Analyzing and predicting of land slide prone areas using remote sensing and GIS techniques.

dc.contributor.authorPushpakumara, TDC
dc.contributor.authorKodagoda, KGHNRP
dc.contributor.authorRanasinghe, DMT
dc.contributor.authorAbeysinghe, ASJ
dc.contributor.authorPuswewala, UGA
dc.contributor.authorSenanayake, I
dc.date.accessioned2015-06-24T10:14:26Z
dc.date.available2015-06-24T10:14:26Z
dc.date.issued2015-06-24
dc.description.abstractLandslide is the major natural disaster in hill country of Sri Lanka. There are ample examples for losses from landslides to human lives, agriculture, economic properties and transportation. Therefore, identification of landslide prone areas plays an important role in avoiding or minimizing the hazards. Among the factors affecting landslides, land use is the foremost controllable and highly floating factor over time. Obtaining land use data using manual techniques is very tricky in slope areas. Therefore the importance of using remote sensing techniques is emerged. This study leads to identification and prediction of landslide prone areas with the variance of land use using geospatial techniques. This research is based on the data collected from Elapatha, Ratnapura district, Sri Lanka. Field data and remotely sensed data such as satellite images, survey data and GPS data are collected and subsequently analyzed using remote sensing and GIS software. In this work, a methodology has been developed to generate a landslide susceptibility potential map of the selected area considering the factors which are causing landslides in Sri Lanka by using remote sensing and GIS techniques.en_US
dc.identifier.conferenceInternational Conference on Building Resilienceen_US
dc.identifier.departmentDepartment of Earth Resources & Engineeringen_US
dc.identifier.emailpushapakumara@civil.mrt.ac.lken_US
dc.identifier.facultyEngineeringen_US
dc.identifier.pgnosp. 8en_US
dc.identifier.placeAhungallaen_US
dc.identifier.urihttp://dl.lib.mrt.ac.lk/handle/123/10952
dc.identifier.year2013en_US
dc.language.isoenen_US
dc.source.urihttp://www.buildresilience.org/2013/proceedings/files/papers/429.pdfen_US
dc.subjectLandslide susceptibility potential mapen_US
dc.titleAnalyzing and predicting of land slide prone areas using remote sensing and GIS techniques.en_US
dc.typeConference-Full-texten_US

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