4.4 Article

Evaluating the effectiveness of landscape configuration metrics from landscape composition metrics

Journal

LANDSCAPE AND ECOLOGICAL ENGINEERING
Volume 13, Issue 1, Pages 169-181

Publisher

SPRINGER JAPAN KK
DOI: 10.1007/s11355-016-0314-6

Keywords

Multivariable regression analysis; Land-use categorization; Scale effect; Landscape heterogeneity

Funding

  1. Key Laboratory for Digital Land and Resources of Jiangxi Province, East China University of Technology [DLLJ201610]
  2. Doctoral Scientific Research Foundation of East China University of Technology [DHBK2015311]
  3. key laboratory of watershed ecology and geographical environment monitoring, NASG [WE2016018]

Ask authors/readers for more resources

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 (R (2)) 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 R (2) 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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.4
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available