Evaluating the effectiveness of landscape configuration metrics from landscape composition metrics

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• 作者：Xiaojian Wei ; Zhanchun Xiao ; Qingling Li…
• 关键词：Multivariable regression analysis ; Land ; use categorization ; Scale effect ; Landscape heterogeneity
• 刊名：Landscape and Ecological Engineering
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：13
• 期：1
• 页码：169-181
• 全文大小：
• 刊物类别：Earth and Environmental Science
• 刊物主题：Landscape Ecology; Nature Conservation; Civil Engineering; Environmental Management; Landscape/Regional and Urban Planning; Plant Ecology;
• 出版者：Springer Japan
• ISSN：1860-188X
• 卷排序：13

文摘

Although landscape configuration and landscape composition metrics are correlated theoretically and empirically, the effectiveness of configuration metrics from composition metrics has not been explicitly investigated. This study explored to what extent substantial information of configuration metrics increases from certain easily calculated and extensively used composition metrics and how strongly the effectiveness is influenced by different factors. The effectiveness of 12 landscape configuration metrics from the percentage of landscape (PLAND) of each land-use class and patch density (PD) was evaluated through the coefficient of determination (R2) of multivariate stepwise linear regression analysis of 150 town-based landscape samples from three regions. The different landscape configuration metrics from PLAND and PD presented significantly different performances in terms of effectiveness [the contagion index and aggregation index possess minimal information, and the effective mesh size (MESH) and area-weighted mean patch fractal dimension possess abundant information]. Furthermore, the effectiveness of configuration metrics showed different responses to changing cell sizes and different land-use categorization in different regions (interspersion and juxtaposition index, patch cohesion index, and MESH exhibited large variations in R2 among the different regions). No single, uniform, consistent characteristic of effectiveness was determined across different factors. This new approach to understanding the effectiveness of configuration metrics helps clarify landscape metrics and is fundamental to landscape metric assessment.