Dadhwal, V.K.

Das, Iswar Das

Kerle, N.

Stein, A.

Das, I.

Dadhwal, V.

University of Twente Research Information

[P2.37] Probabilistic landslide hazard assessment using segmentation based homogenous susceptible units I. Das*1,2, A. Stein1, N. Kerle1, V. Dadhwal2 1University of Twente, Netherlands, 2Indian Institute of Remote Sensing, India This study concerns the development and application of statistical methods to assess landslide hazards at medium scales. Landslide hazards are evaluated on the basis of homogenous susceptible units (HSUs) that are derived from a landslide susceptibility map using an automated segmentation procedure.  It uses a combination of landslide occurrences and geo-environmental factors. We determine the spatial probability, the temporal probability and the size probability as three distinct components of hazard assessment. The spatial probability at location i, Pi, is determined using Bayesian logistic regression. The temporal probability, Pt, of naturally occurring landslides in time is determined using a Poisson model.  The probability of the landslide size PA, expressed as the area greater or equal than a given size A is based on the Inverse gamma distribution. For an HSU at location i, the hazard (H) of a landslide at time t, of a size at least equal to A is Ati PPPH ××=                                                                                  (1) The method is applied to a landslide prone road corridor in the Himalayans. We derive the HSUs automatically from a grid-cell based susceptibility map with spatial probability values for each cell using a region growing algorithm and an optimal size factor.  Using multiresolution segmentation in eCognition software we control the segmentation by scale (size), colour and shape with shape being further classified into compactness and smoothness. Optimal size parameters are determined using Moran’s I autocorrelation index and a variance analysis. On the basis of this information, the susceptibility map has been divided into 315 HSUs. Temporal probability was determined for each individual HSU on the basis of the frequency of occurrences of landslides for a period of 28 years (1982 - 2009). For each HSU we obtained landslide recurrence values, i.e. the expected time between successive failures, based on past events. Under the assumption that the rate of future landslides will remain unchanged, and by adopting a Poisson probability model, we computed the exceedance probability of having one or more landslides in each mapping unit for 1, 5 and 10 year recurrence periods. We estimated PA values 0.78 and 0.21 for A equal to 800 m2 and 5,000 m2, respectively using an Inverse gamma model.  H obtained by multiplying the values for spatial, temporal and size probabilities for each HSU shows that the hazard probability of larger landslides with A ≥  5,000 m2 is low for one year as well as 5 and 10 years recurrence period, where as it is moderate and high for A ≥  800 m2. The present study shows how to carry out statistical modeling for landslide hazard mapping using homogenous susceptible units. Keywords: Landslides, Hazard, Segmentation, Himalayas  

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Probabilistic landslide hazard assessment using segmentation based homogenous susceptible units

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Probabilistic landslide hazard assessment using segmentation based homogenous susceptible units : abstract.

Probabilistic landslide hazard assessment using segmentation based homogenous susceptible units : abstract.

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