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| 基于RS和ANN的城市土地集约利用潜力评价 | |
| 引用本文： | 王力 牛铮 尹君 李志伟. 基于RS和ANN的城市土地集约利用潜力评价[J]. 土木与环境工程学报, 2007, 29(3): 32-35 |
| 作者姓名： | 王力 牛铮 尹君 李志伟 |
| 作者单位： | 1. 中国科学院遥感应用研究所遥感科学国家重点实验室,北京,100101;中国科学院研究生院,北京,100039 2. 中国科学院遥感应用研究所遥感科学国家重点实验室,北京,100101 3. 河北农业大学城乡建设学院,河北保定,071001 |
| 基金项目： | 国家自然科学基金资助项目(40571117) |
| 摘 要： | 在建立了以遥感数据为主要数据源的城市土地利用潜力评价指标体系的基础上,以人工神经网络(ANN)方法作为主体的评价方法,构建了一个定量的土地集约利用潜力评价模型,并应用其对石家庄市土地集约利用潜力进行了评价。评价结果表明,石家庄市桥东区居住用地、商业用地中粗放利用类型占主体,分别达到41.25%和43.09%,居住用地和商业用地集约利用水平较低,而在工业用地中适度利用类型达到61.7%,因此工业用地集约利用水平较高。 |
| 关 键 词： | 土地集约利用潜力评价 遥感 人工神经网络 石家庄 |
| 文章编号： | 1006-7329（2007）03-0032-04 |
| 修稿时间： | 2006-10-18 |
Potential Evaluation of Land Intensive Use in Metropolis Based on RS and ANN |
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| WANG Li,NIU Zheng,YIN Jun,LI Zhi-wei. Potential Evaluation of Land Intensive Use in Metropolis Based on RS and ANN[J]. Journal of Civil and Environmental Engineering, 2007, 29(3): 32-35 | |
| Authors: | WANG Li NIU Zheng YIN Jun LI Zhi-wei |
| Affiliation: | 1. The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101 ,China; 2. Graduate School of the Chinese Academy of Sciences, Beijing 100039, China; 3. College of Urban and Rural construction, Agriculture University of Hebei, Baoding, Hebei 071001, China |
| Abstract: | The index system of potential evaluation of land intensive use in metropolis is put forward.RS is the primary data source in this system.Based on this system,a quantitative evaluation model of land intensive use is founded,which regards the artificial neural network(ANN) method as the subject appraisal method.This model is applied to evaluate the potential of land intensive use in Shijiazhuang.According to the result,the extensive use is predominant in residential area and commercial area,and the moderate use is most in industrial area.Therefore,the level of Land Intensive Use of residential area and commercial area is lower,and the level of Land Intensive Use of industrial area is higher. |
| Keywords: | potential evaluation of land intensive use remote sensing artificial neural network Shijiazhuang |
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