies were carried out in the L-band (wavelength ~22 cm), C-band (wavelength ~6 cm), and more recently, X-band (wavelength ~3 cm). The first satellite SAR sensors accessible to the scientific community had an instrumental configuration of monopolarization and a single incidence angle (ERS-1/2, JERS). The second generation of radar sensors with new instrumental configurations (RADARSAT, ASAR/ENVISAT, PALSAR/ALOS, TerraSAR-X, COSMO-SkyMed, Sentinel-1) allowed the scie...