Measurement of land subsidence due to wasting of tabular massive ground ice using differential JERS-1 SAR interferometry: Bylot Island test site
Paris W. Vachon
Canada Centre for Remote Sensing
588 Booth St., Ottawa, Ontario K1A 0Y7 CANADA
Telephone: (613) 995-1575
Fax: (613) 947-1385
E-mail: paris.vachon@ccrs.nrcan.gc.ca
Dirk Geudtner
German Aerospace Research Establishment (DLR)
Institute of Radio Frequency Technology
P.O. Box 1116
D-82230 Wessling GERMANY
Telephone: +49-8153-28-2363
Fax: +49-8153-28-1449
E-mail: Dirk.Geudtner@dlr.de
A. Laurence Gray
Canada Centre for Remote Sensing
588 Booth St., Ottawa, Ontario K1A 0Y7 CANADA
Telephone: (613) 995-3671
Fax: (613) 947-1383
E-mail: laurence.gray@ccrs.nrcan.gc.ca
Karim Mattar
Canada Centre for Remote Sensing
588 Booth St., Ottawa, Ontario K1A 0Y7 CANADA
Telephone: (613) 995-3987
Fax: (613) 947-1383
E-mail: karim.mattar@ccrs.nrcan.gc.ca
Brian J. Moorman
Earth Science Program
University of Calgary
2500 University Drive N.W.
Calgary, Alberta T2N 1N4 CANADA
Telephone: (403) 220-4835
Fax: (403) 282-6561
E-mail: moorman@ucalgary.ca
Abstract:
Tabular massive ground ice differs from permafrost in that it is not ice mixed with soil, but rather, is ice which is covered by soil. Ground ice may be of considerable vertical extent and originates either with the burial of glacial ice or with the in situ subsurface aggradation of ice. Ground ice is of interest since known occurrences are decreasing in volume (i.e. the ground ice is melting) leading to subsidence of the soil covering. The rate of ground ice volume decrease could be an indicator of global climate change. We attempted to measure the wasting of ground ice using differential synthetic aperture radar (SAR) interferometry (InSAR). JERS-1 is well suited to this requirement since its L-band wavelength is compatible with the degree of subsidence that is expected and is less susceptible to loss in coherence over long repeat periods than C-band radars such as ERS and RADARSAT. Our measurements were taken over a test site on Bylot Island in the Canadian Arctic. Unfortunately, the demise of the JERS-1's tape recorder prevented acquisition of a long time series of data, as was originally intended. We report here on the limited JERS-1 data sets that were obtained, which are supplemented by ERS, RADARSAT, and CV580 airborne InSAR measurements.
Introduction and Scientific Objectives
Recent climatic warming has initiated the melting of ground ice throughout permafrost regions. This is resulting in increased landslide activity and significant terrain disturbance. A direct consequence of these alterations to the land surface is damage to ecosystems and infrastructure (e.g. roads, buildings, and pipelines).
Before landslides or significant surface disturbance is initiated, melting ground ice is thought to cause small changes in the morphology and elevation of the ground surface. With the detection of these surface changes, mitigative measures can be taken to retard the ground ice melt before landslides occur. Unfortunately, conventional techniques cannot provide the three essential elements required to detect the initial stages of ground ice melt: extensive spatial coverage (tens of square kilometers), frequent measurements (monthly or less), and fine-resolution change detection measurements (sub-meter).
Cross-track airborne interferometric SAR is now commonly used to create DEMs of the land surface (Gray et al., 1995; Orwig et al., 1995; Moorman et al., 1998). In certain situations, repeat-pass satellite interferometric SAR can also be used to generate DEMs of the Earth's surface and produce associated temporal derivatives such as glacier flow rates (Vachon et al., 1996). One of the limiting factors in using satellite SAR data for interferometry are the changes in the character of the ground surface over the time period between satellite passes. These changes can result in a reduction in the coherence between images and thus limit the potential for generating a DEM (Vachon et al., 1995).
The decorrelation between SAR images is of interest in detecting melting ground ice. Areas where there is relatively greater change in the character of the ground surface over time (e.g. where ground ice is melting) will be highlighted in a coherence image as areas of localized decorrelation. However, due to the slow rate of surface subsidence associated with the initiation of ground ice melt, longer observation periods are required for a detectable amount of surface change to develop. Unfortunately, as the repeat period of the satellite increases, so does the potential for widespread scene decorrelation due to other processes (e.g. vegetation growth, snow accumulation/ablation, or changes in the soil moisture content).
The coherence between SAR scenes (i.e. the ability to interferometrically correlate the two images) is dependent on a number of factors other than just ground surface change (Vachon et al., 1995). In generating interferometric images from satellite SAR data, both the orbital and sensor characteristics of the satellite play a major role in the suitability of the data for interferometric processing. Orbital considerations include the repeat period of the satellite and its across-track repeatability. Sensor considerations include spatial resolution, incidence angle, radar wavelength, and signal-to-noise ratio. For example, the longer wavelength of the JERS-1 sensor (L-band) is theoretically less sensitive to the small changes that would effect the ERS and RADARSAT sensors (C-band), thus decreasing resolution, but at the same time decreasing the level of background noise.
The optimal system for locating melting ground ice would show a loss of coherence in the areas of melt, while coherence is retained throughout the rest of the scene. The sensor configurations available to us have enabled examination of the loss of coherence within a scene due to geomorphological processes that occur at different rates.
Our study area is on southern Bylot Island in the eastern Canadian Arctic (Fig. 1). This site was chosen since it was known to contain a variety of proglacial massive ground ice bodies that are currently melting at varying rates (Klassen, 1993). The area's cold and dry climate results in little vegetation growth or snow accumulation, thus enhancing the potential for detecting ice-melt related changes.
Currently, 10 of the 18 larger glaciers within the southern portion of Bylot Island are in retreat (Fig. 2). The other eight have shown no signs of change within the last century (Moorman, 1998). Generally, the moraines surrounding the retreating glaciers have ice cores (Fig. 3). Ground ice bodies observed on the island range in size from 1 m3 to over 200,000 m3. Since the mean annual air temperature in the region is roughly -9.5°C, melting of the ice-cored moraines does not occur spontaneously following deglaciation as would occur in more temperate environments. Some ground ice bodies were found to exist in areas that have not been glaciated for tens of thousands of years. The ultimate result of ground ice melt in this environment is slope failure, mudslides (Fig. 4), and the development of thermokarst lakes, many of which can be observed throughout the Bylot Island's lowlands.
Our key interest is in long timeframes between SAR acquisitions. In Table I we list the terrain types of interest on Bylot Island and the expected rates and causes of scene decorrelation. Note that over short timeframes it is easy to see the effects of flowing water in the usual SAR image (Fig. 5a).
Table I: Terrain types and expected causes of scene decorrelation.
| Rate of Scene Decorrelation | Terrain Type | Cause |
| Rapid (1 day) | Streams and slush flows | Movement of water or slush |
| Moderate (1 week) | Glaciers and steeply-sloping terrain | Ice movement, snow accumulation/ablation, erosion |
| Slow (1 month) | Barren, gently-sloping upland terrain | Change in moisture content, snow accumulation/ablation, erosion |
| Very slow (1 year) | Valley bottoms, well-drained gravel | Lack of vegetation and moisture, stays windswept and dry |
We generated amplitude, coherence, and phase images from ERS-1/2 (C-band), RADARSAT (C-band), and JERS-1 (L-band) image pairs for roughly the same area near the termini of glaciers C79 and C93. The characteristics of these three radar systems are compared in relation to observed scene changes and the rate of geomorphic activity and the suitability of each sensor for detecting ground ice melt is discussed. Our intention was to collect several years of observations with JERS-1. Unfortunately, those plans failed with the demise of JERS-1's Mission Data Recorder.
Methods and Research Activities
The SAR data acquired and processed to interferograms for this study are outlined in Table II. In addition to the satellite SAR data, we also obtained a DEM derived from the CCRS airborne SAR operated in cross-track InSAR mode (Gray et al., 1995), as shown in Fig. 5b. We received eight JERS-1 data sets that we attempted to combine interferometrically in a variety of ways, focussing on both inter- and intra-annual cases. All of the inter-annual cases considered had baselines that were too large to support interferogram generation. The intra-annual cases generally had low coherence, with the exception being the 10 August/23 September 1996 acquisitions.
Table II: Satellite SAR interferograms generated for this study.
| Satellite | Dates | Repeat Period | Baseline | Comments |
| ERS-1/2 tandem | 951204/951205 | 1 day | 83m | See Fig. 6 |
| RADARSAT | 961204/961228 | 24 days | 149m | See Fig. 7 |
| JERS-1 | 950301/960331 960331/970318 950301/970318 960514/970501 960331/960514 960514/960810 960810/960923 970202/970318 970318/970501 |
1 year 1 year 2 years 1 year 44 days 88 days 44 days 44 days 44 days |
-3170m -2196m -5360m -2451m -909m -72m 117m 490m 1169m |
Baseline too large Baseline too large Baseline too large Baseline too large Coherence low Coherence low Coherence good; See Fig. 8 Coherence low Coherence low |
The RADARSAT and ERS interferograms illustrate the susceptibility of C-band radar to loss of coherence over long time intervals between passes. The phase signature is lost over the glaciers in the RADARSAT interferogram (24-days interval), but is preserved in the ERS tandem mode interferogram (1-day interval). In the ERS case, the phase signature over the glacier contains both topography and differential glacier flow. The best JERS-1 interferogram contains a good phase signature, even after 44-days, for a pair of fall acquisitions.
Preliminary Results and Problems
Representive ERS tandem modes, RADARSAT and JERS-1 coherence maps are shown in Figs. 6, 7, and 8, respectively. The ERS-1/2 coherence map shows a high degree of coherence across the whole region. Only in the high relief terrain in the lower part of the image is there a decrease in coherence.
In all three data sets the coherence is variable across the scene, and is well correlated with terrain type. The relationship between coherence and terrain type can be largely explained by the rate of surface activity within each terrain unit (see Table I). As can be seen in the coherence maps, there is lower coherence for the areas covered by the (relatively rapidly moving) glaciers. The small dark spot in front of the terminus of the glacier on the left is an area of open water or slush formed from the runoff from a subglacial sprint.
The dark area indicated by the arrow in Fig. 6 is a retrogressive thaw flow. Ground ice can melt very rapidly in the summer and the resultant saturated mudflows can continue to move well into the winter. However, the amount of surface change expected from ground ice melt before a retrogressive thaw flow is initiated would be much less. Thus, a 1-day repeat period is of minimal use in detecting pre-landslide surface changes. In the RADARSAT and JERS-1 coherence maps there is a lower overall coherence relative to the ERS image. This is due to the longer repeat period between the image pairs. However, we see similar coherence patterns as in the ERS coherence map. The glacial valley shows the greatest coherence while the glaciers show the least. Consequently, local areas where coherence is lost can still be detected in the valley (e.g. the wet area in front of the glacier of the left). Note that ground ice is most frequently found in glacial valleys.
The JERS-1 data had low coherence values with only the valley floors and some of the upland terrain showing appreciable coherence. Differentiating between local areas having rapid surface change would be difficult with this data set.
Final Results and Conclusions
It is apparent that scene coherence will be a limiting factor in this work if using C-band radar, especially since more than one month between passes is required to observe the effects of interest. It is expected that degradation in scene coherence could be an indicator of ground ice wasting (due to collapse of the surface soil, for example). Less catastrophic slumping could have a differential phase signature that could be used to estimate the line-of-sight displacement (or more generally the surface displacement vector). Unfortunately, we have been unable to conclusively observe these events based on the JERS-1 data that were available to us.
This preliminary investigation into the suitability of repeat-pass satellite interferometric SAR for detecting ground ice melt reveals a number of considerations in application of this technique to geomorphological analysis. Specifically:
Unfortunately, within this project we have only been able to demonstrate some of the pros and cons of using this technique; further tests are still required to quantify the capabilities of interferometric SAR for detecting ground ice melt.
References
Gray, A. L., Mattar, K. E. & van der Kooij, M. W. A., 1995. Cross-track and long track airborne interferometric SAR at CCRS. In: Proceedings, 17th Canadian Symposium on Remote Sensing, Vol. 1, pp. 232-237. Canadian Remote Sensing Society, Saskatoon, Canada, 232-237.
Klassen, R. A., 1993. Quaternary geology and glacial history of Bylot Island, Northwest Territories, Geological Survey of Canada Memoir 429, 93 pp.
Moorman, B. J., 1998. The Development and Preservation of Tabular Massive Ground Ice in Permafrost Regions, Ph.D. thesis, Carleton University, Ottawa, 308 pp.
Moorman, L. A., Geile, W., & Mercer, B., 1998. New Frontiers: Environmental applications of high accuracy DEMs. In: Proceedings, 27th International Symposium on Remote Sensing of Environment, Tromsø, Norway.
Orwig, L. P., Aronoff, A. D., Ibsen, P. M., Maney, H. D., O'Brien, J. D. & Holt, H.D. Jr., 1995. Wide-area terrain surveying with interferometric SAR. Remote Sensing of the Environment, 53, 97-108.
Vachon, P. W., Geudtner, D., Gray, A. L. & Touzi, R., 1995. ERS-1 synthetic aperture radar repeat-pass interferometry studies: Implications for RADARSAT. Canadian Journal of Remote Sensing, 21, 441-454.
Vachon, P. W., Geudtner, D., Mattar, K., Gray, A. L., Brugman, M. & Cumming, I. G., 1996. Differential SAR interferometry measurements of Athabasca and Saskatchewan Glacier flow rate. Canadian Journal of Remote Sensing, 22, 287-296.
Acknowledgements
We thank B. Armour (Atlantis Scientific) for helpful discussion. The RADARSAT data were acquired through CSA ADRO project #500 and are copyright CSA. The JERS-1 data were acquired through the NASDA JERS-1 Research Invitation and are copyright NASDA. The ERS data are copyright ESA. C. Livingstone (CCRS) expedited the acquisition of the CV580 data. We also thank F. Michel, L. Moorman, D. Kliza, and M. Elver for assistance in the field. Field logistical support was supplied by the Polar Continental Shelf Project. Thanks also to the Hamlet of Pond Inlet for supporting this ongoing field project.