A fractal based quantification analysis of spatial grain characteristics and its variation in landscape fragmentation of Shanghai

冯永玖 Feng, Yongjiu, 刘艳 Liu, Yan, 周茜 Zhou, Qian and 韩震 Han, Zhen (2013) A fractal based quantification analysis of spatial grain characteristics and its variation in landscape fragmentation of Shanghai. 生态环境学报 Ecology and Environmental Sciences, 22 3: 443-450.

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Name Description MIMEType Size Downloads
Author 冯永玖 Feng, Yongjiu
刘艳 Liu, Yan
周茜 Zhou, Qian
韩震 Han, Zhen
Title A fractal based quantification analysis of spatial grain characteristics and its variation in landscape fragmentation of Shanghai
Formatted title
景观格局破碎化的粒度特征及其变异的分形定量研究
Translated title A fractal based quantification analysis of spatial grain characteristics and its variation in landscape fragmentation of Shanghai
Language of Title chi
eng
Journal name 生态环境学报 Ecology and Environmental Sciences
Translated journal name Ecology and Environmental Sciences
Language of Journal Name chi
eng
ISSN 1674-5906
Publication date 2013
Sub-type Article (original research)
Open Access Status
Volume 22
Issue 3
Start page 443
End page 450
Total pages 8
Place of publication Guangzhou, China
Publisher Shijie Zhishi Chubanshe
Language eng
chi
Formatted abstract
文章构建一种用于定量测度景观破碎化指标空间粒度特征的分形方法.该方法基于景观粒度特征中的幂律关系,利用双对数线性回归方法,获取了景观破碎化指标在粒度变换过程中的2个数量关系:拟合优度R2与分维数D,分别刻画景观指标粒度变换的分形特性和随空间粒度变化的程度.以1992—2011年间上海市景观破碎化的过程为例,利用提出的分形方法进行分析.研究显示,总体上内部生境面积破碎化指标FI1FI2没有清晰的分形特性;均匀性指标EI在1992年分形特性显著而在2011年分形特性却不清晰;斑块形状破碎化指标FS1其分形特性同样不清晰,而指标FS2呈现显著的分形特性,并且分维数D表现为正值,即随空间粒度的增大景观指标FS2的值减小.结果表明,拟合优度R2与分维数D的有机组合,能够定量地刻画景观破碎化中的粒度变化特征.研究同时发现,景观指标随空间粒度的变化特征,受指标内在特性、研究数据、研究区域的景观结构以及实验数据重采样方法和方案的影响.该分形方法不但可以用来测度所例举的5种景观破碎化指标的粒度特征,更适用于测度Fragstats中被广泛使用的各种景观指标.

This paper applies the fractal method to quantify the scale characteristic of landscape fragmentation metrics. The method was built based on power law relations in scaling landscape by using a linear log-log regression. Two quantitative measurements, i.e. goodness-of-fit and scaling fractal dimension, were obtained from the regression for describing the grain change in landscape fragmentation. The goodness-of-fit indicates the extent that the scaling relation of a landscape fragmentation metrics accords to the power law, whereas the scaling fractal dimension value indicates the influence degree of changing spatial grain sizes on the value of the landscape metrics. Using the landscape of Shanghai in both 1992 and 2011 as the study areas, the scaling relations of five landscape fragmentation metrics were evaluated. The research demonstrates that, as a whole, the two internal habitat fragmentation indexes, FI1 and FI2, do not show clear fractal features, while evenness index EI has an obvious fractal feature in 1992 but do not show a clear fractal feature in 2011. The patch shape fragmentation metrics FI1 has no clear fractal feature in both 1992 and 2011, however, another patch shape fragmentation metrics, FI2, shows an obvious fractal feature and has a positive scaling fractal dimension, indicating that the value of FI2 increases as the grain size decrease. The results also illustrate that the combination of the goodness-of-fits and fractal dimensions can sufficiently reveal the scaling relations of landscape fragmentation metrics. It shows that the scaling relations of the landscape fragmentation metrics are determined by the nature of the metrics, but can be effected by the experimental data, the landscape structure of the study area, and the re-sampling methods and schemes. The fractal method proposed by this research is appropriate for quantifying scaling relations of landscape metrics in Fragstats as well.
Keyword Landscape fragmentation
Scale characteristics
Spatial grain
Fractal dimension
Quantitative analysis
Shanghai
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ
Additional Notes Title and abstract only in English.

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Geography, Planning and Environmental Management Publications
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Created: Fri, 06 Sep 2013, 16:26:42 EST by Claire Lam on behalf of School of Geography, Planning & Env Management