Skip to main content

Advertisement

SpringerLink
Log in

Shallow landslide susceptibility mapping using high-resolution topography for areas devastated by super typhoon Haiyan

  • Technical Note
  • Published:
Landslides Aims and scope Submit manuscript

Abstract

Super typhoon Haiyan, considered as one of the most powerful storms recorded in 2013, devastated the central Philippines region on 8 November 2013 with damage amounting to more than USD 2 billion. Hardest hit is the province of Leyte which is located in central Philippines. Rehabilitation of the areas that were devastated requires detailed hazard maps as a basis for well-planned reconstruction. Along with severe wind, storm surge, and flood hazard maps, detailed landslide susceptibility maps for the cities and municipalities of Leyte (7246.7 km2) province are necessary. In order to rapidly assess and delineate areas susceptible to rainfall-induced shallow landslides, Stability INdex MAPping (SINMAP) software was used over a 5-m Interferometric Synthetic Aperture Radar (InSAR)-derived digital terrain model (DTM) grid. Topographic, soil strength, and hydrologic parameters were used for each pixel of a given DTM grid to compute for the corresponding factor of safety. The landslide maps generated using SINMAP are highly consistent with the landslide inventory derived from high-resolution satellite imagery from 2002 to 2014 with a detection percentage of 97.5 % and missing factor of 0.025. These demonstrate that SINMAP performs well despite the lack of an extensive geotechnical and hydrological database in the study area. The detailed landslide susceptibility classification is useful to identify safe and unsafe areas for reconstruction and rehabilitation efforts. These maps complement the debris flow and structurally controlled landslide hazard maps that are also being prepared for rebuilding Haiyan’s devastated areas.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

References

  • AGS (2007) Guideline for landslide susceptibility, hazard, and risk zoning for land use planning. Aust Geomech 42(1):13–36

    Google Scholar 

  • Antronico L, Gullà G (2000) Slopes affected by soil slips: validation of an evolutive model. 8th International Symposium on Landslides, Cardiff, Wales. Thomas Telford, London, pp 77–84

    Google Scholar 

  • Baum RL, Savage WZ, Godt JW (2008) TRIGRS—a FORTRAN program for transient rainfall infiltration and grid-based regional slope stability analysis, version 2.0 US Geological Survey Open File Report 2008-1159. Reston, Virginia

  • Beven KJ, Kirkby MJ (1979) A physically-based variable contributing area model of basin hydrology. Hydrol Sci Bull 24(1):43–69. doi:10.1080/02626667909491834

    Article  Google Scholar 

  • BSWM (2014) Soil and physiography map of Leyte. Bureau of Soils and Water Management (BSWM) Map Library Platform. World Bank and Department of Agriculture. http://www.bswm.maps.da.gov.ph/maps-library. Accessed 15 August 2014

  • Burton A, Bathurst JC (1998) Physically-based modelling of shallow landslide sediment yield at a catchment scale. Environ Geol 35(2-3):89–99. doi:10.1007/s002540050296

    Article  Google Scholar 

  • Calcaterra D, de Riso R, Di Martire D (2004) Assessing shallow debris slide hazard in the Agnano Plain (Naples, Italy) using SINMAP, a physically based slope-stability model. In: Lacerda WA, Ehrlich M, Fontoura SAB, Sayao ASF (eds) 9th International Symposium on Landslides, Rio de Janeiro Brazil. Taylor and Francis Group, London, pp 177–183

    Google Scholar 

  • Campus S, Forlati F, Sarri H, Scavia C (2001) Shallow landslides hazard assessment based on multidisciplinary studies. In: Ho KKS, Li KS (eds) 14th Southeast Asian Geotechnical Conference Hong Kong. AA Balkema, Rotterdam, pp 703–708

    Google Scholar 

  • Catani F, Casagli N, Ermini L, Righini G, Menduni G (2005) Landslide hazard and risk mapping at catchment scale in the Arno River basin. Landslides 2(4):329–342. doi:10.1007/s10346-005-0021-0

    Article  Google Scholar 

  • Coe JA, Godt JW, Baum RL, Buckman RC, Michael JA (2004) Landslide susceptibility from topography in Guatemala. In: Lacerda WA, Ehrlich M, Fontoura SAB, Sayao ASF (eds) Landslides evaluation and stabilization, 10th Symposium on Landslides, Balkema Leiden. Taylor and Francis Group, London, pp 69–78

    Google Scholar 

  • Connell LD, Jayatilaka CJ, Nathan R (2001) Modelling flow and transport in irrigation catchments: 2. Spatial application of subcatchment model. Water Resour Res 37(4):965–977. doi:10.1029/2000WR900269

    Article  Google Scholar 

  • D’Amato Avanzi G, Giannecchini R, Puccinelli A (2003) A contribution to an evaluation of landslide susceptibility in the Apuan Alps (Italy): geologic and geomorphic factors of 1996 soil slip-debris flows. In: Picarelli L (ed) International Conference, Fast Slope Movements: Prediction and Prevention for Risk Mitigation, Naples Italy. Patron Editore, Bologna, pp 125–130

    Google Scholar 

  • D’Amato Avanzi G, Giannecchini R, Puccinelli A (2004) The influence of the geological and geomorphological settings on shallow landslides. An example in a temperate climate environment: the June 19, 1996 event in northwestern Tuscany (Italy). Eng Geol 73(3-4):215–228. doi:10.1016/j.enggeo.2004.01.005

    Article  Google Scholar 

  • Deb SK, El-Kadi AI (2009) Susceptibility assessment of shallow landslides on Oahu, Hawaii, under extreme-rainfall events. Geomorphology 108(3-4):219–233. doi:10.1016/j.geomorph.2009.01.009

    Article  Google Scholar 

  • Dietrich WE, Wilson CJ, Montgomery DR, McKean J, Bauer R (1992) Erosion thresholds and land surface morphology. J Geol 20(8):675–679. doi:10.1130/0091-7613(1992)020<0675:ETALSM>2.3.CO;2

    Article  Google Scholar 

  • Dietrich WE, Wilson CJ, Montgomery DR, McKean J (1993) Analysis of erosion thresholds, channel networks, and landscape morphology using a digital terrain model. J Geol 101:259–278

    Article  Google Scholar 

  • Dietrich WE, Reiss R, Hsu M, Montgomery DR (1995) A process-based model for colluvial soil depth and shallow landsliding using digital elevation data. Hydrol Process 9:383–400

    Article  Google Scholar 

  • Dietrich WE, Bellugi D, Real De Asua R (2001) Validation of shallow landslide model, SHALTAB, for forest management. In: Wigmosta MS, Burges SJ (eds) Land use and watersheds: human influence on hydrology and geomorphology in urban and forest areas. American Geophysical Union, pp 195-227

  • Dowman I (2004) Integration of Lidar and IfSAR for mapping. Int Arch Photogramm Remote Sens, Istanbul, Turk 35(B2):90–100

    Google Scholar 

  • Fabbri AG, Chung CF, Cendrero A, Remondo J (2003) Is prediction of future landslides possible with a GIS? Nat Hazards 30(3):487–503. doi:10.1023/B:NHAZ.0000007282.62071.75

    Article  Google Scholar 

  • Floris M, Squarzoni C, Hundseder C, Mason M, Genevois R (2010) The use of IfSAR data in GIS-based landslide susceptibility evaluation. Geophys Res Abstr 12

  • Geospatial World (2011) PRS92 surveying standard compulsory in the Philippines. Geospatial World. http://geospatialworld.net/News/View.aspx?id=21573_Article. Accessed 29 May 2015

  • Giannecchini R (2006) Relationship between rainfall and shallow landslides in the southern Apuan Alps (Italy). Nat Hazards Earth Syst Sci 6:357–364. doi:10.5194/nhess-6-357-2006

    Article  Google Scholar 

  • Grayson RB, Moore ID, McMahon TA (1992a) Physically based hydrologic modelling: 1. A terrain-based model for investigative purposes. Water Resour Res 28(10):2639–2658. doi:10.1029/92WR01258

    Article  Google Scholar 

  • Grayson RB, Moore ID, McMahon TA (1992b) Physically-based hydrologic modelling: 2. Is the concept realistic? Water Resour Res 28(10):2659–2666. doi:10.1029/92WR01259

    Article  Google Scholar 

  • Hamazaki T, Paningbatan EP Jr, Pampolino MF (1990) Data base on red-yellow and related soils in the Philippines: Part 2 Visayas and Mindanao soils. Technical Paper at College of Agriculture. University of the Philippines Los Baños and Tropical Agriculture Research Center, Tokyo

    Google Scholar 

  • Hammond C, Hall D, Miller S, Swetik P (1992) Level I stability analysis (LISA) documentation for Version 2.0: General Technical Report INT-285. USDA Forest Service, Intermountain Research Station

  • Hong Y, Adler R, Huffman G (2007) Use of satellite remote sensing data in the mapping of global landslide susceptibility. Nat Hazards 43(2):245–256. doi:10.1007/s11069-006-9104-z

    Article  Google Scholar 

  • JTWC (2013) Joint Typhoon Warning Center Best Track Archive—Typhoon Haiyan. Naval Meteorology and Oceanography Command, Stennis Space Center, Mississippi. http://www.usno.navy.mil/JTWC/. Accessed 30 November 2013

  • Knapp KR, Kruk MC, Levinson DH, Diamond HJ, Neumann CJ (2010) The International Best Track Archive for Climate Stewardship (IBTrACS): unifying tropical cyclone best track data. Bull Am Meteorol Soc 91:363–376. doi:10.1175/2009BAMS2755.1

    Article  Google Scholar 

  • Lagmay AM, Agaton RP, Bahala MAC, Briones JBLT, Cabacaba KMC, Caro CVC, Dasallas LL, Gonzalo LAL, Ladiero CH, Lapidez JP, Mungcal MTF, Puno JVR, Ramos MMAC, Santiago J, Suarez JK, Tablazon JP (2015) Devastating storm surges of typhoon Yolanda. Int J Disaster Risk Reduct 11:1–12. doi:10.1016/j.ijdrr.2014.10.006

    Article  Google Scholar 

  • Lan HX, Zhou CH, Wang LJ, Zhang HY, Li RH (2004) Landslide hazard spatial analysis and prediction using GIS in the Xiaojiang watershed, Yunnan, China. Eng Geol 76(1-2):109–128. doi:10.1016/j.enggeo.2004.06.009

    Article  Google Scholar 

  • Lee DS, Shan J, Bethel JS (2003) Class-guided building extraction from IKONOS imagery. Photogram Eng Remote Sens 69(2):143–150

    Article  Google Scholar 

  • Liao Z, Hong Y, Wang J, Fukuoka H, Sassa K, Karnawati D, Fathani F (2010) Prototyping an experimental early warning system for rainfall-induced landslides in Indonesia using satellite remote sensing and geospatial datasets. Landslides 7(3):317–324. doi:10.1007/s10346-010-0219-7

    Article  Google Scholar 

  • MapAction (2013) Philippines typhoon Haiyan (Yolanda) accumulated rainfall 06-Nov-2013 to 09-Nov-2013. Situational data source from: PAGASA, Joint Typhoon Warning Centre Philippines. http://mapaction.org. Accessed 24 March 2014

  • Meisina C, Scarabelli S (2007) A comparative analysis of terrain stability models for predicting shallow landslides in colluvial soils. Geomorphology 87(3):207–223. doi:10.1016/j.geomorph.2006.03.039

    Article  Google Scholar 

  • MGB (2006) Landslide susceptibility map of Tacloban City quadrangle Leyte Philippines. Department of Environment and Natural Resources – Mines and Geosciences Bureau (MGB) Lands Geological Survey Division. Sheet Number 3953 I. http://gdis.denr.gov.ph/mgbpublic. Accessed 1 October 2014

  • MGB (2013) Guidebook for the conduct of landslide and flood susceptibility assessment and mapping (1:10000). Department of Environment and Natural Resources – Mines and Geosciences Bureau (MGB) Lands Geological Survey Division. North Avenue, Quezon City, Philippines

  • MGB (2014) Detailed landslide and flood hazard map of Tacloban City, Leyte, Philippines. Department of Environment and Natural Resources – Mines and Geosciences Bureau (MGB) Lands Geological Survey Division. North Avenue, Quezon City, Philippines

  • Montgomery D, Dietrich W (1994) A physically based model for the topographic control on shallow landsliding. Water Resour Res 30(4):1153–1171. doi:10.1029/93WR02979

    Article  Google Scholar 

  • Montrasio L (2000) Stability analysis of soil slip. Proc of Int Conf Risk 2000, In: Brebbia CA (ed) Wit Press, Southampton, pp 357-366

  • Montrasio L, Valentino R (2008) A model for triggering mechanism of shallow landslides. Nat Hazards Earth Syst Sci 8:1149–1159. doi:10.5194/nhess-8-1149-2008

    Article  Google Scholar 

  • Morrissey MM, Wieczorek GF, Morgan BA (2001) A comparative analysis of hazard models for predicting debris flows in Madison Country, Virginia. Open file report 01-0067. USGS (ed) US Department of the Interior, US Geological Survey, Washington

  • Nadim F, Kjekstad O, Peduzzi P, Herold C, Jaedicke C (2006) Global landslide and avalanche hotspots. Landslides 3(2):159–173. doi:10.1007/s10346-006-0036-1

    Article  Google Scholar 

  • NAMRIA (2013) The Philippine IfSAR project. Internal report jointly by NAMRIA, Intermap Technologies Inc. (Denver CO) and Certeza Infosys Corp. NAMRIA Main Office, Taguig City, Philippines

  • NDRRMC (2014) National Disaster Risk Reduction and Management Council (NDRRMC) Updates regarding the effects of Typhoon “Yolanda” (HAIYAN) 17 April 2014. National Disaster Risk Reduction and Management Center, Camp Aguinaldo, Quezon City, Philippines. http://www.ndrrmc.gov.ph/index.php/21-disaster-events/1329-situational-report-re-effects-of-typhoon-yolanda-haiyan. Accessed 2 June 2014

  • Pack RT, Tarboton DG, Goodwin CN (1998) The SINMAP approach to terrain stability mapping. In: 8th Congress of the International Association of Engineering Geology, Vancouver, British Columbia, Canada 21-25 September 1998. http://www.engineering.usu.edu/cee/faculty/dtarb/iaeg.pdf. Accessed 4 May 2013

  • Pack RT, Tarboton DG, Goodwin CN (2001) Assessing terrain stability in a GIS using SINMAP. In: GIS 2001. 15th annual GIS conference, Vancouver, British Columbia. http://hydrology.usu.edu/sinmap/gis2001.pdf. Accessed 4 May 2013

  • Pack RT, Tarboton DG, Goodwin CN, Prasad A (2005) SINMAP 2: a stability index approach to terrain stability hazard mapping technical description and users guide for version 2.0. Utah State University. http://hydrology.usu.edu/sinmap2/sinmap2.PDF. Accessed 4 May 2013

  • Rigon R, Bertoldi G, Over TM (2006) GEOtop: a distributed hydrological model with coupled water and energy budgets. J Hydrometeorol 7(3):371–388. doi:10.1175/JHM497.1

    Article  Google Scholar 

  • Sarkar S, Kanugo DP (2004) An integrated approach for landslide susceptibility mapping using remote sensing and GIS. Photogramm Eng Remote Sens 70(5):617–625

    Article  Google Scholar 

  • Shufelt JA (1999) Performance evaluation and analysis of monocular building extraction from aerial imagery. IEEE Trans Pattern Anal Mach Intell 21(4):311–326

    Article  Google Scholar 

  • Soeters R, Van Westen CJ (1996) Slope instability, recognition, analysis and zonation. In: Turner AK, Schuster RL (eds) Landslides: investigation and mitigation Special Report 247. Transportation Research Board. National Research Council. National Academy Press, Washington, pp 129–177

    Google Scholar 

  • Tarboton DG (1997) A new method for the determination of flow direction and upslope areas in grid digital elevation models. Water Resour Res 33(2):309–319. doi:10.1029/96WR03137

    Article  Google Scholar 

  • Van Asch TWJ, Buma J, Van Beek LPH (1999) A view on some hydrological triggering systems in landslides. Geomorphology 30(1):25–32

    Article  Google Scholar 

  • Varnes DJ (1958) Landslide types and processes. In: Eckel EB (ed) Landslides and engineering practice, Special Report 29. Highway Research Board National Research Council, Washington DC, pp 20–47

    Google Scholar 

  • Varnes DJ (1978) Slope movement types and processes. In: Schuster RL, Krizek RJ (eds) Landslides: analysis and control, Special Report 176. Transportation Research Board National Academy of Sciences, Washington DC, pp 11–33

    Google Scholar 

  • Wieczorek GF (1987) Effect of rainfall intensity and duration on debris flows in central Santa Cruz Mountains, California. In: Costa JE, Wieczorek GF (eds) Debris flows/avalanches: processes, recognition and mitigation. Reviews in Engineering Geology, vol 7. Geological Society of America, pp 23-104

  • Wieczorek GF, Sarmiento J (1988) Rainfall, piezometric levels and debris flows near La Honda, California, in storms between 1975 and 1983. In: Ellen SD, Wieczorek GF (eds) Landslides, floods and marine effects of the storm of January 3-5, 1982 in the San Francisco Bay vol 1434. USGS Professional Paper, pp 43-62

  • Wu W, Sidle R (1995) A distributed slope stability model for steep forested basins. Water Resour Res 31:2079–2110

    Google Scholar 

  • Yange L, Guangqi C, Bo W, Lu Z, Yingbin Z, Chuan T (2013) A new approach of combining aerial photography with satellite imagery for landslide detection. Nat Hazards 66:649–669. doi:10.1007/s11069-012-0505-x

    Article  Google Scholar 

  • Zaitchik BF, van Es HM (2003) Applying a GIS slope-stability model to site-specific landslide prevention in Honduras. J Soil Water Conserv 58(1):45–53

    Google Scholar 

  • Zaitchik BF, van Es HM, Sullivan PJ (2003) Modeling slope stability in Honduras: parameter sensitivity and scale of aggregation. Soil Sci Soc Am J 67(1):268–278

    Article  Google Scholar 

  • Zizioli D, Meisina C, Valentino R, Montrasio L (2013) Comparison between different approaches to modelling shallow landslide susceptibility: a case history in Oltrepo Pavese, Northern Italy. Nat Hazards Earth Syst Sci 13:559–573. doi:10.5194/nhess-13-559-2013

    Article  Google Scholar 

Download references

Acknowledgments

The work described in this paper is supported by the Landslide Hazard Mapping Component of Project NOAH (Nationwide Operational Assessment of Hazards) under the initiatives of the Department of Science and Technology (DOST) for an improved disaster prevention and mitigation system in the Philippines. This support from the Project NOAH team is gratefully acknowledged. The authors are also grateful to the National Mapping and Resource Information Authority (NAMRIA) for providing the digital terrain model, Bureau of Soil and Water Management (BWSM) for the digitized soil maps, and the reviewers for the valuable comments.

Author information

Authors and Affiliations

  1. National Institute of Geological Sciences, University of the Philippines, Diliman 1101, Quezon City, Philippines

    Raquel P. Felix, Alfredo Mahar Francisco A. Lagmay, Rodrigo Narod C. Eco & Iris Jill G. Ortiz

  2. Nationwide Operational Assessment of Hazards, Department of Science and Technology, Quezon City, Metro Manila, NCR, Philippines

    Maricar L. Rabonza, Raquel P. Felix, Alfredo Mahar Francisco A. Lagmay, Rodrigo Narod C. Eco, Iris Jill G. Ortiz & Dakila T. Aquino

Authors
  1. Maricar L. Rabonza
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Raquel P. Felix
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Alfredo Mahar Francisco A. Lagmay
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rodrigo Narod C. Eco
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Iris Jill G. Ortiz
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Dakila T. Aquino
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Maricar L. Rabonza.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rabonza, M.L., Felix, R.P., Lagmay, A.M.F.A. et al. Shallow landslide susceptibility mapping using high-resolution topography for areas devastated by super typhoon Haiyan. Landslides 13, 201–210 (2016). https://doi.org/10.1007/s10346-015-0626-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10346-015-0626-x

Keywords

Search

Navigation