Integrated Remote Sensing and GIS Analysis for Landslide Susceptibility Assessment along the Trenggalek–Ponorogo Road, East Java Province, Indonesia

Adniwan Shubhi Banuzaki, Adelia Kusuma Ayu


Landslide, the second most common hazard in Indonesia, after an earthquake, is causing enormous losses of public infrastructures with subsequent economic disruptions. Roads are the most frequent public property which is affected by landslides. Due to the geomorphological condition of Indonesia, the construction of roads often intersects the mountainous topography. The Trenggalek–Ponorogo Road is one of the roads passing through mountainous terrains that are very susceptible affected by landslides. The road has an important role as the main transportation connector of some regencies in East Java Province. Landslide mitigation strategies along the Trenggalek–Ponorogo Road are needed to prevent enormous losses. This research was aimed to conduct a remote sensing-based assessment of landslide susceptibility areas along the Trenggalek–Ponorogo Road. The landslide susceptibility areas were assessed by considering landslide triggering parameters; those were topographic slope, distance to geological structure, distance to stream, lithology, and land use/land cover. The landslide triggering parameters were presented in spatial data and processed using Geographic Information System (GIS) technology. The Analytical Hierarchy Process (AHP) method was applied to integrate the landslide triggering parameters which have the degree of effect to determine Landslide Potential Index (LPI). The resulting LPI delineated the area into four susceptibility zones: very high, high, moderate, and low, which were presented as landslide susceptibility map. The susceptibility map was then validated by landslide occurrences inventory in the study area. The very high susceptibility zones, which are strongly predicted affecting the Trenggalek–Ponorogo Road, are located in Nglinggis and Grogol Village.


Trenggalek; Ponorogo; remote sensing; GIS; landslide

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Highland, L.M.; Bobrowsky, P. The landslide handbook––A guide to understanding landslides. In U.S. Geological Survey Circular; 2008.

Karnawati, D.; Fathani, T.F.; Andayani, B.; Burton, P.W.; Sudarno, I. Strategic program for landslide disaster risk reduction: a lesson learned from Central Java, Indonesia. WIT Trans. Built Environ. 2009, 110, 115–126.

National Agency for Disaster Management No Title Available online:

Yamagishi, H.; Bhandary, N.P. GIS Landslide; Tokyo, 2017;

Hartono, U.; Baharuddin; Brata, K. Geological Map of the Madiun Quadrangle, Jawa,; Bandung, 1992;

Samodra, H.; Suharsono, S.; Gafoer; Suwarti, T. Geological Map of the Tulungagung Quadrangle, Jawa; 1992;

Geological Agency of Indonesia Response for Landslide Disaster in Tugu District, Trenggalek Regency, East Java.; 2016;

Geological Agency of Indonesia Report of Lanslide Survey in Sawoo, Pulung, Ngebel, and Slahung, Ponorogo Regency, East Java; 2017;

Geological Agency of Indonesia Response for Landslide Disaster in Sawoo and Sokoo District, Trenggalek Regency, East Java; 2017;

Indonesia Geospatial Information Peta rupa bumi Available online: download/perwilayah.

Indonesia Geospatial Information Agency DEMNAS 1507-44, 1507-53, 1508-12, 1508-21.

Dou, J.; Bui, D.T.; Yunus, A.P.; Jia, K.; Song, X.; Revhaug, I.; Xia, H.; Zhu, Z. Optimization of Causative Factors for Landslide Susceptibility Evaluation Using Remote Sensing and GIS Data in Parts of Niigata, Japan. PLoS One 2015, 10.

Clerici, A.; Perego, S.; Tellini, C.; Vescovi, P. A Procedure for Landslide Susceptibility Zonation by the Conditional Analysis Method. Geomorphology 2002, 48, 349–364.

Saha, A.K.; Gupta, R.P.; Arora, M.K. GIS-Based Landslide Hazard Zonation in the Bhagirathi (Ganga) Valley, Himalayas. Int. J. Remote Sens. 2002, 23, 357–369.

Cevik, E.; Topal, T. GIS-based Landslide Susceptibility Mapping for a Problematic Segment of the Natural Gas Pipeline, Hendek (Turkey). Environ. Geol. 2003, 44, 949–662.

Ercanoglu, M.; Gokceoglu, C.; Van Asch, T.W.J. Landslide Susceptibility Zoning North of Yenice (NW Turkey) by Multivariate Statistical Techniques. Nat. Hazards 2004, 32, 1–23.

Lee, S.; Choi, J.; Min, K. Probabilistic Landslide Hazard Mapping Using GIS and Remote Sensing Data at Boun, Korea. Korea, Int. J. Remote Sens. 2004, 25, 2037–2052.

Lee, S. Application of Logistic Regression Model and Its Validation for Landslide Susceptibility Mapping Using GIS and Remote Sensing Data. Int. J. Remote Sens. 2005, 26, 1477–1491.

Yalcin, A. GIS-Based Lanslide Susceptibility Mapping Using Analytical Hierarchy Process and Bivariate Statistics in Ardesen (Turkey) Comparisons of Results And Confirmation. Catena 2008, 72, 1–12.

Dai, F.C.; Lee, C.F.; Li, J.; Xu, Z.W. Assessment of Landslide Susceptibility on the Natural Terrain of Lantau Island, Hong Kong. Environ. Geol. 2001, 43, 381–391.

Sarkar, S.; Kanungo, D.P. An Integrated Approach for Landslide Susceptibility Mapping Using Remote Sensing and GIS. Photogramm. Eng. Remote Sens. 2004, 70, 616–625.

Hamza, T.; Raghuvanshi, T.K. GIS Based Landslide Hazard Evaluation and Zonation – a Case from Jeldu District, Central Ethiopia. J. King Saud Univ. - Sci. 2017, 29, 151–65.

Kayastha, P.; Dhital, M.R.; De Smedt, F. Application of The Analytical Hierarchy Process (AHP) for Landslide Susceptibility Mapping: a Case Study From the Tinau Watershed, West Nepal. Comput. Geosci. 2012, 52, 398–308.

Saaty, T.L. The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation; New York, 1980;


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