Sar integrated techniques for geohazard assessment

doi:10.1016/0273-1177(95)00076-Q

Advances in Space Research

Volume 15, Issue 11, 1995, Pages 67-78

https://doi.org/10.1016/0273-1177(95)00076-Q Get rights and content

Abstract

Integrated remote sensing techniques are used increasingly in geohazard assessment. As SAR (synthetic aperture radar) images become commonly available, it is essential that these data be evaluated in terms of the information they can provide for characterizing areas affected by geological hazards. This paper summarizes the utility of remote sensing in geohazard assessment, and presents two case studies in which SAR and TM (thematic mapper) were used to characterize areas affected by landslides and coastal hazards. Based on the results of these two case studies, a guideline is proposed for the utility of remote sensors for geohazard assessment.

In the first case study integrated SAR/TM techniques were used to identify and classify landslides in the lower Fraser Valley within the Canadian Rockies. The lower Fraser Valley is one of the most strategically important transportation corridors in Canada. Almost all the lifelines that link the resource rich prairie provinces with metropolitan Vancouver utilize this corridor. Landslides within this valley threaten to disrupt these major transport links. Image maps resulting from the integration of geometrically corrected SAR and TM data provided information on the geomorphology of slopes, land cover and the location and distribution of fracture zones. Such characterization enables the identification and classification of landslides and will complement current airphoto methods used for landslide inventories in high relief areas.

In the second case study, enhanced SAR and TM integrated techniques using IHS transform were used to locate areas of erosion and deposition and to update current coastal geomorphological and land cover maps. Coastal Guyana is below sea level, hence sea defence (dykes and sea dams) are used to protect coastal settlements, infrastructure and rich agricultural lands. Erosion of the sea dams has led to severe damage of agricultural lands due to flooding by seawater. The resultant image maps using SAR/TM integrated techniques assist in monitoring the constantly changing shoreline, enable the assessment of flood damage, facilitate in planning areas for coastal dyke repair and maintenance and provide new information for the revision of ongoing coastal geomorphological mapping.

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Citation Excerpt :
SAR systems illuminate the ground with an electromagnetic wave in the microwave spectral range, and record the amplitude and the phase of the backscattered signal. SAR amplitude derived products, including intensity and some derived backscatter coefficients, have been used to identify and map landslides with a photo-interpretative approach since 1995 (Singhroy, 1995; Vargas Cuervo, 1997; Chorowicz et al., 1998; Singhroy et al., 1998; Mondini et al., 2019), and only recently with quantitative methods (Mondini, 2017; Konishi and Suga, 2018a, 2018b; Ge et al., 2019; Uemoto et al., 2019). Singhroy, (1995) complemented traditional methods used for landslide inventories in the Lower Fraser Valley, Canada, through a description of the landslide features (i.e. slide scars, rupture line, debris lobe), in 6-m resolution C-HH-band, airborne SAR images in combination with Landsat Thematic Mapper (TM) optical images.
Landslides triggered by meteorological phenomena occur worldwide and cause extensive and severe damages to properties, and life loss. Detailed maps of event landslides can sensibly shorten emergency response time, possibly resulting in reduced death tolls. In most cases, however, optical post-event images are not always available right after the event, due to dense cloud cover. Since Synthetic Aperture Radar (SAR) sensors overcome the limitation of cloud cover, in this work we explore the use of C-band Sentinel-1 SAR amplitude images to map event landslides. A team of four expert photo-interpreters first defined interpretation criteria of SAR amplitude post-event images of the backscatter coefficient (β₀) and of the derived images of change. The same team mapped two large event landslides occurred in Villa Santa Lucia (Chile) and Tonzang (Myanmar). Maps were prepared on a total of 72 images for the Chile test case and 54 for the Myanmar test case. Images included VV (vertical transmit, vertical receive) and VH (vertical transmit, horizontal receive) polarisation, ascending and descending orbits, multilook processing, adaptive and moving window filters, post-event images and images of change. In the first case, interpreters were asked to map the event landslide on an optical post-event image before mapping on SAR images, whereas in Myanmar it was done in the end. Results were quantitatively compared to the maps prepared on post-event optical images, assumed as benchmark. Results revealed a good agreement between the SAR-derived maps and the benchmark. Locally, errors can be due to geometrical distortions, and speckling-like effects. Also polarisation plays an important role, as opposed to filtering. Despite the preliminary nature of this study, it proved that SAR amplitude derived products are suitable to prepare accurate maps of large event landslides, and that they should be further tested to prepare event inventories.
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Citation Excerpt :
Despite the inherent difficulties, we encourage the exploitation and testing of fully-polarimetric imagery for landslide failure detection and mapping (Table 2). Third, we note that studies that experimented with the combination or the “fusion” of SAR products with other imagery or products are rare (e.g., Singhroy, 1995; Singhroy et al., 1998; Mwaniki et al., 2017). The experiments were limited to the combined, visual interpretation of optical-based and SAR-based products.
Landslides are geomorphological processes that shape the landscapes of all continents, dismantling mountains and contributing sediments to the river networks. Caused by geophysical and meteorological triggers, including intense or prolonged rainfall, seismic shaking, volcanic activity, and rapid snow melting, landslides pose a serious threat to people, property, and the environment in many areas. Given their abundance and relevance, investigators have long experimented with techniques and tools for landslide detection and mapping using primarily aerial and satellite optical imagery interpreted visually, or processed by semi-automatic or automatic procedures or algorithms. Optical (passive) sensors have known limitations due to their inability to capture Earth surface images through the clouds and to work in the absence of daylight. The alternatives are active, “all-weather” and “day-and-night”, microwave radar sensors capable of seeing through the clouds and working in presence and absence of daylight. We review the literature on the use of Synthetic Aperture Radar (SAR) imagery to detect and map landslide failures – i.e., the single most significant movement episodes in the history of a landslide – and of landslide failure events – i.e., populations of landslides in areas ranging from a few to several thousand square kilometres caused by a single trigger. We examine 54 articles published in representative journals presenting 147 case studies in 32 nations, in all continents, except Antarctica. Analysis of the geographical location of 70 study areas shows that SAR imagery was used to detect and map landslides in most morphological, geological, seismic, meteorological, climate, and land cover settings. The time history of the case studies reveals the increasing interest of the investigators in the use of SAR imagery for landslide detection and mapping, with less than one article per year from 1995 to 2011, rising to about 5 articles per year between 2012 and 2020, and an average period of about 4.2 years between the launch of a satellite and the publication of an article using imagery taken by the satellite. To detect and map landslides, investigators use a common framework that exploits the phase and the amplitude of the electromagnetic return signal recorded in the SAR images, to measure terrain surface properties and their changes. To discriminate landslides from the surrounding stable terrain, a classification of the ground properties is executed by expert visual (heuristic) interpretation, or through numerical (statistical) modelling approaches. Despite undisputed progress over the last 26 years, challenges remain to be faced for the effective use of SAR imagery for landslide detection and mapping. In the article, we examine the theoretical, research, and operational frameworks for the exploitation of SAR images for landslide detection and mapping, and we provide a perspective for future applications considering the existing and the planned SAR satellite missions.
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While the kinematics do not change dramatically for changing the strength of sets F4 and F5, decreasing the strength of sets F1 and F2 significantly promotes toppling. Based on a numerical study, Sjöberg (2000) also showed that toppling is favored over sliding with decreasing strength of toppling discontinuities. Choosing a percentage of rock bridges below 8% for set F2 results in toppling also in the lower regions of the instability.
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Sar integrated techniques for geohazard assessment

Abstract

ISPRS Journal of Photogrammetry and Remote Sensing

Satellite Observations of Active Volcanoes. Prospects of the 1990's

Episodes

Remote Sensing for Geothermal Applications

Episodes

Engineering Geology and Remote Sensing in the USSR

Eposides

Application of Airborne C-SAR and SPOT Image Data to the Geological Setting of the Nahanni Earthquake Area

Canadian Journal of Remote Sensing

Lineaments from Airborne SAR Images and the 1988 Saguenay Earthquake, Quebec, Canada

Photogrammetric Engineering and Remote Sensing

Measurement of Sub-Resolution Terrain Displacement Using SPOT Panchromatic Imagery

Episodes

Remote Sensing Looks at an Intraplate Earthquake Surface Rupture

EOS Transaction AGU

GIS and Remote Sensing Analysis: Charlevoix Seismic Zone, Quebec, Canada

Remote Sensing and GIS Applied to Mountain Hazard Mapping

Episodes

Remote Sensing and Landslide Hazard Assessment

Photogrammetric Engineering and Remote Sensing

Global Emergency Observation and Warning (GEOWARN)

Airphoto Interpretation and the Canadian Landscape