Validation of Landslide Susceptibility Maps; Examples and Applications from a Case Study in Northern Spain

Remondo, Juan; González, Ainhoa; Terán, J.R. Díaz de; Cendrero, Antonio; Fabbri, Andrea G.; Chung, Chae-Heon

doi:10.1023/b:nhaz.0000007201.80743.fc

Cited by 235 publications

(155 citation statements)

References 11 publications

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“…The area under the curve (AUROC) varies between 0.5 and 1.0, with higher values indicating a better fit of the model. The model is validated by comparing it to a landslide dataset that is not used for calibrating the model [30,31]. The subdivision of the landslide data into the training and validation parts is generally performed randomly or using non-overlapping temporal or spatial subsets of the landslide inventory [30].…”

Section: Validation Of Susceptibility Assessmentmentioning

confidence: 99%

Evaluation of Remote-Sensing-Based Landslide Inventories for Hazard Assessment in Southern Kyrgyzstan

et al. 2017

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Large areas in southern Kyrgyzstan are subjected to high and ongoing landslide activity; however, an objective and systematic assessment of landslide susceptibility at a regional level has not yet been conducted. In this paper, we investigate the contribution that remote sensing can provide to facilitate a quantitative landslide hazard assessment at a regional scale under the condition of data scarcity. We performed a landslide susceptibility and hazard assessment based on a multi-temporal landslide inventory that was derived from a 30-year time series of satellite remote sensing data using an automated identification approach. To evaluate the effect of the resulting inventory on the landslide susceptibility assessment, we calculated an alternative susceptibility model using a historical inventory that was derived by an expert through combining visual interpretation of remote sensing data with already existing knowledge on landslide activity in this region. For both susceptibility models, the same predisposing factors were used: geology, stream power index, absolute height, aspect and slope. A comparison of the two models revealed that using the multi-temporal landslide inventory covering the 30-year period results in model coefficients and susceptibility values that more strongly reflect the properties of the most recent landslide activity. Overall, both susceptibility maps present the highest susceptibility values for similar regions and are characterized by acceptable to high predictive performances. We conclude that the results of the automated landslide detection provide a suitable landslide inventory for a reliable large-area landslide susceptibility assessment. We also used the temporal information of the automatically detected multi-temporal landslide inventory to assess the temporal component of landslide hazard in the form of exceedance probability. The results show the great potential of satellite remote sensing for deriving detailed and systematic spatio-temporal information on landslide occurrences, which can significantly improve landslide susceptibility and hazard assessment at a regional scale, particularly in data-scarce regions such as Kyrgyzstan.

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Section: Validation Of Susceptibility Assessmentmentioning

confidence: 99%

Evaluation of Remote-Sensing-Based Landslide Inventories for Hazard Assessment in Southern Kyrgyzstan

et al. 2017

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“…Although a coarse DEM resolution could be of poor quality in some cases, the gain in the quality of the results would not be worth the efforts (Remondo, et al, 2003b). Given the dimensions of the shallow landslide and debris flows in the study area, a 10 m×10 m DEM could be optimal for analysing the landslide source and runout susceptibility (Tarolli and Tarboton, 2006).…”

Section: Discussionmentioning

confidence: 99%

“…However, in order to obtain two independent failure samples the study area was divided into a training zone and a test zone (Fig. 3), following the approach of Baeza and Corominas (2001), Remondo et al (2003b and Guinau et al (2005).…”

Section: Terrain Failure Susceptibility Analysismentioning

confidence: 99%

“…It has been demonstrated that reliable susceptibility maps can be produced by using conditional parameters exclusively derived from a DEM (Remondo et al, 2003b;Fabbri et al, 2003;Santacana et al, 2003;Pallàs et al, 2004;Coe et al, 2004).…”

Section: Selection Extraction and Discretisation Of Instability Factmentioning

confidence: 99%

“…A relative failure density (RFD) was used to quantify the accuracy of the method (Eq. 2) (Duque et al, 1990;Baeza and Corominas, 2001;Santacana et al, 2003;Fernández et al, 2003;Remondo et al, 2003b;Fabbri, 2003, 2005;Guinau et al, 2005).…”

Section: Terrain Failure Susceptibility Discretization and Validationmentioning

confidence: 99%

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GIS-based debris flow source and runout susceptibility assessment from DEM data – a case study in NW Nicaragua

Guinau

Vilajosana

Vilaplana

2007

Nat. Hazards Earth Syst. Sci.

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Abstract. In October 1998, Hurricane Mitch triggered numerous landslides (mainly debris flows) in Honduras and Nicaragua, resulting in a high death toll and in considerable damage to property. The potential application of relatively simple and affordable spatial prediction models for landslide hazard mapping in developing countries was studied. Our attention was focused on a region in NW Nicaragua, one of the most severely hit places during the Mitch event.A landslide map was obtained at 1:10 000 scale in a Geographic Information System (GIS) environment from the interpretation of aerial photographs and detailed field work. In this map the terrain failure zones were distinguished from the areas within the reach of the mobilized materials. A Digital Elevation Model (DEM) with 20 m×20 m of pixel size was also employed in the study area.A comparative analysis of the terrain failures caused by Hurricane Mitch and a selection of 4 terrain factors extracted from the DEM which, contributed to the terrain instability, was carried out. Land propensity to failure was determined with the aid of a bivariate analysis and GIS tools in a terrain failure susceptibility map. In order to estimate the areas that could be affected by the path or deposition of the mobilized materials, we considered the fact that under intense rainfall events debris flows tend to travel long distances following the maximum slope and merging with the drainage network. Using the TauDEM extension for ArcGIS software we generated automatically flow lines following the maximum slope in the DEM starting from the areas prone to failure in the terrain failure susceptibility map. The areas crossed by the flow lines from each terrain failure susceptibility class correspond to the runout susceptibility classes represented in a runout susceptibility map.Correspondence to: M. Guinau (mguinau@ub.edu)The study of terrain failure and runout susceptibility enabled us to obtain a spatial prediction for landslides, which could contribute to landslide risk mitigation.

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Regional coseismic landslide hazard assessment without historical landslide inventories: A new approach

Kritikos

Robinson

Davies

2015

J. Geophys. Res. Earth Surf.

115

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Currently, regional coseismic landslide hazard analyses require comprehensive historical landslide inventories as well as detailed geotechnical data. Consequently, such analyses have not been possible where these data are not available. A new approach is proposed herein to assess coseismic landslide hazard at regional scale for specific earthquake scenarios in areas without historical landslide inventories. The proposed model employs fuzzy logic and geographic information systems to establish relationships between causative factors and coseismic slope failures in regions with well-documented and substantially complete coseismic landslide inventories. These relationships are then utilized to estimate the relative probability of landslide occurrence in regions with neither historical landslide inventories nor detailed geotechnical data. Statistical analyses of inventories from the 1994 Northridge and 2008 Wenchuan earthquakes reveal that shaking intensity, topography, and distance from active faults and streams are the main controls on the spatial distribution of coseismic landslides. Average fuzzy memberships for each factor are developed and aggregated to model the relative coseismic landslide hazard for both earthquakes. The predictive capabilities of the models are assessed and show good-to-excellent model performance for both events. These memberships are then applied to the 1999 Chi-Chi earthquake, using only a digital elevation model, active fault map, and isoseismal data, replicating prediction of a future event in a region lacking historic inventories and/or geotechnical data. This similarly results in excellent model performance, demonstrating the model's predictive potential and confirming it can be meaningfully applied in regions where previous methods could not. For such regions, this method may enable a greater ability to analyze coseismic landslide hazard from specific earthquake scenarios, allowing for mitigation measures and emergency response plans to be better informed of earthquake-related hazards.

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Validation of Landslide Susceptibility Maps; Examples and Applications from a Case Study in Northern Spain

Cited by 235 publications

References 11 publications

Evaluation of Remote-Sensing-Based Landslide Inventories for Hazard Assessment in Southern Kyrgyzstan

Evaluation of Remote-Sensing-Based Landslide Inventories for Hazard Assessment in Southern Kyrgyzstan

GIS-based debris flow source and runout susceptibility assessment from DEM data – a case study in NW Nicaragua

Regional coseismic landslide hazard assessment without historical landslide inventories: A new approach

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