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REMOTE SENSING FOR LAND & RESOURCES    2010, Vol. 22 Issue (s1) : 174-177     DOI: 10.6046/gtzyyg.2010.s1.36
Technology Application |
The Remote Sensing Dynamic Monitoring of China’s Shoreline Evolution in the Past 30 Years
 ZHAO Yu-Ling
China Aero Geophysical Survey and Remote Sensing Center for Land and Resources, Beijing 100083, China
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Abstract  

 Based on large quantities of remote sensing data as well as topographic and tidal data, this paper studied the

evolution of the shoreline in China since 1975. The results show that the most typical coast is distributed in the three

economic zones. The mangrove coast is mostly distributed in the Zhujiang Delta Economic Zone, and the total length of the

coast had been shortening from 1975 to 2006. Different typical shorelines have different evolutionary characteristics. The

natural shoreline has been shortening in the past three decades, whereas the man-made shoreline has been extending since

1975.

Keywords Altered rock information extraction      Principal component analysis      Band ratio      Technological process     
:     
  TP 79  
Issue Date: 13 November 2010
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YANG Jin-zhong
FANG Hong-bin
ZHANG Yu-jun
CHEN Wei
Cite this article:   
YANG Jin-zhong,FANG Hong-bin,ZHANG Yu-jun, et al. The Remote Sensing Dynamic Monitoring of China’s Shoreline Evolution in the Past 30 Years[J]. REMOTE SENSING FOR LAND & RESOURCES, 2010, 22(s1): 174-177.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2010.s1.36     OR     https://www.gtzyyg.com/EN/Y2010/V22/Is1/174

[1]中国科学院南京地理与湖泊研究所,江苏省海岸带和海涂资源综合考察队.江苏省海岸带自然资源地图集[M]. 北京:科学出版社,


1988.


[2]朱晓华.关于海岸线长度不确定性问题的研究[J].海洋开发与管理, 2000(1):23-25.


[3]朱晓华,王建,陈霞.海岸线空间分形性质探讨——以江苏省为例[J].地理科学, 2001,21(1):70-76.


[4]蔡则健,吴曙亮. 江苏海岸线演变趋势遥感分析[J]. 国土资源遥感,2002(3):19-23.


[5]赵玉灵,聂洪峰,杨金中.环渤海经济区岸线变迁遥感动态调查[C]∥2008年遥感科技论坛.2008:133-140.


[6]杨金中,赵玉灵,王毅.杭州湾南、北两岸潮滩变迁遥感动态调查[J].地质科学,2004,39(2):168-177.


[7]赵玉灵,杨金中.浙东象山港岸线及潮滩变迁遥感调查[J].国土资源遥感,2007(4):114-117.


[8]杨晓梅,周成虎,杜云艳,等.海岸带遥感综合技术与实例研究[M].北京:海洋出版社,2005.


[9]秦大河,陈宜瑜,李学勇,等.中国气候与环境演变[M].北京:科学出版社,2005.


 

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