Landslide susceptibility mapping based on global and local logistic regression models in Three Gorges Reservoir area, China

Landslide susceptibility analysis based on ArcGIS and Artificial Neural Network for a large catchment in Three Gorges region, China

(2014) Renneng Bi et al.   Environmental Earth Sciences

Landslide susceptibility mapping using geographically-weighted principal component analysis

(2014) Hassanali Faraji Sabokbar et al.   GEOMORPHOLOGY

Landslide susceptibility, Peloponnese Peninsula in South Greece

(2014) C. Chalkias et al.   Journal of Maps

Landslide susceptibility zonation mapping using logistic regression and its validation in Hashtchin Region, northwest of Iran

(2014) Reza Talaei   JOURNAL OF THE GEOLOGICAL SOCIETY OF INDIA

Quantitative risk analysis for landslides: the case of the Three Gorges area, China

(2014) Ling Peng et al.   Landslides

The RUSLE erosion index as a proxy indicator for debris flow susceptibility

(2014) Alessandro Zini et al.   Landslides

Focusing on the spatial non-stationarity of landslide predisposing factors in northern Iceland

(2014) Thierry Feuillet et al.   PROGRESS IN PHYSICAL GEOGRAPHY

Landslide susceptibility mapping based on rough set theory and support vector machines: A case of the Three Gorges area, China

(2013) Ling Peng et al.   GEOMORPHOLOGY

Understanding the non-stationary associations between distrust of the health care system, health conditions, and self-rated health in the elderly: A geographically weighted regression approach

(2012) Tse-Chuan Yang et al.   HEALTH & PLACE

Autologistic modelling of susceptibility to landsliding in the Central Apennines, Italy

(2011) P.M. Atkinson et al.   GEOMORPHOLOGY

Improvement of statistical landslide susceptibility mapping by using spatial and global regression methods in the case of More and Romsdal (Norway)

(2010) Arzu Erener et al.   Landslides

GIS-based logistic regression for landslide susceptibility mapping of the Zhongxian segment in the Three Gorges area, China

(2009) Shi-Biao Bai et al.   GEOMORPHOLOGY

Exploring spatial non-stationarity of fisheries survey data using geographically weighted regression (GWR): an example from the Northwest Atlantic

(2009) M. J. S. Windle et al.   ICES JOURNAL OF MARINE SCIENCE