• landslides;
  • vegetation influenced landslide index;
  • surface cover index;
  • remote sensing;
  • GIS


Local environmental conditions are known to be the most influential in landslide dynamics. Some variables, such as slope, elevation, lithology, vegetative cover, and soil type, are more common and influential than others. Every variable, except for vegetative cover, has been incorporated into many different statistical models as a continuous variable showing nuances and differentiation among the data. In regions where vegetative cover is the single most important variable in determining slope stability, a land cover classification cannot provide the level of information required for efficient modeling of landslide events. It is hoped that the surface cover index (SCI) can be used to numerically assess vegetative cover by using Landsat imagery and sub-pixel analysis. Two models utilizing simple raster calculations involving slope and the SCI were created. Each model was then assessed and validated for accuracy by using a user-created multi-temporal landslide inventory of the Dominical, Costa Rica area. Results determined that normalized inputs of slope and SCI can produce an algorithm with a high degree of accuracy and proved that the SCI can be used in assessing landslide hazard in a tropical forest environment. Copyright © 2011 John Wiley & Sons, Ltd.