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Support Vector Regression on GIS and Map Data for Landslide Susceptibility of Laguna, Philippines

Original Proposal Title: Application of Support Vector Regression on GIS and Map Data for Landslide Susceptibility of Laguna, Philippines

Landslide is a movement of soil, rock, and debris down a sloped part of land. It is a natural disaster that sometimes is unavoidable when the stability of a slope decreases or changes due to natural or instigated factors. Basically, it is gravity acting upon the earth that already has pre-conditional factors. Landslide may be caused but not exclusive to these natural causes: erosion, earthquakes, piling of groundwater or flooding because of heavy rain, weak soil structure and composition. There are also human activities that may contribute to, or even cause, a landslide, these includes: deforestation, vibrations caused by heavy machinery, quarrying, and mining; with heavy rainfall, they will increase the fragility and decrease the integrity of the earth.

Landslide as a natural disaster can cause property damage, injury, and death. Multiple impact factors that interact and may cause landslides can be modeled to create a precursor signal for early warning and prevention of this natural disaster. Geographic Information Systems (GIS) along with maps and weather and precipitation data have been used with Machine Learning algorithms and predictive analytic models to make reliable and life saving forecasts.