The Effect of Land Use on Landscape Ecological Risk in Yancheng Coastal Area, Jiangsu Province

doi:10.6046/gtzyyg.2011.03.25

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Abstract

With the geo-statistical theoretical model and GIS technology, three periods of landscape data from 1987 to 2007 in Yancheng coastal area were assessed for ecological risk and analyzed for spatial variability. Some conclusions have been reached: 1 With the growing intensity of human activities in coastal wetlands, the size of natural wetlands gradually decreased, and the disturbance gradually increased in coastal area. 2 The ecological environment of this area was subjected to increased interference of human activity and landscape fragmentation from 1987. The change of landscape structure led to significant differences in risk indexes of landscape ecology in time and space. The landscape ecological risk of Yancheng coastal area tended to expand. 3 The degree of spatial variability increased in these 20 years. In 1997, spatial heterogeneity of random party was the largest, and the space-related degree was the largest in landscape ecological risk. 4 From 1987 to 2007, the scale and direction of spatial heterogeneity (autocorrelation) of landscape ecological risk in Yancheng coastal area also changed significantly. 5 In each period, the variation in EW direction was larger than that in NS direction. In EW direction, the intensity of landscape ecological risk changed from low to high and then to low again.

Keywords IKONOS Kernel PCA SVM Post-classification

:	TP 79
	X826

Issue Date: 07 September 2011

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	ZHANG Wei
	ZHANG Wei
	LIU Shi-ying
	YANG Jin-zhong
	MAO Sheng-yi

Cite this article:

ZHANG Wei,ZHANG Wei,LIU Shi-ying, et al. The Effect of Land Use on Landscape Ecological Risk in Yancheng Coastal Area, Jiangsu Province[J]. REMOTE SENSING FOR LAND & RESOURCES, 2011, 23(3): 140-145.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2011.03.25 OR https://www.gtzyyg.com/EN/Y2011/V23/I3/140

[1] 王娟,崔保山,刘杰,等.云南澜沧江流域土地利用及其变化对景观生态风险的影响
[J].环境科学学报,2008,28(2),269-277.

[2] 邱彭华,徐颂军,谢跟踪,等.基于景观格局和生态敏感性的海南西部地区生态脆弱性分析
[J].生态学报,2007,27(4):1257-1264.

[3] 朱永恒,濮励杰,赵春雨.景观生态质量评价研究——以吴江市为例
[J].地理科学,2007,27(2):182-187.

[4] 许学工,林辉平,付在毅,等.黄河三角洲湿地区域生态风险评价
[J].北京大学学报(自然科学版),2001,37(1):111-120.

[5] 陈辉,刘劲松,曹宇,等.生态风险评价研究进展
[J].生态学报,2006,26(5):1258-1266.

[6] Plieninger T,Pulido F J,Schaich H.Effects of Land-use and Landscape Structure on Holm Oak Recruitment and Regeneration at Farm Level in Quercus Iex Ldehesas
[J].Journal of Arid Environments,2004,57(3):345-364.

[7] Hayes E H,Landis W G.Regional Ecological Risk Assessment of a Near Shore Marine Environment:Cherry Point,WA
[J].Human and Ecological Risk Assessment,2002,10(2):299-325.

[8] 李景刚,何春阳,李晓兵.快速城市化地区自然/半自然景观空间生态风险评价研究—以北京为例
[J].自然资源学报,2008,23(1):33-47.

[9] 陈洪全.江苏沿海湿地资源特点及其保护利用
[J].生态经济,2003(10):195-198.

[10] 张晓龙,李培英,李萍,等.中国滨海湿地研究现状与展望
[J].海洋科学进展,2005,23(1):87-95.

[11] 陈鹏,潘晓玲.干旱区内陆流域区域景观生态风险分析——以阜康三工河流域为例
[J].生态学杂志,2003,22(4):116-120.

[12] 冯志轩,罗贤,高抒.江苏盐城自然保护区核心区环境动态的遥感分析
[J].海洋通报,2007,26(6):68-74.

[13] 岳文泽,徐建华,徐丽华,等.不同尺度下城市景观综合指数的空间变异特征研究
[J].应用生态学报,2005,16(11):2053-2059.

[14] 王波,毛任钊,曹健,等.海河低平原区农田重金属含量的空间变异性—以河北省肥乡县为例
[J].生态学报,2006,26(12):4082-4090.

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