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Potential of Ers-1 Sar Data for Snow Cover Monitoring
Abstract
The aim of this study is to develop a methodology to map the snow cover parameters (extent, state, liquid water content, snow water equivalent) from an orbiting SAR sensor (ERS-1 and eventually RADARSAT) and to use the resulting information as input to an hydrological simulation model. During the winter of 1992, ERS-1 scenes were ac uired over an agricultural region located to the EAST of Qut%ec City, in Eastern Canada. Snow cover and soil state were characterized by ground measurements over a number of sites in order to interpret quantitatively the SAR data. The pro osed methodology is based on the results of a previous study &ne at INRS-Eau. Those results suggest that a model based on the thermal properties of the snow cover could be developed to estimate the Snow Water Equivalent (SWE) with SAR data using a minimum of ground data. The preliminary analysis of the ground data indicates that a relationship between the surface temperature of the soil and the thermal resistance of the snow cover, similar to that found before, can be obtained. However, it is expected that a specific relationship could be obtained between the signal ratio and the thermal resistance of the snowpack for each soil type. Preliminary results of the SAR data analysis will be presented at the Symposium.
... Although the possibility to determine SWE with an RMSE of 71 mm seems to be of little practical use this is good information in various polarizations and the results would be much better without a couple of data points. It was shown that dry snow can be discriminated from bare ground by using ERS- 1 C-band SAR data (Bernier and Fortin, 1992) and , on the contrary, it was also reported that dry snow could not be discriminated from bare ground when single polarization data is used (Koskinen et.al, 1997). The limitations for application of C-band backscatter intensities to retrieve snow water equivalent because of the weak signal of dry snowpack was also reported in EnviSnow final report (Malnes, E., 2005). ...
One of the key problems of microwave remote sensing is the development of theoretical microwave models for terrain such as soil, vegetation, snow, forest, etc., due to the complexity of modeling of microwave interaction with the terrain. In this thesis this problem is approached from the new point of view of both empirical models and rigorous theoretical models. New information concerning radar remote sensing of snow-covered terrain and permittivity of snow has been produced. A C-band semi-empirical backscattering model is presented for the forest-snow-ground system.
The effective permittivity of random media such as snow, vegetation canopy, soil, etc., describes microwave propagation and attenuation in the media and is a very important parameter in modeling of microwave interaction with the terrain. Good permittivity models are needed in microwave emission and scattering models of terrain. In this thesis, the strong fluctuation theory is applied to calculate the effective permittivity of wet snow. Numerical results for the effective permittivity of wet snow are illustrated. The results are compared with the semi-empirical and the theoretical models. A comparison with experimental data at 6, 18 and 37 GHz is also presented. The results indicate that the model presented in this work gives reasonably good accuracy for calculating the effective permittivity of wet snow. Microwave emission and scattering theoretical models of wet snow are developed based on the radiative transfer and strong fluctuation theory. It is shown that the models agree with the experimental data.
... The capability of single-polarization and single-frequency SAR such as ERS SAR is limited in snow applications (Koskinen et al. 1994, Piesbergen et al. 1995, Paper B, Guneriussen et al. 1997). A theoretical relation between the snow thermal resistance (which is a function of the thickness and density of snow) and backscattering coefficient has been reported previously, suggesting a possibility to estimate the snow water equivalent from the backscattering) (Bernier and Fortin 1993). However, no experimental proof of this has been published. ...
... shows its capability for snowmelt monitoring at subpixel level by using multitemporal SAR images. Bernier and Fortin (1992) have previously reported on the relation between the snow thermal resistance and backscattering coefficient, which suggest a possibility to estimate the snow water equivalent from the backscattering coefficient. However, this approach is far from operational. ...
The main objective of the work described here has been to identify what type of research and development that is needed to support the user needs for new snow parameter information derived from optical, synthetic aperture radar (SAR), passive microwave radiometer (PMR) and multisensor remote sensing data. A review of both existing algorithms and available and nearfuture has been done. Snow products have been defined based on a user requirement investigation. The products cover the parameters snow cover area, snow water equivalent, snow surface albedo, snow depth, snow surface temperature, liquid water within the snowpack and snow surface wetness. The snow product specification has been used as a "driving force" to identify the type of methodology which needs to be developed. INTRODUCTION Monitoring of the seasonal snow is important for several purposes. In northern regions, the snow may represent more than half the annual runoff, putting specific demands on the models and other tools...
This paper presents the results from a study on the use of ERS-1 Synthetic Aperture Radar (SAR) data for snow parameter extraction in mountainous areas. Eight ERS-1 SAR data set and data from four field measurements from the Kvikne area in south Norway have been available. The data have been acquired during the snow melt period from April until June 1992. The SAR data have been calibrated and geocoded using Digital Elevation Model (DEM) data, and analysed in terms of evaluating the relationship between the backscattering coefficient σ0, and snow conditions. A decrease in σ0 of ∼3 dB between dry and wet snow has been observed, which indicates that ERS-1 SAR data can be used for monitoring the extent of wet snow cover. Significant differences between σ0 as a function of local incidence angle for ascending and descending passes have been observed. These differences are likely to be explained by differences in snow properties. For the dry snow cover we have an indication of the volume scattering effects.
At least one-quarter of the Lebanese terrain is covered by snow annually, thus contributing integrally to feeding surface and subsurface water resources. However, only limited estimates of snow cover have been carried out and applied locally. The use of remote sensing has enhanced significantly the delineation of snow cover over the mountains. Several satellite images and sensors are used in this respect. In this study, SPOT-4 (1-km resolution) satellite images are used. They have the capability to acquire consecutive images every 10 days, thus monitoring the dynamic change of snow and its maximum coverage could be achieved. This was applied to Mount Lebanon for the years 2001–2002. The areas covered by snow were delineated, and then manipulated with the slope angle and altitudes in order to classify five major zones of snowmelt potential. The field investigation was carried out in each zone by measuring depths and snow/water ratio. A volume of around 1100 × 10 m of water was derived from snowmelt over the given period. This is equivalent to a precipitation rate of about 425 mm in the region, revealing the considerable portion of water that is derived from snowmelt.
Describes the project to assess the potential of SAR data for snow
cover monitoring. The project is a joint project between NORUT IT and
SINTEF-NHL. The authors have acquired 16 ERS-1 SAR data sets and
conducted four field measurements from a test area in Norway in the snow
melt period of 1992. The preliminary results shows that the C-band SAR
is capable of discriminating between dry and wet snow
Experiment measurements of the variation of the radar backscattering coefficient sigma° and microwave emissivity ε with water equivalent W of dry snow are presented and compared to predictions of simple semiempirical scattering and emission models. The results show that sigma° and ε are generally dependent on the snowpack water equivalent as well as contributions by the underlying soil, and that the variation with W is a function of frequency and angle of incidence.
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Hydrological interest in mapping snow concentrates on the phase of snow depletion when at least part of the snow cover is wet. In this situation, snow has a very low backscatter coefficient, smaller than almost any land surface at X-band. Together with the independence of cloud cover and time, this unique signature of snow enables frequent and regular mapping of snow even in rugged terrain. First results from a synthetic aperture radar experiment made during the melting season—even under unfavourable conditions—clearly indicate this potential.The backscatter data used in this work are based on four seasons of scatterometer-measurements made on the alpine test site Weissfluhjoch, Davos, and on a comparison with additional backscatter data from groups in Europe and the U.S.A
Snow mapping with actives microwaves sensorsThe active and passive response to snow parameters 2. Water equivalent of dry snowEvaluatim of the potential of C-and X-bands SAR data to monitor dry and wet snow coverUtilisation de bois& de conifkres pour Ctalonner des donntes RAS
- H Rott
- C Matzler
- D Strobl
- S Bruzzi
- K G Lenhart
- S Study
- Universitat Geophysik
- M Innsbruck C
- J P Bernier
- M Fortin
- J P Bernier
- A Fortin
- M Pesant
- J P Bernier
- Fortin
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Study on SAR land applications for snow and glacier monitoring
- H Rott
- C Mätzler
- D Strobl
- S Bruzzi
- K G Lenhart