基于模糊模型识别的太行山山前平原区土地整治生态效益评价——以河北省顺平县为例  

Evaluation on Ecological Benifits of Land Reclamation in Taihang Moutain based on Fuzzy Model Recognition-A Case Study of Shunping County of Hebei Province

作　　者：石剑[1] 张路路 刘瑞卿[3] 白立佳[1] 刘磊[1] 许皞[3] 

机构地区：[1]河北农业大学资源与环境科学学院,河北保定071001 [2]河北省土地学会,河北石家庄050091 [3]河北农业大学国土资源学院,河北保定071001

出　　处：《土壤通报》2012年第6期1300-1304,共5页Chinese Journal of Soil Science

基　　金：国家重点基础研究发展规划资助项目(2005CB121107)资助

摘　　要：土地整治是社会经济发展到一定阶段解决土地利用问题的必然选择。土地整治生态效益评价对指导土地整治的科学发展具有重要意义。本文引入基于定性和定量的模糊模型识别方法,选取了土地利用多样性指数变化率、绿色植被覆盖率变化、土地垦殖率变化等9个因子构建了土地整治生态效益评价指标体系,并以太行山山前平原区中河北省顺平县土地整治项目进行实证,得出结论:该案例的生态效益属于C3类,即顺平县土地整治项目的生态效益非常显著。通过模糊模型识别评价土地整治的效果,为全面评价土地整治活动的生态环境影响和进一步规范化和科学化管理土地整治项目提供理论基础。The remote sensing technology is widely used to detect and monitoring soil salinization due to rapidly and timely provided the information about properties,spatial distribution and extent of soil salinization.In this paper,the ALOS Panchromatic image and Multispectral images were selected for the image fusion method,including HIS,PCA,Gram-Schmidt and Wavelet.The performance of each method was analyzed by qualitatively and quantitatively.Also supervised classification method used to extract the soil salinization Information from multispectral images and fused images respectively.The results showed that the Wavelet fusion method can be provide more information,higher spatial resolution and higher classification results＇s accuracy compared with multispectral images.It was most effective image fusion method for monitoring the salinized soil,an advantage over the common data fution methods such as HIS,PCA and Gram-Schmidt.

关 键 词：土地整治 生态效益评价 模糊模型识别 太行山山前平原区 

分 类 号：F307.11[经济管理—产业经济]