Landslide Hazard Mapping in Rwanda Using Logistic Regression

Thursday, 17 December 2015
Poster Hall (Moscone South)
Angela Piller, Portland State University, Geology, Portland, OR, United States, Eric Anderson, University of Alabama in Huntsville, Earth System Science Center, Huntsville, AL, United States; NASA-SERVIR, Hindu Kush-Himalaya Point of Contact, Huntsville, AL, United States and Hannah Ballard, University of Alabama in Huntsville, Huntsville, AL, United States
Landslides in the United States cause more than $1 billion in damages and 50 deaths per year (USGS 2014). Globally, figures are much more grave, yet monitoring, mapping and forecasting of these hazards are less than adequate. Seventy-five percent of the population of Rwanda earns a living from farming, mostly subsistence. Loss of farmland, housing, or life, to landslides is a very real hazard. Landslides in Rwanda have an impact at the economic, social, and environmental level. In a developing nation that faces challenges in tracking, cataloging, and predicting the numerous landslides that occur each year, satellite imagery and spatial analysis allow for remote study. We have focused on the development of a landslide inventory and a statistical methodology for assessing landslide hazards. Using logistic regression on approximately 30 test variables (i.e. slope, soil type, land cover, etc.) and a sample of over 200 landslides, we determine which variables are statistically most relevant to landslide occurrence in Rwanda. A preliminary predictive hazard map for Rwanda has been produced, using the variables selected from the logistic regression analysis.