TY - GEN
T1 - Landslide inventory and susceptibility mapping in a mexican stratovolcano
AU - Paulín, Gabriel Legorreta
AU - Bursik, Marcus
AU - Ramírez-Herrera, M. T.
AU - Lugo-Hubp, J.
AU - Zamorano Orozco, J. J.
AU - Alcántara-Ayala, I.
PY - 2013
Y1 - 2013
N2 - This paper provides an overview of the on-going research project from the Institute of Geography at the National Autonomous University of Mexico (UNAM) that seeks to conduct multi-temporal landslide inventories and produce landslide susceptibility maps by using Geographic Information Systems (GIS). The Río Chiquito-Barranca del Muerto watershed on the southwestern flank of Pico de Orizaba volcano in Mexico is selected as a case-control study area. First, the project aims to derive a landslide inventory map from a representative sample of landslides using aerial photography and field work. Next, Multiple Logistic Regression (MLR) is used to examine the relation between landsliding and several independent variables (elevation, slope, contributing area, land use, geology, and terrain curvature) to create the susceptibility map. Finally, the model is compared with the reality expressed by the inventory map. In this study, the results of the landslide inventory and susceptibility mapping techniques are presented and discussed.
AB - This paper provides an overview of the on-going research project from the Institute of Geography at the National Autonomous University of Mexico (UNAM) that seeks to conduct multi-temporal landslide inventories and produce landslide susceptibility maps by using Geographic Information Systems (GIS). The Río Chiquito-Barranca del Muerto watershed on the southwestern flank of Pico de Orizaba volcano in Mexico is selected as a case-control study area. First, the project aims to derive a landslide inventory map from a representative sample of landslides using aerial photography and field work. Next, Multiple Logistic Regression (MLR) is used to examine the relation between landsliding and several independent variables (elevation, slope, contributing area, land use, geology, and terrain curvature) to create the susceptibility map. Finally, the model is compared with the reality expressed by the inventory map. In this study, the results of the landslide inventory and susceptibility mapping techniques are presented and discussed.
KW - GIS
KW - Landslide inventory
KW - Landslide susceptibility
KW - Multiple logistic regression
UR - https://www.scopus.com/pages/publications/84898076078
U2 - 10.1007/978-3-642-31325-7_18
DO - 10.1007/978-3-642-31325-7_18
M3 - Conference contribution
AN - SCOPUS:84898076078
SN - 9783642313240
T3 - Landslide Science and Practice: Landslide Inventory and Susceptibility and Hazard Zoning
SP - 141
EP - 146
BT - Landslide Science and Practice
PB - Springer Science and Business Media Deutschland GmbH
T2 - 2nd World Landslide Forum, WLF 2011
Y2 - 3 October 2011 through 9 October 2011
ER -