A New Approach to Liquefaction Potential Mapping using Satellite Remote Sensing and Support Vector Machine Algorithm

Earthquake induced ground shaking in areas with saturated sandy soils pose a major threat to communities due to soil liquefaction. Currently liquefaction potential is assessed on two scales: regionally based on surficial geologic unit or locally based on geotechnical sample data. However, the regional maps fail to capture the variability whereas; the collection of geotechnical data on the local scale is costly. Remote sensing products from air and space borne sensors allow us to explore the land surface parameters at different spatial scales. We explore the use of satellite based remote sensing data (Landsat 7 ETM+), together with other satellite derived products and geologic map at a test site in California. A supervised classification using Support Vector Machine (SVM) yielded an overall classification accuracy of 84% on a test data, indicating that the approach is promising for liquefaction potential mapping.