中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Landscape change detection of the newly created wetland in Yellow River Delta

文献类型:期刊论文

作者Yue, TX
刊名ECOLOGICAL MODELLING
出版日期2003
卷号164期号:1页码:21-31
关键词landscape change detection landscape connectivity ecological diversity TM images newly created wetland
通讯作者Yue TX
中文摘要Four models are employed in the landscape change detection of the newly created wetland. The models include ones for patch connectivity. ecological diversity, human impact intensity and mean center of land cover. The landscape data of the newly created wetland in Yellow River Delta in 1984, 1991, and 1996 are produced from the unsupervised classification and the supervised classification on the basis of integrating Landsat TM images of the newly created wetland in the four seasons of the each year. The result from operating the models into the data shows that the newly created wetland landscape in Yellow River Delta had a great chance. The driving focus of the change are mainly from natural evolution of the newly created wetland and rapid population growth, especially non-peasant population growth in Yellow River Delta because a considerable amount of oil and gas fields have been found in the Yellow River Delta. For preventing the newly created wetland from more destruction and conserving benign Succession of the ecosystems in the newly created wetland, six measures are suggested on the basis of research results. (C) 2003 Elsevier Science B.V. All rights reserved.
学科主题Ecology
收录类别SCI
公开日期2011-05-27
源URL[http://ir.igsnrr.ac.cn/handle/311030/3201]  
专题陆地表层格局与模拟院重点实验室_外文论文
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GB/T 7714
Yue, TX. Landscape change detection of the newly created wetland in Yellow River Delta[J]. ECOLOGICAL MODELLING,2003,164(1):21-31.
APA Yue, TX.(2003).Landscape change detection of the newly created wetland in Yellow River Delta.ECOLOGICAL MODELLING,164(1),21-31.
MLA Yue, TX."Landscape change detection of the newly created wetland in Yellow River Delta".ECOLOGICAL MODELLING 164.1(2003):21-31.

入库方式: OAI收割

来源:地理科学与资源研究所

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