Landslide prediction is very important in disaster prevention and reduction procedures

including spatial and temporal landslide prediction

and it is one of practical research fields to evaluate and predict landslide hazards using statistic analysis model

but the prediction result depends mostly on sample numbers and spatial distribution.The aim of this study is to analyze and compare the landslide prediction using different models in Cameron highland

Malaysia

and nine evaluation factors are selected

i.e.elevation

topographic slope

topographic aspect

topographic curvature

distance from lineament

land use and land cover

geomorphic characteristics

distance from road and drainage.Support vector machine（SVM） and logistic regression model are applied to landslide spatial prediction and mapping

and the results show that average prediction accuracy using logistic regression model is about 86.2%

but 95.9% using SVM model

at the same time

the prediction result based on SVM model is more changeless

less influenced by sample numbers.So the SVM model is commended for actual applications

and it is more efficient and accurate for landslide hazard evaluation and spatial prediction.