TSM—Tracing Surface Motion: A Generic Toolbox for Analyzing Ground-Based Image Time Series of Slope Deformation

Abstract

Passive sensors such as multi-spectral (e.g., Single Lens Reflex, SLR) cameras are increasingly being used for geohazards monitoring (landslides, cliffs affected by rock falls, ice glaciers, and volcano flanks) because of their low cost compared to expensive terrestrial laser scanner (TLS) or radar imaging (GB-InSAR) systems. Indeed, due to the large consumer market, sensor resolution and quality (e.g., gain, dynamic range, and geometry) are increasing rapidly. For gravitational processes, such as landslides, recent research has focused on the development and implementation of image correlation techniques to estimate the spatial shift between at least a pair of images by maximizing a cross-correlation function. A generic and fully automated pipeline is proposed for the processing of long image time series acquired for several site configurations. The system associates modules for 1) the selection of the image sequences, 2) the registration of the image stacks and the correction of the camera movements, and 3) the calculation of the terrain motion using change detection approaches. The system is based on the open-source photogrammetric library MicMac and tailored for the processing of monoscopic images. A sensitivity analysis is conducted to design and test the image processing for two use cases respectively the Chambon landslide (Isère, France) characterized by slow motion (< 10 cm.day−1), and the Pas de l’Ours landslide (Hautes-Alpes, France) characterized by moderate motion (> 50 cm.day−1). Four categories of parameters are tested: the image modality, the image matching parameters, the size of the stable area used in the co-registration stage, and the strategy used to combine the images in the time series. The application of the pipeline on the two use cases provides information about the kinematics and the spatial behavior of the landslides.

New Approach for Photogrammetric Rock Slope Premonitory Movements Monitoring

“…In winter, these images corresponded to the afternoon or the last image of the morning because there were a high number of foggy days due to the geographic location of the study area and its proximity to a river. The analysis carried out by [40] shows that the influence of the type of image (black/white, RGB, etc.) was negligible in this process, and the result was much more sensitive to the correlation window used.…”

Temporal Consolidation Strategy for Ground-Based Image Displacement Time Series: Application to Glacier Monitoring

“…As an example, satellite images can be used to monitor glaciers over a whole region of the world [2], or permafrost deformation in a specific area [3]. More closely, fixed digital cameras can also be used to monitor slope movements such as glaciers, rock glacier and landslides [4], [5], [6]. An advantage of systematic image acquisition approaches is to provide redundant displacement information: from a set of n images, up to n(n − 1) combinations can be formed to calculate forward and backward displacements.…”

“…To filter noisy displacements, a median filter has been used to calculate yearly glacier velocity on displacement calculated on images separated by one year [2]. A similar approach has been used on landslide images taken the same day [7], [6]. We can also note the use of a temporal median filter applied on depth map differences for the detection of change from stereo time-lapse images [8].…”