Martti T. Hallikainen

The use of ERS-1 SAR data in snow melt monitoring

ERS-1 SAR data, airborne data and in situ snow data were acquired for the Sodankyla test site in northern Finland for the winters of 1991-1992 and 1992-1993. The test area consists of sparsely forested areas (pine, mixed forests, and mires) and open areas (bogs, lakes, clear-cut areas, and urban area). A set of multitemporal ERS-1 SAR images covering the two winters have been analyzed and the results have been compared with in situ surveys and a digital land-use map. The results indicate that even in the presence of forest canopies (1) wet snow can be distinguished from other soil/snow conditions (dry snow and bare ground), and (2) snow melt maps can be derived from SAR images. Snow-melt maps indicate areas fully covered with wet snow, partly melted areas and snow-free areas.

Incidence angle dependence of the statistical properties of C-band HH-polarization backscattering signatures of the Baltic Sea ice

Incidence angle dependence of three statistical parameters-the mean of the backscattering coefficient (/spl sigma//spl deg/), standard deviation, and autocorrelation coefficient of texture (/spl sigma//sub T/ and /spl rho//sub T/)-of the C-band horizontal-horizontal (HH) polarization backscattering signatures of the Baltic Sea ice are investigated using RADARSAT ScanSAR Narrow images and helicopter-borne Helsinki University of Technology Scatterometer (HUTSCAT) data. The analysis of the large amount of data shows that the relationship between the mean /spl sigma//spl deg/ in decibel scale and the incidence angle in the range from 19/spl deg/ to 46/spl deg/ is usually well described by a linear model. In general, the RADARSAT and HUTSCAT results agree with each other, and they are also supported by theoretical backscattering model calculations; the more deformed the ice, the smaller the slope between /spl sigma//spl deg/ and the incidence angle, and the higher the moisture content of snow or ice, the larger the slope. The derived /spl sigma//spl deg/ incidence angle dependencies can be used to roughly compensate the /spl sigma//spl deg/ incidence angle variation in the SAR images to help their visual and automated classification. The variability of /spl sigma//sub T/ and /spl rho//sub T/ with the increasing incidence angle is insignificant compared to the variability within each ice type. Their average changes with the incidence angle are so small that, in practice, their trends do not need to be compensated. The results of this study can be utilized when developing classification algorithms for the RADARSAT ScanSAR and ENVISAT HH-polarization Wide Swath images of the Baltic Sea ice.

Snow monitoring using radar and optical satellite data

In 1997 HUT, FEI, and FGI started a joint project that aims to develop an operational snow monitoring system in Finland. This project should apply both traditional methods (in situ measurements and hydrological models) and satellite-borne data (ERS-2 SAR and NOAA AVHRR). The emphasis of the project is to develop methods to monitor the snow melt period during spring time. The test site is located in northern Finland, and it consists of the drainage area of River Kemi, which is the largest river in Finland. A total of 18 ERS-2 SAR and six cloudless AVHRR images have been acquired from the test site during the spring of 1997. These images cover totally the snow melt period starting from dry snow and ending to snow-free ground. The optical and microwave radar data sets were compared to each other and to in situ measurements made on the weather stations which are used for current operative snow mapping. The results show that SAR-derived snow cover maps agree reasonably well with ground based observations, and they have a good correlation with AVHRR reflectance for open areas (r=0.82), and even in the presence of vegetation the correlation is relatively high (r=0.77).

Microwave radiometry of snow

Abstract Microwave radiometry provides a useful tool to monitor the properties of snow cover on a global scale. The current state of knowledge of microwave response to dry and wet snow is discussed, and the effects of various snow, soil, and atmospheric parameters to the observed antenna temperature are reviewed. Recent advances in retrieval of the water equivalent of snow cover are discussed.

Fully polarimetric microwave radiometer for remote sensing

The design, characteristics, and operation of the Helsinki University of Technology Fully Polarimetric Radiometer (FPoR) are described. The developed 36.5-GHz radiometer can be used for airborne remote sensing; however, ground-based and laboratory measurements are also possible. A direct cross-correlation technique with analog correlators, which measures all four Stokes parameters simultaneously, is applied. This paper is the first successful demonstration of an analog direct cross-correlation technique for polarimetric remote sensing radiometry. The radiometer was subjected to a variety of laboratory tests, and considerable attention is given to analysis of the characteristics of the instrument. Owing to the effective active temperature control system of the receiver, the radiometric stability of the instrument was found to be very high; test results showing stabilities below 10 mK and of 4-40 mK on time scales of 800 and 8000 s, respectively, are presented. Furthermore, the absolute accuracy of the system is analyzed to be at a sub-Kelvin level for most measurement conditions. A maritime wind vector experiment was carried out over the Gulf of Finland. The feasibility and performance of the applied correlation technique and the whole radiometer system were verified for fully polarimetric airborne measurements. The obtained brightness temperatures of the first three Stokes parameters show typical harmonic behavior with respect to the surface wind; the results suggest, however, that the model coefficients presented earlier for oceans may not be directly applicable for different conditions.

SMOS Calibration Subsystem

Interferometric radiometry is a novel concept in remote sensing that is also presenting particular challenges for calibration methods. In this paper, we describe the calibration subsystem (CAS) developed for the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) interferometer of the Soil Moisture and Ocean Salinity (SMOS) satellite. CAS is important for the overall performance of the payload as it calibrates out the differences between the multiple receivers of MIRAS. SMOS is in the final phase of development and is due to launch in 2008.

Snow-Covered Area Estimation Using Satellite Radar Wide-Swath Images

Satellite radar-based remote sensing of snow cover during the snow-melt season has been widely studied for different geographical regions, such as mountainous, open, and forested areas. However, a single method has not been found to function well on all regions. The investigations on boreal forest zone have allowed the Helsinki University of Technology (TKK) to develop a snow-covered area (SCA) method that is feasible using spatially limited European Remote Sensing-1/2 Satellite data. This paper investigates the use of wide-swath radar data for boreal forest SCA estimation for the first time. The TKK SCA method is adapted here for HH-polarization Radarsat data. The predominant aspect originated by the use of wide-swath synthetic aperture radar (SAR) data is the large variation in the radar incidence angle. The effect of incidence angle variation on SCA estimation is characterized in this paper. The foundation for operational implementation of the TKK SCA method is also established by an error propagation analysis presented in this paper. The error propagation analysis is compared with accuracy characteristics acquired between SAR and optical SCA evaluation. The performance of forest compensation, which is a key element of the TKK method, was analyzed for the wide-swath radar data. Furthermore, the correlation between the topography and the SCA estimation accuracy was examined in this paper. This paper lays the foundation for operational SCA estimation on boreal forest zone using wide-swath SAR data

EFFECTIVE PERMITTIVITY OF WET SNOW USING STRONG FLUCTUATION THEORY

The strong fluctuation theory is applied to calculate the effective permittivity of wet snow by a two-phase model with non-symmetrical inclusions. In the two-phase model, wet snow is assumed to consist of dry snow (host) and liquid water (inclusions). Numerical results for the effective permittivity of wet snow are illustrated for random media with isotropic and anisotropic correlation functions. A three-phase strong fluctuation theory model with symmetrical inclusions is also presented for theoretical comparison. In the three-phase model, wet snow is assumed to consist of air (host), ice (inclusions) and water (inclusions) and the shape of the inclusions is spherical. The results are compared with the Debye-like semi-empirical model and a comparison with experimental data at 6, 18 and 37 GHz is also presented. The results indicate that (a) the shape and the size of inclusions are important, and (b) the two-phase model with non-symmetrical inclusions provides the good results to the effective permittivity of wet snow.

HUT fully polarimetric calibration standard for microwave radiometry

This paper describes the Helsinki University of Technologys Fully Polarimetric Calibration Standard (FPCS). The developed standard generates a complete Stokes reference vector and it is applied for the end-to-end absolute calibration of a fully polarimetric microwave radiometer at 36.5 GHz. The FPCS is based on the function principle of a Gasiewski-Kunkee linearly polarized (tripolarimetric) standard, with an additional phase retardation plate to generate the fourth Stokes parameter. Design considerations and operational aspects of the standard are discussed in this paper. An advanced calibration procedure, which takes advantage of both the tripolarimetric and fully polarimetric calibration scenes to suppress calibration uncertainties, is introduced. The feasibility of the standard has been verified and the generated brightness temperatures in a sample calibration are presented. An extensive set of tests has been performed to evaluate the characteristics and performance of the calibration standard. Furthermore, the use of the advanced calibration procedure to measure the characteristics of the phase retardation plate has been successfully demonstrated. The achievable calibration accuracy is analyzed and discussed relative to requirements for maritime wind vector measurements; the results indicate that the pixel-to-pixel retrieval of the wind speed is possible with high accuracy and the retrieval of the wind direction with at least moderate accuracy. In addition to calibration of a fully polarimetric radiometer, other potential applications, e.g., linearity measurements, are discussed.

Accuracy assessment of SAR data-based snow-covered area estimation method

Employment of satellite radar-based remote sensing data for snow monitoring during the snow melt season has been widely studied by several investigators. Several methods for the estimation of snow-covered area (SCA) fraction have been developed for different types of regions. One common deficiency with the SCA estimation methods has been the lack of statistical accuracy analyses for them. In order to incorporate SCA estimates for operational use, one vital requisite is a thorough statistical analysis of the SCA estimation accuracy. This shortcoming has been addressed for boreal forest region, as an extensive statistical accuracy analysis has been carried out for the Helsinki University of Technology (TKK)-developed SCA method. The TKK SCA method was developed for boreal forest regions, and it is studied here with 24 European Remote Sensing 2 synthetic aperture radar intensity images, on a boreal-forest-dominated test area located in northern Finland. The performance of the SCA method is investigated by using reference data acquired through hydrological modeling. The accuracy analysis is carried out for several statistical variables, and the statistical interpretation is done with respect to several affecting parameters. The accuracy analysis shows a high correlation coefficient between the SCA estimates and the reference data and root mean square error values of 0.213 for open areas and 0.179 for forested areas. In addition, the TKK method employs two reference images for the SCA estimation, and the usability of multiyear reference image utilization was analyzed and proven feasible in this study.