A GIS method for landslide inventory and susceptibility mapping in the Río El Estado watershed, Pico de Orizaba volcano, México

Paulín, Gabriel Legorreta; Bursik, Marcus; Hubp, José Lugo; Mejía, Luis Mario Paredes; Quesada, Fernando Aceves

doi:10.1007/s11069-013-0911-8

Cited by 29 publications

(7 citation statements)

References 24 publications

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“…The spatial and temporal thematic information derived from remote sensing, thematic maps and ground-based information needs to be integrated (Pandey et al 2008). The use of GIS in the modelling of landslide hazards using many different parameters was attempted by several researchers (Sarkar and Kanungo 2004;Hong et al 2007;Kouli et al 2010;Avtar et al 2011;Othman et al 2012;Devkota et al 2013;Paulín et al 2014;Ahmed 2015;Cárdenas and Mera 2016;Hadmoko et al 2017;Stanley and Kirschbaum 2017;Mahdadi et al 2018). Moreover, GIS-based multi-criteria analysis provides powerful techniques for landslide hazard mapping and prediction of landslide hazards.…”

Section: Introductionmentioning

confidence: 99%

Landslide hazard zonation mapping using multi-criteria analysis with the help of GIS techniques: a case study from Eastern Himalayas, Namchi, South Sikkim

2019

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Landslides are one of the most damaging disastrous phenomena that frequently lead to serious problems in hilly areas. The Namchi region of South Sikkim district as a part of Eastern Himalayas is not an exception to it. In the present study, multi-criteria analysis technique is used for landslide hazard zonation mapping. Various thematic layers, namely slope, rainfall distribution map, lineament density, drainage density, slope aspect, geology, land use/land cover and soil map, were integrated in a GIS platform (ArcGIS 10.1) to delineate landslide hazard zone. Analytic hierarchy process was used to determine the weight values of different factors. Relative rating values are assigned for the subclasses of each thematic layer based on their corresponding impact on the landslide triggers, and within a thematic layer, each class was assigned an ordinal rating from 0 to 9. The landslide hazard zonation map of Namchi region was produced based on weighted overly techniques. The landslide hazard map of Namchi region is divided into five vulnerable zones, namely very low-, low-, moderate-, high-and very high-hazard zones. Resulted landslide hazard zonation map was further validated with field study and geospatial technology-based analysis. The findings demonstrate high-landslide-hazard zones are associated with areas of active erosive processes (steep slopes/cut slopes/lineaments). The results indicate the villages Bomtar, Jorethang, Kopchey, Donok, Namthang, Sumbuk, Longchok, Mamring, Turung, Mikkhola, etc. are highly prone to landslides. The final landslide hazard zonation map can be used for the landslide hazard prevention, proper planning of future infrastructure and geoenvironmental development in Namchi region.

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Section: Introductionmentioning

confidence: 99%

Landslide hazard zonation mapping using multi-criteria analysis with the help of GIS techniques: a case study from Eastern Himalayas, Namchi, South Sikkim

2019

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“…Although there is a more generic and rapid approach to the de nition and classi cation of landform units based on hillslope gradient and shape, rock type, and landslide density (WADNR Forest Practices Division, 2006;Legorreta-Paulín et al, 2014), the geomorphological method used here was preferable; its focus on geomorphological detail allowed speci c volcanic and sedimentary terrains of Pico de Orizaba volcano to be characterized. However, it may not be possible to compare these landform units with other volcanic areas in Mexico, as can be achieved with the generic approach.…”

Section: Discussionmentioning

confidence: 99%

“…The landform units map (step 2) was the result of combination and interpretation of thematic maps according to geomorphological criteria and eld evaluation (Demeck, 1972). The method for mapping landform units was adapted after Legorreta-Paulín et al (2014). To de ne landform units, we used more speci c criteria that included photointerpretation, eld geology, land use, hypsometry, slope, drainage density, and the vertical erosion (Fig.…”

Section: Methodsmentioning

confidence: 99%

“…A map of landslide susceptibility within the watershed was created by use of multiple logistic regression (MLR) and SINMAP (Legorreta-Paulín et al, 2013). Also, landform units have been de ned by following the Landslide Hazard Zonation Protocol (LHZP) of the WSDNR, Forest Practices Division 2006(Legorreta-Paulín et al, 2014. No work has hitherto modeled the landslide sediment production per landform unit.…”

Section: Introductionmentioning

confidence: 99%

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Modeling landslide susceptibility and landslide volume per geomorphologic landform unit

Paulín

Anaya

Contreras³

et al. 2021

Preprint

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The analysis of landslide susceptibility and landslide volumes in landforms can provide information for planning disaster management in an area. Landslide susceptibility per landform unit and the potential contribution of material delivered from each unit was calculated for a 105 km2 watershed on the south flank of Pico de Orizaba volcano, Mexico. The landslide susceptibility is calculated from the area and frequency of landslides. The volume is obtained from detailed geometric values of shallow landslides in order to establish an empirical relationship that takes the form of a power law from which the potential volume of all shallow landslides is calculated for the watershed. The study shows that most of the landslides are on volcanic landform units; however, the landslides in sedimentary units contribute more sediments per square kilometer. It also shows that landform units can be used to explain the predisposition and variability of landslide sediment production for a large and complex geological watershed.

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“…In the last decade, Geographic Information Systems (GIS) were used for creating spatial models of potential hazard zonation maps for civil engineering and protection purposes by Mason and Rosenbaum (2002), Mancini et al (2010), and Calvello et al (2013) [1][2][3]. Several authors have presented the important role of GIS in hazard assessment and mitigation; these include Carrara et al (1991), Barredo et al (2000), Fernandez et al (2003), Kolat et al (2006), Yilmaz and Yildirim (2006), Nandi and Shakoor (2009), Paulin et al (2014) [4][5][6][7][8][9][10], and others.…”

Section: Introductionmentioning

confidence: 99%

GIS-Based Rockfall Susceptibility Zoning in Greece

Saroglou

2019

Geosciences

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The assessment of rockfall risks on human activities and infrastructure is of great importance. Rock falls pose a significant risk to (a) transportation infrastructure, (b) inhabited areas, and (c) Cultural Heritage sites. The paper presents a method to assess rockfall susceptibility at national scale in Greece, using a simple rating approach and Geographic Information Systems (GIS) techniques. An extensive inventory of rockfalls for the entire country was compiled for the period between 1935 and 2019. The rockfall events that were recorded are those which have mainly occurred as distinct rockfall episodes in natural slopes and have impacted human activities, such as roads, inhabited areas, and archaeological sites. Through a detailed analysis of the recorded data, it was possible to define the factors which determine the occurrence of rockfalls. Based on this analysis, the susceptibility zoning against rockfalls at the national scale was prepared, using a simple rating approach and GIS techniques. The rockfall susceptibility zoning takes into account the following parameters: (a) the slope gradient, (b) the lithology, (c) the annual rainfall intensity, (d) the earthquake intensity, and (e) the active fault presence. Emphasis was given on the study of the earthquake effect as a triggering mechanism of rockfalls. Finally, the temporal and spatial frequency of the recorded events and the impact of rockfalls on infrastructure assets and human activities in Greece were evaluated.

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A GIS method for landslide inventory and susceptibility mapping in the Río El Estado watershed, Pico de Orizaba volcano, México

Cited by 29 publications

References 24 publications

Landslide hazard zonation mapping using multi-criteria analysis with the help of GIS techniques: a case study from Eastern Himalayas, Namchi, South Sikkim

Landslide hazard zonation mapping using multi-criteria analysis with the help of GIS techniques: a case study from Eastern Himalayas, Namchi, South Sikkim

Modeling landslide susceptibility and landslide volume per geomorphologic landform unit

GIS-Based Rockfall Susceptibility Zoning in Greece

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