Shallow Landslide Hazard Mapping for Davao Oriental, Philippines, Using a Deterministic GIS Model

Part of the Advances in Natural and Technological Hazards Research book series (NTHR, volume 45)


Davao Oriental located at 7°30′N and 126°50′E is one of the many landslide-prone provinces in the Philippines experiencing severe rainfall throughout the year. With the increase in population and other infrastructural developments, it is necessary to map the landslide potential of the area, to assure the safety of the people and delineate suitable land for development. In order to produce rainfall-induced shallow landslide hazard maps, Stability Index Mapping (SINMAP) was used over a 5-m interferometric synthetic aperture radar (IFSAR)-derived digital terrain model (DTM). SINMAP is based on the infinite slope stability model. Topographic, soil geotechnical, and hydrologic parameters (cohesion, angle of friction, bulk density, infiltration rate, and hydraulic transmissivity) were assigned to each pixel of the DTM with the total area of 5,164.5 km2 to compute for the corresponding factor of safety. The landslide hazard maps generated using SINMAP are found to be accurate when compared to the landslide inventory from 2003 to 2013. The landslide susceptibility classification was translated to zoning maps indicating areas that are safe from shallow landslides, areas that can be built upon with slope intervention and monitoring, and the no-build areas. These maps complement the structurally controlled landslide, debris flow, and other natural hazard maps that are being prepared to aid proper zoning for residential and infrastructural developments.


Landslide Hazard mapping Deterministic model Philippines Davao Oriental Natural hazards 



We would like to thank the creators of SINMAP (Pack et al.) for making this program available to the research and development community and communicating with us in the early stages. We also thank the National Mapping and Resource Information Authority (NAMRIA) for the IFSAR DTM used in this simulation. Funding for the project titled Enhancing Landslide Hazard Maps Through LIDAR and Other High Resolution Imageries is from the Department of Science and Technology (DOST), government of the Philippines.

Other Notes

DOST Project NOAH is a program implemented by the Philippine government to assess the different hazards present in the Philippines. Assessment of flood, landslide, and storm surge hazards is part of the program. Completed maps are to be added to the NOAH website ( for free access to the general public to aid in the information dissemination to reduce effects of meteorological hazards in the country. The website, in partnership with PAGASA, also displays various weather sensors and visualizations to aid in the understanding of weather data.


  1. 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: U.S. Geological Survey Open-File Report, 2008–1159, p 75Google Scholar
  2. Caine N (1980) The rainfall intensity: duration control of shallow landslides and debris flows. Geogr Ann Ser A Phys Geogr 62:23–27. doi: 10.2307/520449 CrossRefGoogle Scholar
  3. Cannon SH, Gartner J (2005) Wildfire related debris flow from a hazards perspective. In: Debris-flow hazards and related phenomena, Springer-Praxis books in geophysical sciences. Springer, Berlin, pp 321–344. doi: 10.1007/3-540-27129-5_15 Google Scholar
  4. Dietrich WE, Reiss R, Hsu ML, Montgomery DR (1995) A process-based model for colluvial soil depth and shallow landsliding using digital elevation data. Hydrol Process 9:383–400. doi: 10.1002/hyp.3360090311 CrossRefGoogle Scholar
  5. Felicisimo M, Cuartero A, Remondo J, Quirós E (2013) Mapping landslide susceptibility with logistic regression, multiple adaptive regression splines, classification and regression trees, and maximum entropy methods: a comparative study. Landslides 10(2):175–189. doi: 10.1007/s10346-012-0320-1 CrossRefGoogle Scholar
  6. Godt JW, Baum RL, Lu N (2009) Landsliding in partially saturated materials. Geophys Res Lett 36:L02403. doi: 10.1029/2008GL035996 Google Scholar
  7. Hammond C, Hall D, Miller S, Swetik P (1992) Level I Stability Analysis (LISA) Documentation for Version 2.0 (General technical Report INT-285). Accessed 16 Jun 2014
  8. Hong Y, Adler RF, Huffman GJ (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 CrossRefGoogle Scholar
  9. Iverson RM (2000) Landslide triggering by rain infiltration. Water Resour Res 36(7):1897–1910. doi: 10.1029/2000WR900090 CrossRefGoogle Scholar
  10. Lagmay AMF (2012) Disseminating near-real time hazards information and flood maps in the Philippines through web-GIS. Project NOAH Open File Reports. V1:21–36: ISSN-23627409Google Scholar
  11. Lu N, Godt JW (2008) Infinite slope stability under steady unsaturated seepage conditions. Water Resour Res 44:W11404. doi: 10.1029/2008WR006976 Google Scholar
  12. MGB Geoportal (2010) Landslide hazard map of Davao Oriental, Mines and Geosciences Bureau Geoportal. Accessed 4 Jun 2014
  13. MGB-UNDP (2004, March) Manual for standardization, geohazard mapping program. Mines and Geosciences Bureau project, funded by the United Nations Development Program, Montgomery DR, Dietrich WE (1994) A physically based model for the topographic control on shallow landsliding. Water Resour Res 30(4):1153–1171. doi: 10.1029/93WR02979 CrossRefGoogle Scholar
  14. Orense R (2004) Slope failures triggered by heavy rainfall. Philipp Eng J 25(2):73–90. Accessed 5 Apr 2014
  15. Pack RT, Tarboton DG, Goodwin CN (1998) Terrain stability mapping with SINMAP, technical description and users guide for version 1.00, Report number 4114-0, Terratech Consulting, Salmon Arm, BC, CanadaGoogle Scholar
  16. Pack RT, Tarboton DG, Goodwin CN, Prasad A (2005) SINMAP 2- A stability index approach to terrain stability mapping. Utah State University. Accessed 5 May 2013
  17. Ren D, Leslie LM, Karoly D (2008) Mudslide risk analysis using a new constitutive relationship for granular flow. Earth Interact 12:1–16. doi: Google Scholar
  18. Ren D, Wang J, Fu R, Karoly D, Hong Y, Leslie LM, Fu C, Huang G (2009) Mudslide-caused ecosystem degradation following Wenchuan earthquake 2008. Geophys Res Lett 36:L05401. doi: 10.1029/2008GL036702 Google Scholar
  19. Witt AC (2005) Using a GIS (Geographic Information System) to model slope instability and debris flow hazards in the French Board river watershed. Thesis, North Carolina State University. Accessed 6 Oct 2014
  20. Wu W, Sidle RC (1995) A distributed slope stability model for steep forested basins. Water Resour Res 31(8):2097–2110. doi: 10.1029/95WR01136 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Institute of Civil EngineeringUniversity of the PhilippinesQuezon CityPhilippines
  2. 2.Project NOAH, Deparment of Science and TechnologyUniversity of the PhilippinesQuezon CityPhilippines
  3. 3.National Institute of Geological SciencesUniversity of the PhilippinesQuezon CityPhilippines

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