Applied Small Format Aerial Photograph (SFAP) for Detail Landslide Susceptibility Mapping

International Journal of Geoinformatics and Geological Science
© 2020 by SSRG - IJGGS Journal
Volume 7 Issue 3
Year of Publication : 2020
Authors : Heni Masruroh, Junun Sartohadi, M. Anggri Setiawan
pdf
How to Cite?

Heni Masruroh, Junun Sartohadi, M. Anggri Setiawan, "Applied Small Format Aerial Photograph (SFAP) for Detail Landslide Susceptibility Mapping," SSRG International Journal of Geoinformatics and Geological Science, vol. 7,  no. 3, pp. 46-52, 2020. Crossref, https://doi.org/10.14445/23939206/IJGGS-V7I3P106

Abstract:

Landslide is a disaster which affected by a human and geographic physical condition. Commonly, landslide susceptibility mapping is created by semi-detailed data and direct landslide inventory mapping. It becomes less detailed information and needs more time for data inventory. Small format aerial photograph details remote sensing data for landslide inventory and producing landslide detail mapping. The paper proposes a small format aerial photograph for detailed landslide susceptibility mapping based on landslide inventory. The method for landslide susceptibility mapping is based on landslide detail data produced by interpretation SFAP. We use 2D manual interpretation SFAP to landslide inventory data. This research was conducted in the Bompon micro catchment, Magelang Regency, Central Java. We applied a detailed landslide section and type of landslide to determine the susceptibility landslide area, i.e, crown of landslide, zona depletion, zona accumulation, main body of and toe landslide. Each section of the landslide occurred in different surface morphology. The result shows the landslide susceptibility areas depend on the detailed landslide section. Crown, zona depletion, and the main body of landslide are the unstable zone. They have occurred in the surface morphology such as peak-interfluve, upper slope-shoulder, middle slope-transportation zone, and lower slope-translational zone. Simultaneously, zona accumulation and toe landslide are the stable zone and occurred in the surface morphology such as foot slope-depositional zone and colluvial plain. The accuracy value is 86%; it was done by extensive field check.

Keywords:

Small Format Aerial Photograph, Landslide, Susceptibility map

References:

[1] Aber, J., Marzolf, I., dan Ries, J. Small Aerial Photography Principles, Technique, and Geoscience Applications. Oxford: Elsevier (2010).
[2] Bera, Somnath., Guru Balamurugan, Ghatterjee, Ranit., Shaw, Rajib. Geographic Variation of Resilience to Landslide Hazard: A Household-Based Comparative Studies in Kalimpong Hilly Region, India. International Journal of Disaster Risk Reduction, (2020) 1-15.
[3] Carrara, A., Cardinali, M., Guzzetti, F., dan Reichenbach, P. GIS Technology in Mapping Landslide Hazard. In: Carrara, A. and Guzzetti, F. (eds.), Geographical Information Systems in Assessing Natural Hazards, (1995) 135–175.
[4] Congalton, R. A Review of Assessing The Accuracy of Classification of Remotely Sensed Data. Remote Sensing, (1991) 35-46.
[5] Fiorucci, C., Rossi., Mondini., Santurri., Ardizzone.,dan Guzzeti.. Seasonal Landslide Mapping and Estimation of Landslide Mobilization Rates Using Aerial and Satellite Images. Geomorphology, (2011) 59-70.
[6] Hadmoko, D. S., Lavigne, F., Sartohadi, J., Hadi, P., dan Winaryo.. Landslide Hazard and Risk Assessment and Their Application in Risk Management and Landuse Planning in Eastern flank of Menoreh Mountains, Yogyakarta Province, Indonesia. Natural Hazard, 54 (2010) 623-642.
[7] Janssen. Accuracy Assessment of Satellite-Derived Land Cover Data: A Review. Photogrammetric Engineering & Remote Sensing, (1994) 419-426.
[8] Lillesand., dan Kiefer. Remote Sensing and Image Interpretation. Third Edition. John Wiley and Sons, New York (1994).
[9] Li, Y., Chen, G., Wang, B., Zheng, Lu., Zhang, Y., Tang, C. A New Approach of CombiningAerial Photography with Satellite Imagery for Landslide Detection. Natural Hazard. (2013) 649-669.
[10] Marfai, M. A., King, Lorenz., Singh, P.L., Mardiatno, D., Sartohadi, J., Hadmoko, D.S., and Dewi, A. Natural Hazards in Central Java Province, Indonesia: an overview. Environmental Geology. (2007) 335-351.
[11] Mantovani, Franco., Soeters, Robert., Van Westen. Remote sensing techniques for LandslideStudies and Hazard Zonation in Europe. Geomorphology. (1996) 213-225.
[12] Metternicht, Graciela., Hurni, Lorenz., Gogu, Radu. Remote Sensing of Landslide: An analysis of the potential contribution to geo-spatial system for hazard assessment in Mountainous Environment. Remote Sensing Environment, (2005). 285-303.
[13] Miyagi, Toyohiko., Prasad, Gyawali., Tanavud, Charchai., Potichan, Anirut, Landslide risk Evaluation and Mapping-Manual of Aerial Photo Interpretation for Landslide Topography and Risk Management. National Research Institute for Earth Science (2004).
[14] Mihai, Bogdan., Sandric, Ionut., Saveloscu, Ionut., Chitu, Zenaida, Detailed Mapping of Landslide Susceptibility for Urban Planning Purposes in Carpathian Subcarpathian Town of Romanis. Cartography. (2010) 418-428.
[15] Nichol, J. S., Shaker, Ahmed., dan Wong, S Application of high-resolution stereo satellite images to detailed landslide hazard assessment. Geomorphology, (2006) 1-8.
[16] Nuarsa. Penggunaan Analisis Citra Digital dan Sistem Informasi Geografi untuk Prediksi Besarnya Erosi di DAS Ayung Bagian Hilir Kabupaten Badung Propinsi Bali. Tesis: Kartografi dan Penginderaan Jauh Universitas Gadjah Mada (Tidak dipublikasikan) (1998).
[17] Olofsson, P., Foody, Giles., Herold, M., Stehman, Stheven.m Woodcock, Curtis., and Wulder, M. Good Practices for Estimating Area and Assessing Accuracy of Land Change. Remote Sensing of Environment, (2014) 42-57.
[18] Panizza, M. (1996). Environmental Geography. The Netherland: Elsevier Science.
[19] Pradhan, Biswajeet. Application of a neuro-fuzzy model to landslide-susceptibility mapping for Shallow Landslides iin a Tropical Hilly Area. Computers and Geosciences, (2011) 1264-1276.
[20] Rossiter, D. G. Soil Geographic Databases. Lecture Note International Institute for Aerospace Survey & Earth Sciences (ITC), (1999) 1-42.
[21] Sartohadi, J. The landslide Distribution in Loano Sub District Purworejo District, Central Java Province, Indonesia. Forum Geografi, 22(2) (2008) 129-144
[22] Samodra, G. Development of Risk Analysis Technique and Its Application to Geo Disaster Management in Indonesia. Ph.D. Dissertation: Kyusu University, Japan (2015).
[23] Sutanto. Metode Penelitian Penginderaan Jauh. Yogyakarta: Penerbit Ombak. (2013).
[24] Stehman, S., dan Czaplewski, R. Design and Analysis for Thematic Map Accuracy Assessment: Fundamental Principle. Remote Sensing Environment, (1998) 331-344.
[25] Strozzi, T., Ambrozzi, C., dan Raetzo, H. Interpretation of Aerial Photographs and Satellite SAR Interferometry for The
Inventory of Landslide. Remote Sensing, (2013) 2554-2570.
[26] Tofani., Segoni., agostini., Catani., Casagli,. Technical Note: Use of Remote Sensing for Landslide Studies in Europe. Natural Hazard System, (2013) 299-209.
[27] Van Westen., Mantovani, Fransco., dan Soeters, R. Remote Sensing Technique for Landslide Studies and Hazard Zonation in Europe. Geomorphology. (1996) 213-255.
[28] Vranken, Liesbet., Turnhout, Van., Eechaut, Den. Economic Valuation of Landslide Damage in Hilly Region: A Case Study from Flanders, Belgium. Science of the Total Environment, (2013) 323-336.
[29] Wahono, B. F. Application of Statistical and Heuristic Method for Landslide susceptibility assessment. Tesis: Geo-Information for Spatial Planning and Disaster Risk Management Graduate School of Universitas Gadjah Mada (Tidak Dipublikasikan) (2010).
[30] Westen, V. Remote Sensing for Natural Disaster Management. Photogrammetry and Remote Sensing, (2000) 1609-161.