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Microwave Remote Sensing (microwave + remote_sensing)
Selected AbstractsEarly findings in comparison of AMSR-E/Aqua L3 global snow water equivalent EASE-grids data with in situ observations for Eastern TurkeyHYDROLOGICAL PROCESSES, Issue 15 2008A. Emre Tekeli Abstract Microwave remote sensing (RS) enables the direct determination of snow water equivalent (SWE), which is an important snow parameter for water resources management. The accuracy of remotely sensed SWE values has always been a concern. Previous studies evaluated global SWE monitoring. However, regional effects such as vegetation, snow grain size, snow density and local meteorological conditions may lead to uncertainties. Thus, regional validation studies that quantify and help to understand these uncertainties and possible error sources are important both for algorithm development and accurate SWE computation. In this study, data of Advanced Microwave Scanning Radiometer (AMSR-E)/Aqua level 3 global SWE Equal Area Scalable Earth (EASE) Grids are compared with ground measurements for 2002,2003 winter period for Eastern Turkey, which includes the headwaters of the Euphrates and Tigris rivers and is fed largely from snowmelt. Thus, accurate determination of SWE is important in optimum resource management for both Turkey and downstream nations. Analyses indicated that AMSR-E generally overestimated SWE in early season. As winter progressed, higher in situ SWE values with respect to AMSR-E were observed which led to underestimation by AMSR-E. The differences between AMSR-E and in situ SWE varied between , 218 and 93 mm. Use of in situ snow densities lead the correlation coefficient between AMSR-E and in situ SWE to increase from 0·10 to 0·32. Underestimation of SWE by AMSR-E occurs after some warm periods, while overestimations occur following refreezing. On rainy days or some days after precipitation within the warm periods, zero AMSR-E SWE values are observed. Copyright © 2008 John Wiley & Sons, Ltd. [source] Regionalization of methane emissions in the Amazon Basin with microwave remote sensingGLOBAL CHANGE BIOLOGY, Issue 5 2004John M. Melack Abstract Wetlands of the Amazon River basin are globally significant sources of atmospheric methane. Satellite remote sensing (passive and active microwave) of the temporally varying extent of inundation and vegetation was combined with field measurements to calculate regional rates of methane emission for Amazonian wetlands. Monthly inundation areas for the fringing floodplains of the mainstem Solimões/Amazon River were derived from analysis of the 37 GHz polarization difference observed by the Scanning Multichannel Microwave Radiometer from 1979 to 1987. L-band synthetic aperture radar data (Japanese Earth Resources Satellite-1) were used to determine inundation and wetland vegetation for the Amazon basin (<500 m elevation) at high (May,June 1996) and low water (October 1995). An extensive set of measurements of methane emission is available from the literature for the fringing floodplains of the central Amazon, segregated into open water, flooded forest and floating macrophyte habitats. Uncertainties in the regional emission rates were determined by Monte Carlo error analyses that combined error estimates for the measurements of emission and for calculations of inundation and habitat areas. The mainstem Solimões/Amazon floodplain (54,70°W) emitted methane at a mean annual rate of 1.3 Tg C yr,1, with a standard deviation (SD) of the mean of 0.3 Tg C yr,1; 67% of this range in uncertainty is owed to the range in rates of methane emission and 33% is owed to uncertainty in the areal estimates of inundation and vegetative cover. Methane emission from a 1.77 million square kilometers area in the central basin had a mean of 6.8 Tg C yr,1 with a SD of 1.3 Tg C yr,1. If extrapolated to the whole basin below the 500 m contour, approximately 22 Tg C yr,1 is emitted; this mean flux has a greenhouse warming potential of about 0.5 Pg C as CO2. Improvement of these regional estimates will require many more field measurements of methane emission, further examination of remotely sensed data for types of wetlands not represented in the central basin, and process-based models of methane production and emission. [source] Active microwave remote sensing for soil moisture measurement: a field evaluation using ERS-2HYDROLOGICAL PROCESSES, Issue 11 2004Jeffrey P. Walker Abstract Active microwave remote sensing observations of backscattering, such as C-band vertically polarized synthetic aperture radar (SAR) observations from the second European remote sensing (ERS-2) satellite, have the potential to measure moisture content in a near-surface layer of soil. However, SAR backscattering observations are highly dependent on topography, soil texture, surface roughness and soil moisture, meaning that soil moisture inversion from single frequency and polarization SAR observations is difficult. In this paper, the potential for measuring near-surface soil moisture with the ERS-2 satellite is explored by comparing model estimates of backscattering with ERS-2 SAR observations. This comparison was made for two ERS-2 overpasses coincident with near-surface soil moisture measurements in a 6 ha catchment using 15-cm time domain reflectometry probes on a 20 m grid. In addition, 1-cm soil moisture data were obtained from a calibrated soil moisture model. Using state-of-the-art theoretical, semi-empirical and empirical backscattering models, it was found that using measured soil moisture and roughness data there were root mean square (RMS) errors from 3·5 to 8·5 dB and r2 values from 0·00 to 0·25, depending on the backscattering model and degree of filtering. Using model soil moisture in place of measured soil moisture reduced RMS errors slightly (0·5 to 2 dB) but did not improve r2 values. Likewise, using the first day of ERS-2 backscattering and soil moisture data to solve for RMS surface roughness reduced RMS errors in backscattering for the second day to between 0·9 and 2·8 dB, but did not improve r2 values. Moreover, RMS differences were as large as 3·7 dB and r2 values as low as 0·53 between the various backscattering models, even when using the same data as input. These results suggest that more research is required to improve the agreement between backscattering models, and that ERS-2 SAR data may be useful for estimating fields-scale average soil moisture but not variations at the hillslope scale. Copyright © 2004 John Wiley & Sons, Ltd. [source] Improvement of TOPLATS-based discharge predictions through assimilation of ERS-based remotely sensed soil moisture valuesHYDROLOGICAL PROCESSES, Issue 5 2002Valentijn R. N. Pauwels In this paper, we investigate the possibility to improve discharge predictions from a lumped hydrological model through assimilation of remotely sensed soil moisture values. Therefore, an algorithm to estimate surface soil moisture values through active microwave remote sensing is developed, bypassing the need to collect in situ ground parameters. The algorithm to estimate soil moisture by use of radar data combines a physically based and an empirical back-scatter model. This method estimates effective soil roughness parameters, and good estimates of surface soil moisture are provided for bare soils. These remotely sensed soil moisture values over bare soils are then assimilated into a hydrological model using the statistical correction method. The results suggest that it is possible to determine soil moisture values over bare soils from remote sensing observations without the need to collect ground truth data, and that there is potential to improve model-based discharge predictions through assimilation of these remotely sensed soil moisture values. Copyright © 2002 John Wiley & Sons, Ltd. [source] Third and fourth Stokes parameters in polarimetric passive microwave remote sensing of rough surfaces over layered mediaMICROWAVE AND OPTICAL TECHNOLOGY LETTERS, Issue 12 2008Leung Tsang Abstract We consider the four Stokes parameters in microwave emission from a layered medium with the top interface being a rough surface. The rough surface varies in one horizontal direction so that azimuthal asymmetry exists in the 3-D problem. Dyadic Green's functions of multilayered media are used to formulate the surface integral equations. Periodic boundary conditions are used. The numerical results show that the presence of the layered media below the rough surface reduces the vertical and horizontal brightness temperatures. The interaction between the rough surface and the layered media also enhance the third and fourth Stokes parameters. In particular, the fourth Stokes parameter can be large for such geometrical configurations. Results show that the nonzero third and fourth Stokes parameters exist for all frequencies and are particularly large when the rough surface has large slope. © 2008 Wiley Periodicals, Inc. Microwave Opt Technol Lett 50: 3063,3069, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.23892 [source] | ||||||||||