Application of Bayesian Statistics Inference Techniques Based on GIS to the Evaluation of Habitat Probabilities of Bos Gaurus Readei
基于GIS的贝叶斯统计推理技术在印度野牛生境概率评价中的应用

At present, GIS has been widely applied to the study of wildlife habitat. However, GIS, which is a tool of spatial data analysis and processing, lacks of the capacity of heuristic reasoning. Therefore, it is an important way to solve this problem by the integration of Bayesian statistics inference with GIS. in this article, the Naban river nature reserve of Xishuangbanna was taken as an experimental area, GIS and multivariate statistical techniques were applied to the development of two logistic multiple regression models for Bos gaurus readei habitat: trend surface model and environmental model. Independent variables were locational coordinates in the first model, and a set of environmental factors in the second model. Bayesian statistics were then used to integrate the two models into a Bayesian integrated model. The results show that the Bayesian integrated model is superior to the environmental model and can be applied to wildlife habitat evaluation.