Topography Effects on Brightness Temperature in Remote Sensing at L-band (original) (raw)
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Progresses on microwave remote sensing of land surface parameters
Science China Earth Sciences, 2012
Highly accurate observations at various scales on the land surface are urgently needed for the studies of many areas, such as hydrology, meteorology, and agriculture. With the rapid development of remote sensing techniques, remote sensing has had the capacity of monitoring many factors of the Earth's land surface. Especially, the space-borne microwave remote sensing systems have been widely used in the quantitative monitoring of global snow, soil moisture, and vegetation parameters with their all-weather, all-time observation capabilities and their sensitivities to the characteristics of land surface factors. Based on the electromagnetic theories and microwave radiative transfer equations, researchers have achieved great successes in the microwave remote sensing studies for different sensors in recent years. This article has systematically reviewed the progresses on five research areas including microwave theoretical modeling, microwave inversion on soil moisture, snow, vegetation and land surface temperatures. Through the further enrichment of remote sensing datasets and the development of remote sensing theories and inversion techniques, remote sensing including microwave remote sensing will play a more important role in the studies and applications of the Earth systems.
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021
Incidence angle diversity of space-borne L-band radiometers needs to be taken into account for a consistent estimation of surface soil moisture (SM). In this study, the Land Parameter Retrieval Model (LPRM) is applied to SMOS brightness temperatures to calibrate the effective scattering albedo (w) and the soil roughness (h 1) parameter against ERA5-land SM. The analysis is carried out for SMOS data at three different incidence angles (32.5±5°, 42.5±5° and 52.5±5°) focusing in 2016 on the three main land cover types of the Iberian Peninsula according to the Climate Change Initiative (agricultural, forest and grassland). The parameterization shows an increasing trend of w and h 1 with rise of incidence angle. The SM retrieval have been evaluated with in situ SM measurements of the REMEDHUS network on rainfed crop fields. Both compare well at the three incidence angles, obtaining high correlations (0.81-0.85), an ubRMSE around 0.04 m 3 m-3 and low bias (0-0.015 m 3 m-3).
Physical retrieval of land surface temperature using the special sensor microwave imager
Journal of Geophysical Research, 1998
This study developed a physical algorithm for retrieving land surface temperatures (LST) by using the special sensor microwave imager (SSM/I) brightness temperature measurements at 19.35 and 22.23 GHz. A nonlinear algebraic equation is obtained for the LST and is solved through the Newtonian iterative procedure. The technique does not require any surface classification because the surface emissivity variations are essentially eliminated by using two closely spaced channels. In addition, the algorithm is less influenced by ice scattering from precipitation and snow cover because of the use of low frequencies. The retrieval accuracy is first examined using simulated measurements. It is found that the root-mean-square (RMS) error is about 3.8 K, with the largest errors occurring in dry atmospheres having total precipitable water of 5.0 mm or less. The RMS error slightly increases to 4.4 K when the algorithm is applied for the actual SSM/I measurements. Large biases were found for cold temperatures where the atmospheric water vapor content may be very low. Microwave measurements are also used to derive land surface properties such as soil moisture [Wang, 1995; Jackson and O'Neill, 1987; Schmugge et al., 1992]; canopy cover [Choudhury, 1995]; and surface temperature [McFarland et al., 1990; Njoku, 1995]. In comparison with the infrared methods, the microwave measurements can provide useful information of land surface properties under nearly all weather conditions. One of the unique microwave sensors providing for land surface studies is the special sensor microwave imager (SSM/I). The SSM/I Paper number 98JD00275. 0148-0227/98/98JD-00275509.00 has seven channels, at 19.35, 22.235, 37, and 85.5 GHz with dual polarization, except 22.235 GHz, which has only vertical polarization.
2013
This article reports the potential of the ‘MADRAS’ payload on-board the Megha-Tropiques satellite for land surface studies. The analysis has been divided into two parts as application of MADRAS data for studying the land surface properties and estimation of microwave emissivity directly from MADRAS brightness temperature (TB) data by applying an in-house developed Microwave Radiative Transfer Computation Code. The derived emissivity is further used to characterize the microwave emissivity of different land surface classes. The polarization difference (PD) parameters, the difference between horizontal (H-) and vertical (V-) polarization of TBs at 18 and 36 GHz clearly discern surface features of different surface classes such as deserts, arid/semi-arid an d vegetated regions. Land surface microwave emissivity for MADRAS channels is derived on a global basis. These are inter-compared with the emissivity derived from the operational TRMM Microwave Imager and are in reasonably good agre...
Soil moisture and temperature profile effects on microwave emission at low frequencies
Remote Sensing of Environment, 1995
Soil moisture and temperature vertical profiles vary quickly during the day and may have a significant influence on the soil microwave emission. The objective of this work is to quantify such an influence and the consequences in soil moisture estimation from microwave radiometric information. The analysis is based on experimental data collected by the ground-based PORTOS radiometer at 1.4, 5.05, and 10. 65 GHz and data simulated by a coherent model of microwave emission from layered media [Wilheit model (1978)]. In order to simulate diurnal variations of the brightness temperature (TB), the Wilheit model is coupled to a mechanistic model of heat and water flows in the soil. The Wilheit model is validated on experimental data and its performances for estimating TB are compared to those of a simpler approach based on a description of the soil media as a single layer (Fresnel model). When the depth of this single layer (hereafter referred to as the sampling depth) is determined to fit the experimental data, similar accuracy in TB estimation is found with both the Wilheit and Fresnel models. The soil microwave emission is found to be strongly affected by the diurnal variations of soil moisture and temperature profiles. Consequently, the TB sensitivity to soil moisture and temperature profiles has an influence on the estimation, from microwave observations, of the surface soil moisture in a surface layer with a fixed depth (Os): the accuracy of 05 retrievals and the optimal sampling depth depends both on the variation in soil moisture and temperature profile shape.
Surface soil moisture is a key variable used to describe water and energy exchanges at the land surface/atmosphere interface. Passive microwave remotely sensed data have great potential for providing estimates of soil moisture with good temporal repetition on a daily basis and on a regional scale ( f 10 km). However, the effects of vegetation cover, soil temperature, snow cover, topography, and soil surface roughness also play a significant role in the microwave emission from the surface. Different soil moisture retrieval approaches have been developed to account for the various parameters contributing to the surface microwave emission. Four main types of algorithms can be roughly distinguished depending on the way vegetation and temperature effects are accounted for. These algorithms are based on (i) land cover classification maps, (ii) ancillary remote sensing indexes, and (iii) two-parameter or (iv) three-parameter retrievals (in this case, soil moisture, vegetation optical depth, and effective surface temperature are retrieved simultaneously from the microwave observations). Methods (iii) and (iv) are based on multiconfiguration observations, in terms of frequency, polarization, or view angle. They appear to be very promising as very few ancillary information are required in the retrieval process. This paper reviews these various methods for retrieving surface soil moisture from microwave radiometric systems. The discussion highlights key issues that will have to be addressed in the near future to secure operational use of the proposed retrieval approaches. D
IEEE Transactions on Geoscience and Remote Sensing, 2016
This paper investigates the impact of the soil moisture distribution in the top layer on the accuracy of soil moisture retrieval by microwave remote sensing methods. We modeled soil emission at L-band by coherent and noncoherent models for the different moisture distributions in the top layer. As a result, it is found that, at high moisture gradients, the difference between average moisture within the sensing depth at L-band and the moisture retrievable from remote sensing data can be more than 20% in absolute terms. In addition, high differences between Soil Moisture and Ocean Salinity (SMOS) Level 2 data and the in situ measurements were revealed in cases of high gradients. Such high gradients may be observed during some time in the top layer of the drying soil after rainfall. These differences are significantly more than the accuracy declared by SMOS development team. We proposed a simple method that allows the assessment of the type of soil moisture profile by SMOS and Global Change Observation Mission-Water "SHIZUKU" (GCOM-W1) satellites data. The procedure for simple processing of data of the two satellites is described. In addition, we compared the type of soil moisture profile retrieved from satellite data and the soil moisture profile found by in situ measurements.
Effective soil moisture sampling depth of L-band radiometry
2009
The aim of this study is to analyze the influence of the soil moisture sampling depth in the parameterization of soil emission in microwave radiometry at L-band. The analysis is based on brightness temperature, soil moisture and temperature measurements acquired over a bare soil during the SMOSREX experiment. A more detailed profile of surface soil moisture was obtained with a soil heat and water flows mechanistic model. It was found that (1) the soil moisture sampling depth depends on soil moisture conditions, (2) the effective soil moisture sampling depth is shallower than provided by widely used field moisture sensors, and (3) the soil moisture sampling depth has an impact on the calibration of soil roughness model parameters. These conclusions are crucial for the calibration and validation of remote sensing data at L-band.