Landslide susceptibility mapping using index of entropy and conditional probability models in GIS: Safarood Basin, Iran

Pourghasemi, Hamid Reza; Mohammady, Majid; Pradhan, Biswajeet

doi:10.1016/j.catena.2012.05.005

Cited by 447 publications

(210 citation statements)

References 78 publications

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“…2) as one of the major LCFs. There exists a close connection between elevation and landslide occurrence (Bai et al 2010;Chen et al 2013;Goetz et al 2015;Chalkias et al 2014;Jebur et al 2014;Mashari et al 2012;Pourghasemi et al 2012). All DEM-delivered LCFs are calculated based on the elevation which means that they can be represented by the elevation.…”

Section: Elevationmentioning

confidence: 99%

“…3) is the crucial landslide-conditioning factor because sliding of loose material is directly related to the slope (Bai et al 2010;Chen et al 2013;Goetz et al 2015;Chalkias et al 2014;Jebur et al 2014;Mashari et al 2012;Pourghasemi et al 2012;Akgun et al 2008;Constantin et al 2011;Thiery et al 2007;Sarkar and Kanungo 2004;Feizizadeh et al 2014Kayastha et al 2013Ozturk et al 2016). …”

Section: Slopementioning

confidence: 99%

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Impact of DEM-derived factors and analytical hierarchy process on landslide susceptibility mapping in the region of Rożnów Lake, Poland

Pawłuszek

Borkowski

2016

Nat Hazards

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Choosing appropriate landslide-controlling factors (LCFs) in landslide susceptibility mapping (LSM) is a challenging task and depends on the nature of terrain and expert knowledge and experience. Nowadays, it is very common to use digital elevation model (DEM) and DEM-derivatives, as a representation of the topographic conditions. The objective of this study is to explore topography in depth and simultaneously reduce redundant information within DEM-derivatives using principal component analysis. Moreover, this study investigates the impact of DEM-derived factors on LSM. Therefore, three various strategies were tested. The first strategy included a set of LCFs created from the four initial principal components, which were provided from DEM-derived factors. The second strategy included a set of parameters which contained additional lithological and environmental factors. The third strategy utilises the analytical hierarchy process (AHP) to assign weights to each LCF. The LSM was performed based on landslide susceptibility index. Obtained results show that 60% of existing landslides fell into high and very high susceptibility zones using first and second strategies. It proves that topographic factors play a significant role in LSM. Adding additional lithological and environmental factors to the set of LCFs did not improve the results significantly, unless the AHP was used in the third strategy. It improved results significantly; up to 70%. Results from second and third strategies highlight utility of AHP in LSM. Presented studies were performed on the area very prone to landslide occurrence in the region of Ro_ znów Lake, Poland.

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Section: Elevationmentioning

confidence: 99%

Section: Slopementioning

confidence: 99%

Impact of DEM-derived factors and analytical hierarchy process on landslide susceptibility mapping in the region of Rożnów Lake, Poland

Pawłuszek

Borkowski

2016

Nat Hazards

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“…The pa ram e ters were sub di vided into classes (e.g., a rock type or slope in cli na tion class). The method ap plied for the spa tial analy sis and de vis ing the land slide sus cep ti bil ity map for the study area was the en tropy in dex method (van Westen, 2004;Constantin et al, 2011;Bednarik et al, 2012;Pourghasemi et al, 2012). All lists, cal cu la tions and anal y ses in cluded in the study were per formed us ing ILWIS 3.7.2.…”

Section: Methodsmentioning

confidence: 99%

Landslide susceptibility mapping in the Beskid Niski Mts., Western Carpathians (Dukla commune, Poland)

Bronowski

Chybiorz

Jura

2016

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. Land slide sus cep ti bil ity map ping in the Beskid Niski Mts., West ern Carpathians (Dukla com mune, Po land). Geo log i cal Quar terly, 60 (3): 586-596, doi: 10.7306/gq.1275 Land slides are one of the most prom i nent pro cesses de grad ing the Beskidy Mts. slopes. Sus cep ti bil ity as sess ment is based on the de tailed map ping of the Dukla com mune (235 km 2 ) at the scale 1:10,000 in frames of the pro ject Land slide Coun teract ing Sys tem. The ter rain af fected by land slides is 19.59 km 2 , which is 8.34% of the re searched area. The larg est num ber of land slides can be found in the Beskid Dukielski Mts. area, where nearly 78% of all land slide ar eas are con cen trated. Anal y sis of land slide-caus ing fac tors was per formed us ing the in dex of en tropy method. The fol low ing five fac tors were con sid ered: lithol ogy, slope in cli na tion, slope as pect, dis tance to faults, and dis tance to drain age. The most im por tant role in the de vel opment of mass move ments in the study area is played by slope in cli na tion (0.0079) and li thol ogy of siliciclastic flysch (0.0066). The method ap plied also con trib uted to de vis ing a land slide sus cep ti bil ity map of con sid er able ac cu racy at 90.5%. The analy ses of the land slide fac tors have proven that un der stand ing of ge ol ogy and land forms is not only of cog ni tive sig nif i cance, but adds to prac ti cal ap pli ca tions in spa tial man age ment. The stud ies con firmed use ful ness of large-scale map ping of landslides and ap ply ing sta tis ti cal meth ods and GIS tech niques in the spa tial anal y sis of landform trans for ma tions. The ob tained land slide sus cep ti bil ity map can be a ba sis for as sess ing land slide risk. High and very high land slide sus cep ti bil ity classes cover nearly 50% of the study area.

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“…The natural break classification scheme was applied for the classification of the landslide susceptibility zones. Recently, the classification method mainly used the natural break classification scheme [72][73][74][75][76]. The landslide susceptibility maps were reclassified into four classes: low (0-0.3323), moderate (0.3323-0.4593), high (0.4593-0.5699), and very high (0.5699-0.8533).…”

Section: Landslides Susceptibility Mappingmentioning

confidence: 99%

Landslide Susceptibility Mapping in Vertical Distribution Law of Precipitation Area: Case of the Xulong Hydropower Station Reservoir, Southwestern China

Cao

Wang

Chen

et al. 2016

Water

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This study focused on landslide susceptibility analysis mapping of the Xulong hydropower station reservoir, which is located in the upstream of Jinsha River, a rapidly uplifting region of the Tibetan Plateau region. Nine factors were employed as landslide conditioning factors in landslide susceptibility mapping. These factors included the slope angle, slope aspect, curvature, geology, distance-to-fault, distance-to-river, vegetation, bedrock uplift and annual precipitation. The rapid bedrock uplift factor was represented by the slope angle. The eight factors were processed with the information content model. Since this area has a significant vertical distribution law of precipitation, the annual precipitation factor was analyzed separately. The analytic hierarchy process weighting method was used to calculate the weights of nine factors. Thus, this study proposed a component approach to combine the normalized eight-factor results with the normalized annual precipitation distribution results. Subsequently, the results were plotted in geographic information system (GIS) and a landslide susceptibility map was produced. The evaluation accuracy analysis method was used as a validation approach. The landslide susceptibility classes were divided into four classes, including low, moderate, high and very high. The results show that the four susceptibility class ratios are 12.9%, 35.06%, 34.11%and 17.92% of the study area, respectively. The red belt in the high elevation area represents the very high susceptibility zones, which followed the vertical distribution law of precipitation. The prediction accuracy was 85.74%, which meant that the susceptibility map was confirmed to be reliable and reasonable. This susceptibility map may contribute to averting the landslide risk in the future construction of the Xulong hydropower station.

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Landslide susceptibility mapping using index of entropy and conditional probability models in GIS: Safarood Basin, Iran

Cited by 447 publications

References 78 publications

Impact of DEM-derived factors and analytical hierarchy process on landslide susceptibility mapping in the region of Rożnów Lake, Poland

Impact of DEM-derived factors and analytical hierarchy process on landslide susceptibility mapping in the region of Rożnów Lake, Poland

Landslide susceptibility mapping in the Beskid Niski Mts., Western Carpathians (Dukla commune, Poland)

Landslide Susceptibility Mapping in Vertical Distribution Law of Precipitation Area: Case of the Xulong Hydropower Station Reservoir, Southwestern China

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