摘要
采用Logistic回归模型、广义加法模型(GAM)和分类与回归树(CART)3种统计方法,对深圳市的研究区域进行了滑坡灾害的危险性评价;利用Kappa值和ROC曲线,结合危险性评价结果图对3种方法的效果进行了比较,并分析了3种方法在选取主控因子以及确定因子影响程度等方面各自具有的特点。在研究区域的条件下,GAM的效果优于Logistic回归模型和CART,Logistic回归模型和CART的效果大致相当。Logistic回归模型和CART可自主选择主控因子,通过GAM可定量研究因子的影响程度以及变化趋势。
Three statistical methods, the Logistic regression, generalized additive models (GAM), classification and regression tree (CART), were applied to the analysis of landslide susceptibility in Shenzhen using. By calculating the Kappa value and the area under the ROC curve (AUC) through 10-fold cross validation, the authors made comparison of the three methods and evaluated the credibility of the landslide susceptibility maps derived. It tan be concluded that under the condition of the study area, GAM is the best method while the performances of the Logistic regression and CART are approximately same. The Logistic regression and CART can be used to automatically detect the important factors, but by GAM the relationship between every influencing factor and the dependent variable can be visualized.
出处
《北京大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2009年第4期639-646,共8页
Acta Scientiarum Naturalium Universitatis Pekinensis
基金
国家高技术研究发展计划(2007AA12Z216)
国家自然科学基金(40701134)
香港、澳门青年学者合作研究基金(40629001)资助
关键词
滑坡灾害危险性评价
LOGISTIC回归
广义加法模型
分类与回归树
landslide susceptibility analysis
Logistic regression
generalized additive models
classification and regression tree