A SAR image study of a snow-covered area in the French Alps

ELSEVIER

A SAn Image Study of a Snow-Covered Area in the French Alps Michel Fily,* Jean-Pierre Dedieu, t and Sylviane Surdyk* T w o radar experiments were performed in the French Alps in December 1989 and April 1990. The main objective was to study the signature of snow-covered terrain for different snow conditions. The E-SAn (Band X)from DLR was used, and the data were processed by CNES. The study area was situated at Les Arcs, a ski resort, with elevations ranging from 1600 m to 2600 m. Ground data included snow depth, liquid water content, and snow and air temperature. A SPOT image was available for December and aerial photographs for the following July. In December there was almost no snow, while in April the area was completely snow covered. Because of the highly varying topography, a DEM (digital elevation model) was used to correct the image geometrically and radiometrically. A simple scheme was developed for these corrections. The snow was slightly wet in April and many features appearing on the image are due to the snow itself or to the snow-ground interface. In particular, the ski runs are clearly visible due to the different structure of the packed snow. Only a small area could be compared between December and April due to technical problems in December. It appears that the snow-free and snowcovered signatures are very similar for this particular terrain, which is a golf course in summer; that is, smooth wet soil with short grass. These experiments show that geometrical corrections are necessary when studying mountainous area. Furthermore calibrated data are required to compare snow-free and snow-covered terrain when the snow is slightly wet and therefore slightly absorbant with respect to the electromagnetic waves.

*Laboratoire de Glaciologie et de G6ophysique de l'Environnement, CNRS, Universit~ Joseph Fourier, Saint Martin d'Heres, France ~Laboratoire de la Montagne Alpine, Institut de G~ographie Alpine, Grenoble, France Address correspondence to Michel Fily, Laboratoire de Glaciologie et de G~ophysique de rEnvironnement, CNRS, Universit~ Joseph Fourier, B.P 96, 38402 Saint Martin d'Heres Cedex, France. Received 1 May 1993; revised 25June 1994. REMOTE SENS. ENVIRON. 51:253-262 (1995) ©Elsevier Science Inc., 1995 655 Avenue of the Americas, New York, NY 10010

INTRODUCTION Knowledge of the snow water equivalent (SWE) is essential for the forecasting of snowmelt runoff and the management of water resources for hydropower, irrigation, industry, and human needs (Hall and Martinec, 1985). For climate studies the area of snow cover is important mainly because of the high albedo of snow which modifies the radiative transfer at the earth surface (Barry, 1985). For avalanche forecasting, many snow parameters are relevant such as depth, density, liquid water content (LWC), and stratification (M/itzler, 1987a; Sergent et al., 1993). Snow-covered area and snow water equivalent change rapidly over the year in alpine areas. The areas involved are large, and ground data are often difficult to acquire. Therefore, satellite imagery is already extensively used to provide the necessary snow parameters (Lucas and Harrison, 1990; Rott, 1990). Optical sensors provide information on the variation of snow covered area (Dozier, 1984; Barry, 1990), the snow equilibrium line on glaciers (Rott, 1990; Dedieu et al., 1989), and the size of the grains of the upper layers of snow (Bourdelles and Fily, 1993; Warren, 1982). Optical imagery has three major limitations: First, no data are available when clouds are present; second, penetration of the radiation is very limited in the corresponding wavelengths-from a few centimeters in the visible to a few millimeters in the near infrared (Warren, 1982); and, last, no differences are obvious between dry and wet snow because the water and ice refraction indices are similar even if the snow that has been wet has larger grain sizes and may therefore be less reflective in the near-infrared part of the spectrum (Dozier, 1989). Microwave sensors are largely independent of cloud cover and the microwave penetration depth provides information on the snow volume (M/itzler, 1987b; Ulaby et al., 1981; 1982; 1986). Moreover, the dielectric properties of water and snow are different in the centimeter wavelength domain (M/itzler et al., 1984). Therefore, 0034-4257 / 95 / $9.50 SSDI 0034-4257(94)00049-S

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these sensors are very promising tools for the study of snow. Microwave radiometry has already been used to obtain information on snow cover and its characteristics (Hallikainen and Jolma, 1986; Chang et al., 1976; Foster et al., 1984; Kunzi et al., 1982; Wang et al., 1992). But the spatial resolution of the radiometers is only of a few tens of kilometers, which is a severe limitation when studying small drainage basins or glaciers. Also, the emissivity of wet snow is very similar to that of snow-free ground (M~itzler and H/ippi, 1989). Synthetic aperture radars offer two major advantages: They are all-weather instruments, and their spatial resolution is comparable to that which can be obtained using optical instruments, that is, a few tens of meters. Many studies are available on SAR capabilities over snow (Rott, 1984; Rott et al., 1985; 1988; Shiet al., 1991; Ulaby et al., 1986; Bernier et al., 1994). They need to be pursued to allow the use of the large quantity of SAR data currently available as well as that which will become available in the near future. Data from the European ERS1 and Japanese JERS are already available. Soon the Canadian Radarsat will be launched, and multifrequency radar will be onboard the American Earth Observing Program satellites. The objective of this article is to show what was obtained from a SAR image on the Alps, the problems encountered when using this image, and the processing scheme used. This experiment was performed as part of a study funded by the French CNES (Centre National d'Etudes Spatiales) to study the capabilities of SAR over snow in order to better define the characteristics of an operational satellite-borne SAR to be launched at the beginning of the next century. The characteristics of this SAR which is mainly developed by the CNES are not definitely defined: They will be multipolarization and multifrequency. Major problems were due to the topography, and a large part of this article is devoted to the description of a simple scheme for geometrical and radiometrical corrections. A radiometric interpretation of the image is given which focuses on the snow radiometry and on the importance of the underlying terrain.

DATA DESCRIPTION Geographical Location The area studied is located in the Vanoise range of the Northern French Alps (Fig. 1). The image is centered over the Les Arcs ski resort above the Isere Valley at Bourg Saint Maurice. This area was chosen because it is an experimental drainage basin for the Laboratoire de la Montagne Alpine (LAMA) in Grenoble, meaning that ground data are available on a regular basis. The mean slope faces the northwest, with a fairly constant altimetric profile in our area of interest. The site elevations are between 1600 m and 2500 m, and the slope between 10 ° and 30 °

Figure 1. Geographical location of the SAR images acquired in April 1990 (dashed rectangle) with the location of the two automatic weather stations and the snow-depth measurement network. The bond rectangle is the studied subal-ea.

SAR Images The SAR images were acquired on 3 December 1989 at 5:30 p.m. local time and 27 April 1990 at 10:30 a.m. by the German E-SAR aboard a DLR aircraft. They were acquired in X band (9.6 GHz) with HH and VV polarization. Image synthesis was performed by the CNES at Toulouse. The spatial resolution is 1.5 m along-range and 1 m along-track. Unfortunately, no calibration of the radar was performed, and only a relative radiometric interpretation can be made. On 3 December 1989, the incidence angle of the radar was misadjusted (from nadir to 60°), and only the area below 2000 m elevation was covered. Also, the image quality was fairly poor. The snow cover was very sparse on this date with only a few patches of 20-30 cm dry snow.

On the other hand, the image quality for 27 April 1990 is quite good. Most of the work was performed on one of these images with VV polarization covering our area of interest (Fig. 2). The radar incidence angle is roughly between 20 ° and 80 °. On this date the area was completely covered by 1-2 m of snow. On the image, the forested areas and many ski lifts are clearly seen. The dark area on the right side of the image is

SAR Study of Alps Snow-CoveredArea 255

at representative sites and snow depth isocontours are given in Figure 10 from 26 April 1990 records. The snow metamorphism is very rapid at this time of the year because of the temperature difference between day and night, from - 3°C to + 4°C on 27 April. During the night, the upper layer of the snow cover freezes, and an ice crust is formed. During the day the temperature increases, and the snow melts and becomes wet. Some snow characteristics such as temperature, liquid water content (LWC), density, and stratigraphy were measured at different elevations the day following the SAR acquisition at the same time, that is, about 10:30 a.m. local time (Table 1). The meteorological situation was the same on both days.

SPOT Image and Aerial Photography A SPOT image was acquired on 3 December at 10:34 a.m. local time, the same day as the SAR acquisition. It is a panchromatic image with one visible channel between 0.51/~m and 0.73 gm. Its spatial resolution is 10 m × 10 m. A set of four aerial photographs was taken in July 1990 by the French National Geographic Institute (IGN) at the 1/20000 scale. At this time of the year, the terrain is completely snow-free, and the photos are very useful in obtaining the underlying ground characteristics for the interpretation of the images. These photos were digitized at a 5 m pixel resolution.

Digital Elevation Model (DEM) For precise geographical positioning, a 1 / 10,000 topographic map was used. From this map the elevation contours were digitized and numerically interpolated to generate a DEM with a 10-m spatial resolution.

Tab/e 1. Snow Characteristics as Measured at Different Elevations on 28 April 1990~

Figure 2. X-band SAR image taken on 27 April 1990, over Les Arcs. The polarization is VV. The image is neither geometrically nor radiometrically corrected. The valley is on the left. See Figure 1 for geographical location.

Site 1: Elevation: 2235 m Snow depth: 215 cm Temperature at 9:45 a.m.: Tar = 3 . 6 ° C Tsua=O°C T10~m= - 1.00C Density: 265 kg m -3 at 10 cm and 309 kg m-3 at 30 cm Stratigraphy: refrozen crust at 12 cm, 32 cm and 44 cm Site 2 Elevation: 2090 m Temperature at 10:35 am: T~ Density: 568 kg m -3 between Stratigraphy: site located on a

located east of the crest and is in shadow (not seen by the radar).

Ancilliary Data Ground Data Ground data were available from the sites at different locations (Fig. 1). Two automatic weather stations continuously recorded air temperature, pressure, and humidity. Snow depth was measured by 16 stakes located

Snow depth: 135 cm = 4.8°C, Tsua=0°C, T10cm= - 1 . 0 ° C the surface and 10 em ski track, very hard layer below 10 cm

Site 3 Elevation: 1870 m Snow depth: 80 cm Temperature at 11:00 a.m.: T~r = 8.90C, isothermal snow cover at 0°C Density: 358 kg m-3 near the surface, 546 kg m-3 at 20 em depth Volumetric snow water content: 1.4% near the surface, 1.8% at 20 cm depth Stratigraphy: • grain size about 1 mm diameter between 0 cm and 10 cm • coarse grain (3 mm) between 10 cm and 16 cm • fine grain (1 mm) between 16 cm and 47 cm • ice below The sites are located on Figure 10.

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SAR

GEOMETRIC AND RADIOMETRIC CORRECTIONS Geometric Corrections Because we need to merge many sets of data (SPOT, DEM, photographs, SAR scenes), they have to be properly geolocated. Different methods are used for different types of data. An overview of all the input and output data is given by the flow chart in Figure 3. The SPOT image was geometrically corrected using a classical interpolation based on a polynomial fit with control points. The aerial photographs were digitized and then merged into an orthophotographic image using a resampling method with the DEM. These methods are not e~cient for the SAR images because the deformation due to the variation of the ground resolution across track is too large. The only constant geometric parameter is the range resolution (Fig. 4), which was equal to 1.5 m in our case. The ground resolution and the pixel size depend on the local incidence angle, which is the difference between the radar incidence angle and the terrain slope. The pixel size is given by the projection of the ground resolution onto a horizontal surface. Many algorithms are described in the literature for the geometric correction of SAR images (Raggam et al., 1986; Rott et al., 1988; Toutin and Carbonneau, 1992). We chose a very simple scheme which could be easily performed by any SAR image user. Two steps were necessary: First a coarse preliminary correction was performed from the mean terrain slope and the flight parameters; then ground control points were used to fit a polynomial geometric transformation.

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For the first step, eight control points were chosen along a profile perpendicular to the flight direction to determine the elevation profile. Only one elevation profile was selected in our area of interest because the terrain was very regular, but many profiles could have been chosen for a more complex terrain. Many control points were easily found because of the presence of metal ski lifts, which are precisely located on the map and easily seen on the image. The plane was located from the flight characteristics; its altitude was 3927 m. There was no precise positioning system on-board and only an inertial system was available. From the terrain profile and the aircraft position a crude variation of the pixel size maybe computed assuming a constant slope between each control point:

Figure 3. Flow chart showing the available data and the final products after corrections.

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SAR Study of Alps Snow-Covered Area 257

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given by the CNES. The intensity of the backscattered radiation is proportional to the solid angle illuminating the pixel and then to the ground resolution as defined in Figure 4. Therefore, the variations of the brightness across track are partly due to topographic effects. It is clearly seen in Figure 2 or 7 that there is a general decrease of the brightness from left to right. This is because the ground resolution is larger on the left side of the image. From the geolocated SAR image and the DEM the slope of each pixe! and hence the local incidence angle 0 could be computed (Fig. 4). The slopes were averaged for 20 m x 20 m areas to take into account the elevation and the location uncertainties. As said earlier the measured intensity is proportional to the ground resolution which is itself inversely proportional to sin(0). In order to eliminate the topographic effects, a corrected intensity (Ic..... ted) can be computed from 0 and the measured intensity (/initial) using Ic. . . . .

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Figure 8. Geoloeated and radiometrieally corrected April SAR image. The border of the image corresponds to the limits of the digital elevation model. North is upward. The pixel values along the black transect are given in Figure 9. The white rectangle represents the area shown on the thematic map (Fig. 10).

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SAR Study of Alps Snow-Covered Area 259

Figure 10. Thematic map corresponding to the analysis of the Figure 8 SAR image. The snow depth isocontours are from 26 April records.

seen in Figure 9, where pixel values are given before and after correction along the profile shown in Figure 8. IMAGE ANALYSIS

Snow Radiometry from the Radar Images As the radar was not calibrated, no absolute backscattering coefficients could be computed. In any event, some features concerning the snow cover can be observed, and comparisons can be made between different images assuming that the backscattering of some targets such as coniferous is very stable. From many measurements done on a test area in the Swiss Alps, M/itzler and Hiippi (1989) found three typical signatures corresponding to snow-free ground, dry snow, and wet snow. Snow-free ground has a higher baekseattering coefficient, and dry snow has almost the same signature because it is transparent at the E-SAR frequency. On the other hand, wet snow has a very low backscattering coefficient because it is opaque due to the high absorption coefficient of water (Stiles and Ulahy, 1980). As the snow was slightly wet (up to 1% LWC) at

the time of the radar measurement, it should appear darker than other surfaces on the April image. Our case appears to be more complex. A dark area appears clearly on the left part of the image just above the Arcs 1800 buildings (zone marked as wet soil in Fig. 10). However, this area also appears very dark in December when there were only a few patches of thin, dry (and therefore transparent) snow. Second, many features are seen in Figure 8 that are due to underlying terrain characteristics such as small torrent beds. From those observations it can be concluded that the snow was partly transparent in April and that the low backscattering is also due to the terrain characteristics. The transparency of snow shows that the LWC is very low as stated in Table 1: dry snow at 10:35 a.m. at 2090 m altitude and about 1% LWC at 11:00 a.m. and 1870 m. The terrain shows a low backscattering there because it is a golf course during the summer. This means that it is a smooth lawn above a wet, soft soil. Therefore, the underlying ground characteristics have an important effect on the backscattering coefficient. This importance has already been stated by other authors (Bernier et al., 1994).

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The other interesting characteristics of the image in terms of snow radiometry is the high backscattering of downhill ski runs (Fig. 10). A lot of mechanical compaction work is carried on the ski runs during the ski season. At the time of the measurements, the ski resort was closed, and no distinct features were apparent on the surface of the snow; but the snow is nevertheless much more stratified there with very hard layers. From in situ stratigraphy we found that the density of snow was a lot higher on the ski runs (500-570 kg/m 3) than elsewhere (270-350 k g / m 3) and that a very hard layer was present at 10 cm below the surface. These hard and rough layers with ice pieces make the snow cover nonuniform, explaining the observed high backscattering. Close examination of the image shows that some snow avalanches have very high backscattering (Fig. 10). These avalanches appear on the ground as rough snow piles, thus resulting in high surface backscattering. In conclusion, the signature of the snow covered area appears to be a complex mixture of underlying surface effects (grass or moraines), snow volume effects (ski runs), and even snow surface effects (avalanches). A single signature cannot be given for snow; only the comparison between a snow-free image and a snowcovered image could give useful information.

(a)

Comparison between the Radar Images and the Optical Data December 1989 SPOT+ SAR The 3 December 1989 SPOT panchromatic image was interpolated at a 5 m pixel size and geometrically corrected for a pixel-to-pixel comparison with the SAR data taken the same day. The resulting images are given in Figure 11. On the SPOT image (Fig. lla), the patches of snow appear in white and the forested areas in grey. On the SAR image (Fig. llb), the snow patches do not appear because dry snow is transparent, but a large wet area (golf course) appears clearly in dark in the center of this image. This information is not provided by the SPOT optical data, and it shows that the underlying ground characteristics have an important effect on the backscattering coefficient. 1990 April SAR +July Aerial Photographs The April geometrically and radiometrically corrected SAR image was merged with the orthophotography generated from the DEM and a mosaic of four aerial panchromatic views. The result is shown in Figure 12 as a color composite image which is used to show which type of information on the surface cover may be obtained from each sensor. On both images the borders between forested and unforested areas appear clearly and are the same. The coniferous forest appears in a very dark blue with a characteristic SAR texture. The surfaces with high backscattering and also high re-

(b)

Figure 11. SPOT (a) and radar (b) images taken on 3 December 1989. See text for explanation.

flectance are in yellow (bare and dry soils) or in red (buildings, chairlifts, protective walls along the roads). All the grass areas were a uniform grey color on the original photographs but appear in different shades on the composite image. In winter, all this low vegetated area is an alpine ski resort, and, as seen before, the backscattering coefficient is higher on the ski runs, which results in a darker blue on the image. Also the wet areas are brown on the SAR image but cannot be

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Figure 12. Composite image from 1990 April 27 SAR image and July aerial photos. See text for explanation.

distinguished on the photographs. The map shown in Figure 10 was derived from the interpretation of the SAR corrected image (Fig. 8) and this color composition (Fig. 12).

This work was funded by the French Centre National d~Etudes Spatiales. We are grateful to the STAR company of the Les Arcs ski resort for their contribution. REFERENCES

CONCLUSION From the above study, some conclusions can be made. 1. Geometrical and radiometrical corrections of radar images are crucial in mountain terrain because of the important effects of the topography. A simple scheme is proposed which can be easily implemented by any end user of SAR images. 2. SAR gives no information on thin dry snow but allows the detection of wet soils and faults which are invisible on optical imagery. 3. The snow signature is not unique because some highly variable terrain characteristics have an important effect on dielectric characteristics: wetness, stratigraphy, and roughness. Because snow, even slightly wet, is transparent, information can be obtained only from comparison between snow-free and snow-covered images of the same area. This implies a good absolute calibration of the radar and radiometrical correction of the images.

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