Technical note Temporal remote sensing data and GIS application in landslide hazard zonation of part of Western ghat, India

Nagarajan, R.; Mukherjee, Anupam; Roy, Arijit; Khire, M. V.

doi:10.1080/014311698215865

Cited by 123 publications

(44 citation statements)

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“…In the last twenty years, Geographical Information Systems (GIS) and Remote Sensing have become integral tools for the evaluation of natural hazard phenomena (Nagarajan et al, 1998;Liu et al, 2004). Moreover, GIS is an excellent and useful tool for the spatial analysis of a multi-dimensional phenomenon such as landslides, and for landslide susceptibility mapping van Westen et al, 1999;Lan et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

GIS-based landslide susceptibility mapping models applied to natural and urban planning in Trikala, Central Greece

Bathrellos¹,

Kalivas²,

Skilodimou³

2008

Estud. geol.

104

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Mapas de susceptibilidad de deslizamientos basados en GIS aplicados a la planificación natural y urbanística en Trikala, Grecia CentralGLandslide susceptibility mapping is a practical tool in natural and urban planning; it can be applied for determining land use zones, in construction design and planning of a variety of projects.In this study, two different GIS based landslide susceptibility maps were generated in the mountainous part of the Trikala Prefecture in Thessaly, Central Greece. This was accomplished by using different methods for correlating factors, which have an effect on landslide occurrences. The instability factors taken into account were: lithology, tectonic features, slope gradients, road network, drainage network, land use and rainfall. A frequency distribution of the half number of the landslide events of the study area in each class of the instability factors was performed in order to rate the classes. Two models have been used to combine the instability factors and assess the overall landslide susceptibility, namely: the Weight Factor Model (WeF), which is a statistical method, and the Multiple Factor Model (MuF) that is a logical method. The produced maps were classified into four zones: Low, Moderate, High and Very High susceptible zones and validated using the other half number of the landslide events of the area. Evaluation of the results is optimized through a Landslide Models Indicator (La.M.I.).Key words: Landslide susceptibility models, Maps, GIS, spatial planning, Central Greece. RESUMENLos mapas de susceptibilidad de deslizamientos representan una práctica herramienta en la planificación urbana y de espacios naturales. Así, puede aplicarse a la determinación de los usos de terrenos, en el diseño de construcción civil y para la planificación de gran variedad de actividades.En este estudio se generaron dos tipos diferentes de mapas de susceptibilidad basados en GIS para la parte montañosa de la prefectura de Trikala en Tesalia (Grecia Central). Estos se llevaron a cabo usando dos métodos de correlación de los factores que pueden tener un efecto en la generación de deslizamientos. Los factores de desestabilización tenidos en cuenta fueron: litología, aspectos tectónicos, pendiente, red de carreteras, red de drenaje, uso de la tierra y pluviometría. La distribución de frecuencias de la media de eventos de deslizamiento en cada clase de factores de desestabilización, fue utilizada para clasificar cada una de dichas clases. Para combinar los factores de desestabilización y estimar la susceptibilidad a la generación de deslizamientos, se usaron dos tipos de modelos: el Weight Factor Model (WeF), basado en estimaciones estadísticas, y el Multiple Factor Model (MuF) basado en operadores lógicos. Los mapas producidos se dividieron en cuatro zonas en función de su grado de susceptibilidad: Bajo, Moderado, Alto y Muy Alto. Su validez se ponderó a partir de los valores medios de deslizamientos detectados en cada zona. Se propone que la evaluación de cada modelo se puede optimizar mediante la a...

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Section: Introductionmentioning

confidence: 99%

GIS-based landslide susceptibility mapping models applied to natural and urban planning in Trikala, Central Greece

Bathrellos¹,

Kalivas²,

Skilodimou³

2008

Estud. geol.

104

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“…Cheng et al (2004) discussed locating landslides induced by earthquakes with multitemporal satellite images, which was similar to the work of Hervas et al (2003), who explored the Tessina landslide of Italy with optical remotely sensed imagery. Spatial analysis provided by geographical information systems (GIS) can synthetically assess the factors of landslide, so the techniques of GIS and remote sensing can be integrated to explore potential landslides in steep lands (Nagarajan et al 1998, PerottoBaldiviezo et al 2004, Roessner et al 2005. Temesgen et al (2001) used GIS and remote sensing to evaluate the relationships of landslides with various controlling parameters in Ethiopia, which were used to develop the risk susceptibility index.…”

Section: Introductionmentioning

confidence: 99%

Estimating Wenchuan Earthquake induced landslides based on remote sensing

Zhang

Lin

Peng

et al. 2010

International Journal of Remote Sensing

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“…Overviews of various landslide susceptibility zonation techniques can be found in Carrara et al (1991), , Guzzetti et al (1999), and Zorn and Komac (2004;2007). Many techniques use GIS and remote sensing to determine landslide-prone areas (e.g., Nagarajan et al 1998;van Westen and Lulie Getahun 2003). With the help of GIS, it is possible to integrate different spatial data layers to determine landside-prone areas (e.g., van Westen 1994;Carrara etal.…”

Section: Introductionmentioning

confidence: 99%

Landslide susceptibility zonation: A case study of the Municipality of Banja Luka (Bosnia and Herzegovina)

Tošić¹,

Dragićević²,

Zorn³

et al. 2014

AGS

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Along with flash floods, landslides are one of the most widespread and damaging natural hazards in Bosnia and Herzegovina. This paper determines areas susceptible to landslides in the Municipality of Banja Luka (Republika Srpska, northwest Bosnia and Herzegovina). Based on a terrain survey in a 55.4 km2 area, 216 landslides were identified with a total area of 2.9 km2 or 5.2% of the municipality. According to landslide susceptibility modeling, low susceptibility is present from one-quarter to one-half of the territory and very high susceptibility is present from several percentages up to one-third of the territory, depending on the model used. The results may support government mitigation programs and help in developing a landslide hazard and risk assessment model for the area.

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Technical note Temporal remote sensing data and GIS application in landslide hazard zonation of part of Western ghat, India

Cited by 123 publications

References 0 publications

GIS-based landslide susceptibility mapping models applied to natural and urban planning in Trikala, Central Greece

GIS-based landslide susceptibility mapping models applied to natural and urban planning in Trikala, Central Greece

Estimating Wenchuan Earthquake induced landslides based on remote sensing

Landslide susceptibility zonation: A case study of the Municipality of Banja Luka (Bosnia and Herzegovina)

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