This chapter aims to provide an overview of the most recent techniques for estimating soil moisture (SMC) using microwave radiometric techniques, with a particular focus on those most suitable for applications and described in the context of some case studies Many problems can arise in the retrieval of soil moisture from satellite, since its estimate requires low-frequency observations and relatively high ground resolutions, to be representative of the moisture spatial variations. Nonetheless, the possibility of obtaining surface feature information, particularly in areas of the world where very few data are available (e.g. large boreal and equatorial forests, deserts, poles, etc.), is appealing and therefore prompted this research. A long series of satellites with on-board multi-frequency, multi-polarization microwave radiometers (i.e. SMMR, SSM/I, AMSR-E, SMOS, and more recently AMSR2, onboard G-COMW1) have been able to retrieve information from the Earth's surface. An impressive amount of information on various surfaces has been compiled over many years, which have been very useful for interpreting and modelling satellite data. Many models and algorithms for the estimating soil moisture on a large scale have proven fundamental along with hydrological models in retrieving moisture at a soil depth which benefits many applications. Models for simulating emission from a surface are usually based on the radiative transfer theory, expressed in the simplified form of the 'tau-omega' model. The additional step which involves inverting the model for estimating the soil moisture parameters is accomplished in several ways, through use of semi-empirical or statistical inversion algorithms. In this paper an overview of the most suitable and recent methods for retrieving soil moisture content will be provided, with particular focus on those most applicative and described in the context of some case studies. In particular, an algorithm for hydrological purposes (called hereinafter HydroAlgo), able to generate maps of soil moisture content (SMC) from AMSR-E/AMSR-2 data, will be described. It was developed and implemented within the framework of the JAXA ADEOS-II/AMSR-E and GCOM/AMSR-2 programs, as well as within a project headed by the Italian Space Agency which was devoted to civil protection from floods and landslides. Keywords: soil moisture, microwave radiometry, soil emissivity, radiative transfer theory, inversion algorithms
Passive microwave remote sensing tecniques for the retrieval of surface soil moisture from space
S Paloscia;E Santi
2014
Abstract
This chapter aims to provide an overview of the most recent techniques for estimating soil moisture (SMC) using microwave radiometric techniques, with a particular focus on those most suitable for applications and described in the context of some case studies Many problems can arise in the retrieval of soil moisture from satellite, since its estimate requires low-frequency observations and relatively high ground resolutions, to be representative of the moisture spatial variations. Nonetheless, the possibility of obtaining surface feature information, particularly in areas of the world where very few data are available (e.g. large boreal and equatorial forests, deserts, poles, etc.), is appealing and therefore prompted this research. A long series of satellites with on-board multi-frequency, multi-polarization microwave radiometers (i.e. SMMR, SSM/I, AMSR-E, SMOS, and more recently AMSR2, onboard G-COMW1) have been able to retrieve information from the Earth's surface. An impressive amount of information on various surfaces has been compiled over many years, which have been very useful for interpreting and modelling satellite data. Many models and algorithms for the estimating soil moisture on a large scale have proven fundamental along with hydrological models in retrieving moisture at a soil depth which benefits many applications. Models for simulating emission from a surface are usually based on the radiative transfer theory, expressed in the simplified form of the 'tau-omega' model. The additional step which involves inverting the model for estimating the soil moisture parameters is accomplished in several ways, through use of semi-empirical or statistical inversion algorithms. In this paper an overview of the most suitable and recent methods for retrieving soil moisture content will be provided, with particular focus on those most applicative and described in the context of some case studies. In particular, an algorithm for hydrological purposes (called hereinafter HydroAlgo), able to generate maps of soil moisture content (SMC) from AMSR-E/AMSR-2 data, will be described. It was developed and implemented within the framework of the JAXA ADEOS-II/AMSR-E and GCOM/AMSR-2 programs, as well as within a project headed by the Italian Space Agency which was devoted to civil protection from floods and landslides. Keywords: soil moisture, microwave radiometry, soil emissivity, radiative transfer theory, inversion algorithmsI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.