Utilization of fine resolution satellite data for landslide susceptibility modelling: A case study of kashmir earthquake induced landslides

Muhammad Zeeshan Ali, Hone Jay Chu, Saleem Ullah, Muhammad Shafique, Asad Ali

Research output: Contribution to journalConference article

Abstract

The 2005 Kashmir earthquake has triggered thousands of landslides which devastated most of the livelihood and other infrastructure in the area. Landslide inventory and subsequently landslide susceptibility mapping is one of the main prerequisite for taking mitigation measure against landslide effects. This study has focused on developing most updated and realistic landslide inventory and Susceptibility mapping. The high resolution data of Worldveiw-2 having spatial resolution of 0.4 m is used for landslide inventory. Support Vector Machine (SVM) classifier was used for landslide inventory developing. Total 51460 number of landslides were classified using semi-automatic technique with covering area of 265 Km2, smallest landslide mapped is covering area of 2.01 m2 and the maximum covered area of single landslide is 3.01 Km2. Nine influential causative factors are used for landslide susceptibility mapping. Those causative factors include slope, aspect, profile curvature, elevation, distance from fault lines, distance from streams and geology. Logistic regression model was used for the Landslides susceptibility modelling. From model the highest coefficient was assigned to geology which shows that the geology has higher influence in the area. For landslide susceptibility mapping the 70 % of the data was used and 30% is used for the validation of the model. The prediction accuracy of the model in this study is 92 % using validation data. This landslide susceptibility map can be used for land use planning and also for the mitigation measure during any disaster.

Original languageEnglish
Pages (from-to)25-30
Number of pages6
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume42
Issue number3/W8
DOIs
Publication statusPublished - 2019 Aug 20
Event2019 GeoInformation for Disaster Management, Gi4DM 2019 - Prague, Czech Republic
Duration: 2019 Sep 32019 Sep 6

Fingerprint

Landslides
satellite data
landslide
Earthquakes
natural disaster
utilization
Satellites
earthquake
modeling
Geology
livelihood
disaster
land use
geology
logistics
infrastructure
regression
planning
Kashmir earthquake 2005
land use planning

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Geography, Planning and Development

Cite this

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title = "Utilization of fine resolution satellite data for landslide susceptibility modelling: A case study of kashmir earthquake induced landslides",
abstract = "The 2005 Kashmir earthquake has triggered thousands of landslides which devastated most of the livelihood and other infrastructure in the area. Landslide inventory and subsequently landslide susceptibility mapping is one of the main prerequisite for taking mitigation measure against landslide effects. This study has focused on developing most updated and realistic landslide inventory and Susceptibility mapping. The high resolution data of Worldveiw-2 having spatial resolution of 0.4 m is used for landslide inventory. Support Vector Machine (SVM) classifier was used for landslide inventory developing. Total 51460 number of landslides were classified using semi-automatic technique with covering area of 265 Km2, smallest landslide mapped is covering area of 2.01 m2 and the maximum covered area of single landslide is 3.01 Km2. Nine influential causative factors are used for landslide susceptibility mapping. Those causative factors include slope, aspect, profile curvature, elevation, distance from fault lines, distance from streams and geology. Logistic regression model was used for the Landslides susceptibility modelling. From model the highest coefficient was assigned to geology which shows that the geology has higher influence in the area. For landslide susceptibility mapping the 70 {\%} of the data was used and 30{\%} is used for the validation of the model. The prediction accuracy of the model in this study is 92 {\%} using validation data. This landslide susceptibility map can be used for land use planning and also for the mitigation measure during any disaster.",
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Utilization of fine resolution satellite data for landslide susceptibility modelling : A case study of kashmir earthquake induced landslides. / Ali, Muhammad Zeeshan; Chu, Hone Jay; Ullah, Saleem; Shafique, Muhammad; Ali, Asad.

In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, Vol. 42, No. 3/W8, 20.08.2019, p. 25-30.

Research output: Contribution to journalConference article

TY - JOUR

T1 - Utilization of fine resolution satellite data for landslide susceptibility modelling

T2 - A case study of kashmir earthquake induced landslides

AU - Ali, Muhammad Zeeshan

AU - Chu, Hone Jay

AU - Ullah, Saleem

AU - Shafique, Muhammad

AU - Ali, Asad

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Y1 - 2019/8/20

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JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

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