RT - Journal Article
T1 - Landslide Susceptibility Mapping in Sajaroud Basin Using Logistic Regression Model
JF - JSTNAR
YR - 2010
JO - JSTNAR
VO - 14
IS - 53
UR - http://jstnar.iut.ac.ir/article-1-1336-en.html
SP - 99
EP - 112
K1 - Landslide
K1 - Hazard mapping
K1 - Logistic Regression
K1 - Geographic information System
K1 - Sajaroud
AB - In this research, logistic regression analysis was used to create a landslide hazard map for Sajaroud basin. At first, an inventory map of 95 landslides was used to preduce a dependent variable, which takes a value of 0 for absence and 1 for presence of landslides. Ten factors affecting landslide occurence such as elevation , slope gradient, slope aspect, slope curvature, rainfall, distance from fault, distance from drainage, distance from road , land use and geology were taken as independent parameters. The effect of each parameter on landslide occurrence was determined from the corresponding coefficient that appears in the logistic regression function. The interpretation of the coefficients showed that road network plays the most important role in determining landslide occurrence. Elevation, curvature, rainfall and distance from fault were excluded from the final analysis because these variables did not significantly add to the predictive power of the logistic regression. After transferring final probability function into Arc/view 3.2 software, landslide susceptibility map was prepared. The results of accuracy assessment showed that overall accuracy of produced map is 85.3 percent. Therefore, 53% of the area was located in very low hazard, 18.3% in low hazard, 21% in moderate hazard and 7.7 % residual area is located in high hazard regions. Model and then susceptibility map verity was assessed using -2LL, Cox and Snell R2, Nagelkerk R2, and was validated.
LA eng
UL http://jstnar.iut.ac.ir/article-1-1336-en.html
M3
ER -