Showing papers by "C.J. van Westen published in 2011"

Segment Optimization and Data-Driven Thresholding for Knowledge-Based Landslide Detection by Object-Based Image Analysis

Abstract: To detect landslides by object-based image analysis using criteria based on shape, color, texture, and, in particular, contextual information and process knowledge, candidate segments must be delineated properly. This has proved challenging in the past, since segments are mainly created using spectral and size criteria that are not consistent for landslides. This paper presents an approach to select objectively parameters for a region growing segmentation technique to outline landslides as individual segments and also addresses the scale dependence of landslides and false positives occurring in a natural landscape. Multiple scale parameters were determined using a plateau objective function derived from the spatial autocorrelation and intrasegment variance analysis, allowing for differently sized features to be identified. While a high-resolution Resourcesat-1 Linear Imaging and Self Scanning Sensor IV (5.8 m) multispectral image was used to create segments for landslide recognition, terrain curvature derived from a digital terrain model based on Cartosat-1 (2.5 m) data was used to create segments for subsequent landslide classification. Here, optimal segments were used in a knowledge-based classification approach with the thresholds of diagnostic parameters derived from If-means cluster analysis, to detect landslides of five different types, with an overall recognition accuracy of 76.9%. The approach, when tested in a geomorphologically dissimilar area, recognized landslides with an overall accuracy of 77.7%, without modification to the methodology. The multiscale classification-based segment optimization procedure was also able to reduce the error of commission significantly in comparison to a single-optimal-scale approach.

The application of numerical debris flow modelling for the generation of physical vulnerability curves

Abstract: . For a quantitative assessment of debris flow risk, it is essential to consider not only the hazardous process itself but also to perform an analysis of its consequences. This should include the estimation of the expected monetary losses as the product of the hazard with a given magnitude and the vulnerability of the elements exposed. A quantifiable integrated approach of both hazard and vulnerability is becoming a required practice in risk reduction management. This study aims at developing physical vulnerability curves for debris flows through the use of a dynamic run-out model. Dynamic run-out models for debris flows are able to calculate physical outputs (extension, depths, velocities, impact pressures) and to determine the zones where the elements at risk could suffer an impact. These results can then be applied to consequence analyses and risk calculations. On 13 July 2008, after more than two days of intense rainfall, several debris and mud flows were released in the central part of the Valtellina Valley (Lombardy Region, Northern Italy). One of the largest debris flows events occurred in a village called Selvetta. The debris flow event was reconstructed after extensive field work and interviews with local inhabitants and civil protection teams. The Selvetta event was modelled with the FLO-2D program, an Eulerian formulation with a finite differences numerical scheme that requires the specification of an input hydrograph. The internal stresses are isotropic and the basal shear stresses are calculated using a quadratic model. The behaviour and run-out of the flow was reconstructed. The significance of calculated values of the flow depth, velocity, and pressure were investigated in terms of the resulting damage to the affected buildings. The physical damage was quantified for each affected structure within the context of physical vulnerability, which was calculated as the ratio between the monetary loss and the reconstruction value. Three different empirical vulnerability curves were obtained, which are functions of debris flow depth, impact pressure, and kinematic viscosity, respectively. A quantitative approach to estimate the vulnerability of an exposed element to a debris flow which can be independent of the temporal occurrence of the hazard event is presented.

Quantitative estimation of landslide risk from rapid debris slides on natural slopes in the Nilgiri hills, India

Abstract: . A quantitative procedure for estimating landslide risk to life and property is presented and applied in a mountainous area in the Nilgiri hills of southern India. Risk is estimated for elements at risk located in both initiation zones and run-out paths of potential landslides. Loss of life is expressed as individual risk and as societal risk using F-N curves, whereas the direct loss of properties is expressed in monetary terms. An inventory of 1084 landslides was prepared from historical records available for the period between 1987 and 2009. A substantially complete inventory was obtained for landslides on cut slopes (1042 landslides), while for natural slopes information on only 42 landslides was available. Most landslides were shallow translational debris slides and debris flowslides triggered by rainfall. On natural slopes most landslides occurred as first-time failures. For landslide hazard assessment the following information was derived: (1) landslides on natural slopes grouped into three landslide magnitude classes, based on landslide volumes, (2) the number of future landslides on natural slopes, obtained by establishing a relationship between the number of landslides on natural slopes and cut slopes for different return periods using a Gumbel distribution model, (3) landslide susceptible zones, obtained using a logistic regression model, and (4) distribution of landslides in the susceptible zones, obtained from the model fitting performance (success rate curve). The run-out distance of landslides was assessed empirically using landslide volumes, and the vulnerability of elements at risk was subjectively assessed based on limited historic incidents. Direct specific risk was estimated individually for tea/coffee and horticulture plantations, transport infrastructures, buildings, and people both in initiation and run-out areas. Risks were calculated by considering the minimum, average, and maximum landslide volumes in each magnitude class and the corresponding minimum, average, and maximum run-out distances and vulnerability values, thus obtaining a range of risk values per return period. The results indicate that the total annual minimum, average, and maximum losses are about US$ 44 000, US$ 136 000 and US$ 268 000, respectively. The maximum risk to population varies from 2.1 × 10−1 for one or more lives lost to 6.0 × 10−2 yr−1 for 100 or more lives lost. The obtained results will provide a basis for planning risk reduction strategies in the Nilgiri area.

Spatial distribution of landslide dams triggered by the 2008 Wenchuan Earthquake.

Abstract: Landslide dams are a common type of river disturbance in tectonically active mountain belts with narrow and steep valleys. Here we present an unprecedented inventory of 828 landslide dams triggered by the 2008 Wenchuan earthquake, China. Of the 828 landslide dams, 501 completely dammed the rivers, while the others only caused partial damming. The spatial distribution of landslide dams was similar to that of the total landslide distribution, with landslide dams being most abundant in the steep watersheds of the hanging wall of the Yingxiu-Beichuan Thrust Fault, and in the northeastern part of the strike-slip fault near Qingchuan. We analyzed the relation between landslide dam distribution and a series of seismic, topographic, geological, and hydrological factors.

Mapping of elements at risk for landslides in the tropics using airborne laser scanning

Abstract: SUMMARY Mapping elements at risk for landslides in the tropics pose as a challenging task. Aerialphotograph, satellite imagery, and synthetic aperture radar images are less effective to accurately provide physical presence of objects in a relatively short time. In this paper, we utilized an airborne laser scanning (ALS) for extracting elements at risk for landslides, which we emphasized on the buildings and roads extraction in a populated tropical region (Cameron Highlands, Malaysia). We presented the building filter derived from the hierarchical robust interpolation method for building extraction. Meanwhile, the road extraction was performed based on the ALS-derived topographic openness, analyzed in a stereoscopic model. Building and road attributes in relation to landslides were subsequently generated such as perimeter and area of building footprint; number and height of the buildings; road location; length; road gradient, and road-cuts. We quantitatively evaluated the building detection method and measured the vertical accuracy of ALS-derived road. The evaluation showed the building detection rate of 88.6%, the correctness of 90% and the overall quality of 80.7%. The vertical accuracy of the ALS-derived road was about 0.68 m and spatially improved compared to the existing road map. This study illustrates the effectiveness of ALS data for mapping elements at risks in the tropics, which are essential for landslide vulnerability and risk assessment.