Nowosad Jakub, Gao Peichao
Institute of Geoecology and Geoinformation, Adam Mickiewicz University, Krygowskiego 10, 61-680 Poznan, Poland.
State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China.
Entropy (Basel). 2020 Aug 26;22(9):937. doi: 10.3390/e22090937.
Entropy is a fundamental concept in thermodynamics that is important in many fields, including image processing, neurobiology, urban planning, and sustainability. As of recently, the application of Boltzmann entropy for landscape patterns was mostly limited to the conceptual discussion. However, in the last several years, a number of methods for calculating Boltzmann entropy for landscape mosaics and gradients were proposed. We developed an R package as an open source tool for calculating Boltzmann entropy of landscape gradients. The package contains functions to calculate relative and absolute Boltzmann entropy using the hierarchy-based and the aggregation-based methods. It also supports input raster with missing (NA) values, allowing for calculations on real data. In this study, we explain ideas behind implemented methods, describe the core functionality of the software, and present three examples of its use. The examples show the basic functions in this package, how to adjust Boltzmann entropy values for data with missing values, and how to use the package in larger workflows. We expect that the package will be a useful tool in the discussion of using entropy for a description of landscape patterns and facilitate a thermodynamic understanding of landscape dynamics.
熵是热力学中的一个基本概念，在包括图像处理、神经生物学、城市规划和可持续性等许多领域都很重要。直到最近，玻尔兹曼熵在景观格局中的应用大多局限于概念性讨论。然而，在过去几年里，人们提出了一些计算景观镶嵌体和梯度的玻尔兹曼熵的方法。我们开发了一个R包作为计算景观梯度玻尔兹曼熵的开源工具。该包包含使用基于层次结构和基于聚合的方法来计算相对和绝对玻尔兹曼熵的函数。它还支持带有缺失（NA）值的输入栅格，从而能够对实际数据进行计算。在本研究中，我们解释了所实现方法背后的思想，描述了该软件的核心功能，并给出了三个使用示例。这些示例展示了该包的基本功能、如何针对缺失值数据调整玻尔兹曼熵值，以及如何在更大的工作流程中使用该包。我们期望这个包将成为讨论使用熵来描述景观格局的有用工具，并促进对景观动态的热力学理解。
