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Spatial Heterogeneity Analysis: Introducing a New Form of Spatial Entropy

3S Center, Tsinghua University; Institute of Geomatics, Department of Civil Engineering, Tsinghua University, Beijing 100084, China
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Entropy 2018, 20(6), 398; https://doi.org/10.3390/e20060398
Received: 26 April 2018 / Revised: 17 May 2018 / Accepted: 18 May 2018 / Published: 23 May 2018
(This article belongs to the Special Issue Spatial Information Theory)
Distinguishing and characterizing different landscape patterns have long been the primary concerns of quantitative landscape ecology. Information theory and entropy-related metrics have provided the deepest insights in complex system analysis, and have high relevance in landscape ecology. However, ideal methods to compare different landscape patterns from an entropy view are still lacking. The overall aim of this research is to propose a new form of spatial entropy (Hs) in order to distinguish and characterize different landscape patterns. Hs is an entropy-related index based on information theory, and integrates proximity as a key spatial component into the measurement of spatial diversity. Proximity contains two aspects, i.e., total edge length and distance, and by including both aspects gives richer information about spatial pattern than metrics that only consider one aspect. Thus, Hs provides a novel way to study the spatial structures of landscape patterns where both the edge length and distance relationships are relevant. We compare the performances of Hs and other similar approaches through both simulated and real-life landscape patterns. Results show that Hs is more flexible and objective in distinguishing and characterizing different landscape patterns. We believe that this metric will facilitate the exploration of relationships between landscape patterns and ecological processes. View Full-Text
Keywords: information entropy; landscape configuration; thermodynamics; spatial diversity; proximity information entropy; landscape configuration; thermodynamics; spatial diversity; proximity
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MDPI and ACS Style

Wang, C.; Zhao, H. Spatial Heterogeneity Analysis: Introducing a New Form of Spatial Entropy. Entropy 2018, 20, 398.

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