Landslide susceptibility mapping using multi-criteria evaluation techniques in Chittagong Metropolitan Area, Bangladesh

Landslides are a common hazard in the highly urbanized hilly areas in Chittagong Metropolitan Area (CMA), Bangladesh. The main cause of the landslides is torrential rain in short period of time. This area experiences several landslides each year, resulting in casualties, property damage, and economic loss. Therefore, the primary objective of this research is to produce the Landslide Susceptibility Maps for CMA so that appropriate landslide disaster risk reduction strategies can be developed. In this research, three different Geographic Information System-based Multi-Criteria Decision Analysis methods—the Artificial Hierarchy Process (AHP), Weighted Linear Combination (WLC), and Ordered Weighted Average (OWA)—were applied to scientifically assess the landslide susceptible areas in CMA. Nine different thematic layers or landslide causative factors were considered. Then, seven different landslide susceptible scenarios were generated based on the three weighted overlay techniques. Later, the performances of the methods were validated using the area under the relative operating characteristic curves. The accuracies of the landslide susceptibility maps produced by the AHP, WLC_1, WLC_2, WLC_3, OWA_1, OWA_2, and OWA_3 methods were found as 89.80, 83.90, 91.10, 88.50, 90.40, 95.10, and 87.10 %, respectively. The verification results showed satisfactory agreement between the susceptibility maps produced and the existing data on the 20 historical landslide locations

First insights on the potential of Sentinel-1 for landslides detection

This paper illustrates the potential of Sentinel-1 for landslide detection, Accepted 23 March 2016 mapping and characterization with the aim of updating inventory maps and monitoring landslide activity. The study area is located in Molise, one of the smallest regions of Italy, where landslide processes are frequent. The results achieved by integrating Differential Synthetic Aperture Radar Interferometry (DInSAR) deformation maps and time series, and Geographical Information System (GIS) multilayer analysis (optical, geological, geomorphological, etc.) are shown. The adopted methodology is described followed by an analysis of future perspectives. Sixty-two landslides have been detected, thus allowing the updating of pre-existing landslide inventory maps. The results of our ongoing research show that Sentinel-1 might represent a significant improvement in terms of exploitation of SAR data for landslide mapping and monitoring due to both the shorter revisit time (up to 6 days in the close future) and the wavelength used, which determine an higher coherence compared to other SAR sensors

Automated Satellite-Based Landslide Identification Product for Nepal

Landslide event inventories are a vital resource for landslide susceptibility and forecasting applications. However, landslide inventories can vary in accuracy, availability, and timeliness as a result of varying detection methods, reporting, and data availability. This study presents an approach to use publicly available satellite data and open source software to automate a landslide detection process called the Sudden Landslide Identification Product (SLIP). SLIP utilizes optical data from the Landsat 8 OLI sensor, elevation data from the Shuttle Radar Topography Mission (SRTM), and precipitation data from the Global Precipitation Measurement (GPM) mission to create a reproducible and spatially customizable landslide identification product. The SLIP software applies change detection algorithms to identify areas of new bare-earth exposures that may be landslide events. The study also presents a precipitation monitoring tool that runs alongside SLIP called the Detecting Real-time Increased Precipitation (DRIP) model that helps identify the timing of potential landslide events detected by SLIP. Using SLIP and DRIP together, landslide detection is improved by reducing problems related to accuracy, availability, and timeliness that are prevalent in the state-of-the-art of landslide detection. A case study and validation exercise was performed in Nepal for images acquired between 2014 and 2015. Preliminary validation results suggest 56% model accuracy, with errors of commission often resulting from newly cleared agricultural areas. These results suggest that SLIP is an important first attempt in an automated framework that can be used for medium resolution regional landslide detection, although it requires refinement before being fully realized as an operational tool

Towards the optimal Pixel size of dem for automatic mapping of landslide areas

Determining appropriate spatial resolution of digital elevation model (DEM) is a key step for effective landslide analysis based on remote sensing data. Several studies demonstrated that choosing the finest DEM resolution is not always the best solution. Various DEM resolutions can be applicable for diverse landslide applications. Thus, this study aims to assess the influence of special resolution on automatic landslide mapping. Pixel-based approach using parametric and non-parametric classification methods, namely feed forward neural network (FFNN) and maximum likelihood classification (ML), were applied in this study. Additionally, this allowed to determine the impact of used classification method for selection of DEM resolution. Landslide affected areas were mapped based on four DEMs generated at 1m, 2m, 5m and 10m spatial resolution from airborne laser scanning (ALS) data. The performance of the landslide mapping was then evaluated by applying landslide inventory map and computation of confusion matrix. The results of this study suggests that the finest scale of DEM is not always the best fit, however working at 1m DEM resolution on micro-topography scale, can show different results. The best performance was found at 5m DEM-resolution for FFNN and 1m DEM resolution for results. The best performance was found to be using 5m DEM-resolution for FFNN and 1m DEM resolution for ML classification

A Landslide Climate Indicator from Machine Learning

In order to create a Landslide Hazard Index, we accessed rain, snow, and a dozen other variables from the National Climate Assessment Land Data Assimilation System. These predictors were converted to probabilities of landslide occurrence with XGBoost, a major machine-learning tool. The model was fitted with thousands of historical landslides from the Pacific Northwest Landslide Inventory (PNLI)

Recorded displacements in a landslide slope due to regional and teleseismic earthquakes

Regional and teleseismic earthquakes can induce displacements along joints in a landslideinvolved rocky slope in Central Italy. The rarity of these effects is due to specific physical properties of the seismic signals associated with: (i) the energy content, (ii) the distribution of relative energy and peak of ground acceleration related to the ground motion components and (iii) the spectral amplitude distribution in the frequency domain; these properties allow the triggering earthquakes to be distinguished from the others. The observed effects are relevant when compared to the direction of the landslide movement and the dimensions of the involved rock mass volume. The landslide movement is less constrained in the direction parallel to the dip of the slope and the landslide dimensions are associated with characteristic periods that control the landslide deformational response in relation to the spectral content of the ground motion. The earthquake-induced displacements are significant because they have the same order of magnitude as the average annual cumulative displacement based on a decade of strain measurements within the slope

An integrated approach for evaluating the effectiveness of landslide risk reduction in unplanned communities in the Caribbean

Despite the recognition of the need for mitigation approaches to landslide risk in developing countries, the delivery of ‘on-the-ground’ measures is rarely undertaken. With respect to other ‘natural’ hazards it is widely reported that mitigation can pay. However, the lack of such an evidence-base in relation to landslides in developing countries hinders advocacy amongst decision makers for expenditure on ex-ante measures. This research addresses these limitations directly by developing and applying an integrated risk assessment and cost-benefit analysis of physical landslide mitigation measures implemented in an unplanned community in the Eastern Caribbean. In order to quantify the level of landslide risk reduction achieved, landslide hazard and vulnerability were modelled (before and after the intervention) and project costs, direct and indirect benefits were monetised. It is shown that the probability of landslide occurrence has been substantially reduced by implementing surface-water drainage measures, and that the benefits of the project outweigh the costs by a ratio of 2.7 to 1. This paper adds to the evidence base that ‘mitigation pays’ with respect to landslide risk in the most vulnerable communities – thus strengthening the argument for ex-ante measures. This integrated project evaluation methodology should be suitable for adoption as part of the community-based landslide mitigation project cycle, and it is hoped that this resource, and the results of this study, will stimulate further such programmes.Landslide modelling, Risk assessment, Cost Benefit Analysis, Developing countries, Community

Landslide motion assessment including rate effects and thermal interactions: revisiting the Canelles landslide

The re-activation of a large (40 Mm3) landslide on the valley slopes of a reservoir motivated a research initiative to estimate the risk of a fast-sliding mass moving into the reservoir. A previous simplified analysis had suggested that a joint consideration of strain rate effects on friction and thermal pressurization phenomena in the sliding surface could provide a rational approach to answer the question raised. The paper describes first the capability of strain rate effects on friction to reproduce long-term creeping records of two real cases. The joint and coupled phenomena of creeping motion and thermal pressurization in shearing bands was incorporated into a material point method computational technique for hydromechanical analysis of porous materials. A representative cross section of the Canelles landslide was then analysed, profiting from previous finite element investigations of the landslide. It was found that a rapid rate of landslide acceleration could be a possibility under extreme external actions. However, it was also found that a moderate strain rate effect on the basal residual friction angle could create conditions that avoid the triggering of a fast motion.Peer ReviewedPostprint (author's final draft

Spatiotemporal evolution, mineralogical composition, and transport mechanisms of long-runout landslides in Valles Marineris, Mars

Long-runout landslides with transport distances of >50 km are ubiquitous in Valles Marineris (VM), yet the transport mechanisms remain poorly understood. Four decades of studies reveal significant variation in landslide morphology and emplacement age, but how these variations are related to landslide transport mechanisms is not clear. In this study, we address this question by conducting systematic geological mapping and compositional analysis of VM long-runout landslides using high-resolution Mars Reconnaissance Orbiter imagery and spectral data. Our work shows that: (1) a two-zone morphological division (i.e., an inner zone characterized by rotated blocks and an outer zone expressed by a thin sheet with a nearly flat surface) characterizes all major VM landslides; (2) landslide mobility is broadly dependent on landslide mass; and (3) the maximum width of the outer zone and its transport distance are inversely related to the basal friction that was estimated from the surface slope angle of the outer zone. Our comprehensive Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) compositional analysis indicates that hydrated silicates are common in landslide outer zones and nearby trough-floor deposits. Furthermore, outer zones containing hydrated minerals are sometimes associated with longer runout and increased lateral spreading compared to those without detectable hydrated minerals. Finally, with one exception we find that hydrated minerals are absent in the inner zones of the investigated VM landslides. These results as whole suggest that hydrated minerals may have contributed to the magnitude of lateral spreading and long-distance forward transport of major VM landslides