Identifying permafrost slope disturbance using multi-temporal optical satellite images and change detection techniques

Active layer detachments (ALDs) are a common form of permafrost slope disturbance that pose a serious risk for infrastructure and can impact environmental and ecological stability in Arctic regions. Effective recognition and detection of slope disturbances are critical for future hazard analysis. Historically, this has primarily been done through manual image interpretation and field mapping, both of which are cost-intensive. Semi-automatic detection techniques have been successfully applied in more temperate regions to identify slope failures, however, little work has been done to map permafrost disturbances. In this paper we present a methodology to detect and map ALDs using multi-temporal IKONOS satellite imagery in combination with vegetation index differencing and object-based image analysis, to semiautomatically identify landscape change associated with ALDs. A normalized difference vegetation index (NDVI) was computed for each of the two dates (2004 and 2010) and then subtracted generating a NDVI difference surface. Using areas where vegetation was removed as a proxy for the presence of ALDs, a multi-resolution segmentation algorithm was used to threshold the NDVI difference map into objects to demarcate regions of similarity (i.e., potential ALDs). To discriminate between disturbed and undisturbed zones a NDVI threshold was applied removing false positives. The thresholded image was then verified with a disturbance inventory collected from the field. These methods were successfully applied to the study area achieving 43% detection accuracy when identifying all ALDs. Morphometric characteristics were used to separate ALDs into two forms, elongate and compact, with accuracies assessed for each. Elongate ALDs, with a detection accuracy of 67%, are typically more destructive, moving substantially more material downslope over longer distances and posing a greater risk for infrastructure. By contrast, compact ALDs are associated with minimal downslope sliding distances (< 1 m to several meters) and result in little to no extension in the scar zone and thus limited downslope material movement. The method used in this study detected only 7% of compact disturbances indicating that morphology and size are important variables when detecting ALDs. These results collectively show promise for the semi-automated detection of slope disturbances (i.e., elongate ALDs) in permafrost settings and a cost-effective method to delineate areas for more detailed hazard assessment methods.