Annual Landslide Research Articles

Object-oriented analysis of multi-temporal panchromatic images for creation of historical landslide inventories

Object-oriented analysis (OOA) has been demonstrated to produce more accurate results than pixel-based image processing. Studies carried out by previous researchers have shown how landslide inventories can be prepared from multispectral satellite images using OOA. However, panchromatic images are frequently the only data available after a landslide event. Furthermore, preparation of historical inventories relies on the analysis of satellite images and aerial photographs acquired over past few decades that are also mostly only available in black and white. In such cases the methodology developed using multispectral data cannot be used directly due to limited spectral information, in particular in near-infrared bands. In this paper we present a new methodology that addresses some of these issues. Using high resolution panchromatic images from Cartosat-1 (2.5 m) and IRS-1D (5.8 m), and a 10 m gridded DTM extracted from Cartosat-1, we developed a new approach which uses change detection techniques and a global contextual criteria in an object-based environment to detect and classify landslides into five different types. Continuous time series images from 1998 to 2006 were used to prepare annual landslide inventories in a highly rugged Himalayan terrain. The maximum and minimum detection percentages achieved for all landslides are 96.7% and 71.5%, respectively, with corresponding quality percentages of 88.1% and 55.3%, respectively. However, the lack of spectral information proved to be a hurdle resulting in a high branching factor that indicates that further work is required to eliminate false positives. Nevertheless, the method was able to create much needed historical landslide inventories, which are critical for landslide hazard and risk assessment studies.

Replay of the 1987 Val Pola Landslide, Italian Alps

The 1987 Val Pola Landslide was the most destructive and costly natural disaster that occurred in Italy during the last two decades. The disaster response and monitoring system, along with related construction activities for this single landslide event amounts to nearly half of the annual landslide prevention budget in Italy. It is also one of the few cases of landslide study for which a large amount of quantitative data have been gathered. The Val Pola landslide thus provides an invaluable benchmark for geotechnical modelling and model calibrations due to its fully three-dimensional features and significant multi-directional impact in space. In this paper, the entire runout process including the reactivation of the landslide has been numerically replayed using a (quasi) three-dimensional finite element method in the Lagrangian reference frame, based on Voellmy rheology and high-precision basal topography available in a GIS database. Comparison between the results of the present analysis and the available field observations is remarkable, demonstrating the capability of the present methodology in tackling large-scale landslides of complex nature. The technique is thus of value in land use zoning and the study of geomorphologic features. It also provides a powerful and handy tool in studying possible scenarios of future landform processes.

Seasonal movement of the Slumgullion landslide determined from Global Positioning System surveys and field instrumentation, July 1998–March 2002

Measurements of landslide movement made by global positioning system surveys and extensometers over a 3.5-year period show that the Slumgullion landslide in the San Juan Mountains of southwest Colorado moved throughout the monitoring period, but that daily velocities varied on a seasonal basis. Landslide velocities peaked in the early spring and summer in response to snowmelt and summer thunderstorms, respectively. Velocities were slowest in mid-winter when air and soil temperatures were coldest and precipitation was generally low and/or in the form of snow with a low water content. We hypothesize that the seasonal variability in velocities is due to ground-water levels and corresponding pore pressures that decrease when surface water is unavailable or cannot infiltrate frozen landslide material, and increase when surface water from melting snow or rainfall infiltrates unfrozen landslide material. We also suggest that patches of bouldery debris and fractures (created by continuous movement of the landslide) are conduits through which surface water can infiltrate, regardless of the frozen or unfrozen state of the landslide matrix material. Therefore, the availability of surface water is more important than landslide temperature in controlling the rate of landslide movement. This hypothesis is supported by field instrumentation data that show (1) landslide velocities coinciding with precipitation amounts regardless of the depth of freezing of landslide material, (2) spring and annual landslide velocities that were greatest when the depth of freezing was also the greatest, and (3) a rapid (several weeks or less) velocity and pore pressure response to rainfall. The persistent, but seasonally variable movement of the landslide, fits the bathtub model for landslide movement described by Baum and Reid [Baum, R.L., Reid, M.E., 2000. Ground water isolation by low-permeability clays in landslide shear zones. In: Bromhead, E.N., Dixon, N., Ibsen, M.-L. (Eds.), Landslides in Research, Theory and Practice. Proc. 8th Int. Symp. on Landslides, Cardiff, Wales, vol. 1, 139–144]. In their model, the landslide is isolated both mechanically and hydrologically from adjacent materials by low permeability clays. These clays cause the landslide to retain water. Our data support this model by suggesting that pore pressures at the basal landslide surface are always adequate to maintain landslide movement and that any infiltration of water at the surface of the landslide is adequate to rapidly increase landslide velocity.