Absolute entropy how to#

The third argument, na_adjust, allows for scaling the output value based on the proportion of missing (NA) cells in the input data.

It can be either “hierarchy” for the hierarchy-based method or “aggregation” for the aggregation-based method . The second argument, method, allows selecting a method of calculation used. Input data can be either a matrix, array, object from the raster package (RasterLayer, RasterStack, RasterBrick), or from the stars package . This package has one main function get_boltzmann(), which expects input data as the first argument and several additional arguments as the next arguments. The belg package, in order to be used, must be first attached to an R session with library(belg). Such observations have drawn much attention and described as “astounding” by leading ecologists. They further observed that almost all applications of Shannon entropy to landscape ecology-including spatial heterogeneity, the unpredictability of pattern dynamics and, and pattern scale dependence-can be questionable in terms of thermodynamic basis. concluded that Shannon entropy is “merely a formal parallelism” (p. 54) to Boltzmann entropy. However, considerable criticisms are emerging about the equivalence between the two entropies. It has been widely considered as Boltzmann entropy in essence, and both entropies are used interchangeably (e.g., Lopez-Ruiz et al. Shannon entropy (i.e., information entropy) was proposed by the American mathematician Claude Shannon to quantify the information content of a telegraph message and laid the foundation of information theory.

), image processing (e.g., Sawant and Manoharan ), urban planning (e.g., Fistola and La Rocca ), and neurobiology (e.g., Blokh and Stambler ).Īs a result, the use of Boltzmann entropy in landscape ecology has long limited to conceptual discussion, with Shannon entropy being used as an alternative in practical applications (e.g., Rocchini et al. In addition to its fundamental role in physics, it has found applications in diverse fields such as sustainability (e.g., Gao et al. Entropy has been widely used to express the most remarkable law of classical physics, the second law of thermodynamics, as follows, “the entropy of a closed system increases continuously and irrevocably toward a maximum”. This concept (widely referred to as thermodynamic entropy) was first described by the German physicist Rudolf Clausius in the 1850s to discuss the change of unavailable energy during a spontaneous process then modeled by the Austrian physicist Ludwig Boltzmann using the famous Boltzmann equation (hence the term Boltzmann entropy). We expect that the belg 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.Įntropy is a core concept in thermodynamics, which is a branch of physics, and explains “almost all known physical processes in the universe”.

Absolute entropy how to#

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 belg package in larger workflows. In this study, we explain ideas behind implemented methods, describe the core functionality of the software, and present three examples of its use. It also supports input raster with missing (NA) values, allowing for calculations on real data. The package contains functions to calculate relative and absolute Boltzmann entropy using the hierarchy-based and the aggregation-based methods. We developed an R package belg as an open source tool for calculating Boltzmann entropy of landscape gradients. However, in the last several years, a number of methods for calculating Boltzmann entropy for landscape mosaics and gradients were proposed. As of recently, the application of Boltzmann entropy for landscape patterns was mostly limited to the conceptual discussion. Entropy is a fundamental concept in thermodynamics that is important in many fields, including image processing, neurobiology, urban planning, and sustainability.