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Calculating the Wasserstein Metric-Based Boltzmann Entropy of a Landscape Mosaic

Shannon entropy is currently the most popular method for quantifying the disorder or information of a spatial data set such as a landscape pattern and a cartographic map. However, its drawback when applied to spatial data is also well documented; it is incapable of capturing configurational disorder...

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Detalles Bibliográficos
Autores principales: Zhang, Hong, Wu, Zhiwei, Lan, Tian, Chen, Yanyu, Gao, Peichao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516855/
https://www.ncbi.nlm.nih.gov/pubmed/33286154
http://dx.doi.org/10.3390/e22040381
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author Zhang, Hong
Wu, Zhiwei
Lan, Tian
Chen, Yanyu
Gao, Peichao
author_facet Zhang, Hong
Wu, Zhiwei
Lan, Tian
Chen, Yanyu
Gao, Peichao
author_sort Zhang, Hong
collection PubMed
description Shannon entropy is currently the most popular method for quantifying the disorder or information of a spatial data set such as a landscape pattern and a cartographic map. However, its drawback when applied to spatial data is also well documented; it is incapable of capturing configurational disorder. In addition, it has been recently criticized to be thermodynamically irrelevant. Therefore, Boltzmann entropy was revisited, and methods have been developed for its calculation with landscape patterns. The latest method was developed based on the Wasserstein metric. This method incorporates spatial repetitiveness, leading to a Wasserstein metric-based Boltzmann entropy that is capable of capturing the configurational disorder of a landscape mosaic. However, the numerical work required to calculate this entropy is beyond what can be practically achieved through hand calculation. This study developed a new software tool for conveniently calculating the Wasserstein metric-based Boltzmann entropy. The tool provides a user-friendly human–computer interface and many functions. These functions include multi-format data file import function, calculation function, and data clear or copy function. This study outlines several essential technical implementations of the tool and reports the evaluation of the software tool and a case study. Experimental results demonstrate that the software tool is both efficient and convenient.
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spelling pubmed-75168552020-11-09 Calculating the Wasserstein Metric-Based Boltzmann Entropy of a Landscape Mosaic Zhang, Hong Wu, Zhiwei Lan, Tian Chen, Yanyu Gao, Peichao Entropy (Basel) Article Shannon entropy is currently the most popular method for quantifying the disorder or information of a spatial data set such as a landscape pattern and a cartographic map. However, its drawback when applied to spatial data is also well documented; it is incapable of capturing configurational disorder. In addition, it has been recently criticized to be thermodynamically irrelevant. Therefore, Boltzmann entropy was revisited, and methods have been developed for its calculation with landscape patterns. The latest method was developed based on the Wasserstein metric. This method incorporates spatial repetitiveness, leading to a Wasserstein metric-based Boltzmann entropy that is capable of capturing the configurational disorder of a landscape mosaic. However, the numerical work required to calculate this entropy is beyond what can be practically achieved through hand calculation. This study developed a new software tool for conveniently calculating the Wasserstein metric-based Boltzmann entropy. The tool provides a user-friendly human–computer interface and many functions. These functions include multi-format data file import function, calculation function, and data clear or copy function. This study outlines several essential technical implementations of the tool and reports the evaluation of the software tool and a case study. Experimental results demonstrate that the software tool is both efficient and convenient. MDPI 2020-03-26 /pmc/articles/PMC7516855/ /pubmed/33286154 http://dx.doi.org/10.3390/e22040381 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Hong
Wu, Zhiwei
Lan, Tian
Chen, Yanyu
Gao, Peichao
Calculating the Wasserstein Metric-Based Boltzmann Entropy of a Landscape Mosaic
title Calculating the Wasserstein Metric-Based Boltzmann Entropy of a Landscape Mosaic
title_full Calculating the Wasserstein Metric-Based Boltzmann Entropy of a Landscape Mosaic
title_fullStr Calculating the Wasserstein Metric-Based Boltzmann Entropy of a Landscape Mosaic
title_full_unstemmed Calculating the Wasserstein Metric-Based Boltzmann Entropy of a Landscape Mosaic
title_short Calculating the Wasserstein Metric-Based Boltzmann Entropy of a Landscape Mosaic
title_sort calculating the wasserstein metric-based boltzmann entropy of a landscape mosaic
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516855/
https://www.ncbi.nlm.nih.gov/pubmed/33286154
http://dx.doi.org/10.3390/e22040381
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