%0 Journal Article
%T Assessment of giant panda habitat based on integration of expert system and neural network
集成的专家系统和神经网络应用于大熊猫生境评价
%A Andrew KSkidmore
%A MCBronsveld
%A LIU Xuehua
%A Andrew KSkidmore
%A MCBronsveld
%A
刘雪华
%A Andrew K.Skidmore
%A M.C.Bronsveld
%J 应用生态学报
%D 2006
%I
%X To conserve giant panda effectively, it is important to understand the spatial pattern and temporal change of its habitat. Mapping is an effective approach for wildlife habitat evaluation and monitoring. The application of recently developed artificial intelligence tools, including expert systems and neural networks, could integrate qualitative and quantitative information for modeling complex systems, and built the information into a GIS, which could be helpful for giant panda habitat mapping. This study built a mapping approach for giant panda habitat mapping, which integrated expert system and neural network classifiers (ESNNC), and used multi-type data within GIS. The giant panda habitat types and their suitability were mapped by ESNNC. The results showed that the habitat types and their suitability in Foping Nature Reserve were assessed with a higher accuracy (> 80 %) by ESNNC, compared with non-integrated classifiers, i. e., expert system, neural network, and maximum likelihood. Z-statistic test showed that ESNNC was significantly better than the other three non-integrated classifiers. It was recommended that the integrated approach could be widely applied into wildlife habitat assessment.
%K Expert system
%K Neural network
%K Remote sensing
%K GIS
%K Habitat mapping
%K Spatial analysis
%K Giant panda
%K Foping Nature Reserve
专家系统
%K 神经网络
%K 遥感
%K 地理信息系统
%K 生境制图
%K 空间分析
%K 大熊猫
%K 佛坪保护区
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=90BA3D13E7F3BC869AC96FB3DA594E3FE34FBF7B8BC0E591&jid=42FEDDFE54F8BCD9D5FD1926ABDD7722&aid=368049610E4FE186&yid=37904DC365DD7266&vid=BCA2697F357F2001&iid=38B194292C032A66&sid=BEE722AB5028E81F&eid=5824536C90612D67&journal_id=1001-9332&journal_name=应用生态学报&referenced_num=0&reference_num=39