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Aggregation-based method for computing absolute Boltzmann entropy of landscape gradient with full thermodynamic consistency

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Abstract

Context

The second law of thermodynamics is a central organizing principle of nature, whose core concept, Boltzmann entropy, is fundamentally important in landscape ecology research. However, the use of this entropy has remained at a conceptual level in landscape ecology for one and a half centuries. It was not until very recently that methods were developed for computing the Boltzmann entropy of landscape gradients and mosaics.

Objectives

The aim of this study was to examine the computational method (i.e., resampling-based method) for landscape gradients. The first objective was to validate whether the Boltzmann entropy computed using this method was thermodynamically consistent (i.e., consistent with statistical thermodynamics). The second objective was to propose a different method for computing thermodynamically consistent entropy.

Methods

A kinetic-theory-based approach was proposed for testing the thermodynamic consistency of entropy. This approach was applied to both relative and absolute Boltzmann entropies by the resampling-based method, revealing that the absolute Boltzmann entropy is only partly consistent. Hypothesis-driven experiments were designed to determine the cause.

Results

The cause was demonstrated to be the generalization technique for generating the macrostate of a landscape gradient, which is called resampling. A different computational method was developed on the basis of an alternative technique (i.e., aggregation).

Conclusions

Validation of its thermodynamic consistency is necessary even if a “thermodynamic” entropy is computed strictly according to the formula. The entropy computed using the aggregation-based method passed the validation and is recommended to be used in linking landscape ecological processes with statistical thermodynamics.

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References

  • Boltzmann L (1872) Weitere Studien über das Wärmegleichgewicht unter Gasmolekülen [Further studies on the thermal equilibrium of gas molecules]. Sitzungsberichte Akademie der Wissenschaften 66:275–370

    Google Scholar 

  • Clausius R (1850) Über die bewegende Kraft der Wärme und die Gesetze, welche sich daraus für die Wärmelehre selbst ableiten lassen [On the moving force of heat, and the laws regarding the nature of heat itself which are deducible therefrom]. Ann Phys 79(4):368–397

    Article  Google Scholar 

  • Cushman SA (2015) Thermodynamics in landscape ecology: the importance of integrating measurement and modeling of landscape entropy. Landscape Ecol 30(1):7–10

    Article  Google Scholar 

  • Cushman SA (2016) Calculating the configurational entropy of a landscape mosaic. Landscape Ecol 31(3):481–489

    Article  Google Scholar 

  • Cushman SA (2018a) Calculation of configurational entropy in complex landscapes. Entropy 20(4):298

    Article  Google Scholar 

  • Cushman SA (2018b) Editorial: entropy in landscape ecology. Entropy 20(5):314

    Article  Google Scholar 

  • Dalarsson N, Dalarsson M, Golubovic L (2011) Introductory statistical thermodynamics. Academic Press, Amsterdam

    Google Scholar 

  • Díaz-Varela E, Roces-Díaz JV, Álvarez-Álvarez P (2016) Detection of landscape heterogeneity at multiple scales: use of the quadratic entropy index. Landsc Urban Plan 153:149–159

    Article  Google Scholar 

  • Forman RTT, Godron M (1986) Landscape ecology. John Wiley & Sons, New York

    Google Scholar 

  • Gao PC, Wang JC, Zhang H, Li ZL (2019) Boltzmann entropy-based unsupervised band selection for hyperspectral image classification. IEEE Geosci Remote Sens Lett 16(3):462–466

    Article  Google Scholar 

  • Gao PC, Zhang H, Li ZL (2017) A hierarchy-based solution to calculate the configurational entropy of landscape gradients. Landscape Ecol 32(6):1133–1146

    Google Scholar 

  • Gao PC, Zhang H, Li ZL (2018) An efficient analytical method for computing the Boltzmann entropy of a landscape gradient. Trans GIS 22(5):1046–1063

    Article  Google Scholar 

  • Gokcen NA, Reddy RG (2013) Thermodynamics. Springer, New York

    Google Scholar 

  • Guo DS (2010) Local entropy map: a nonparametric approach to detecting spatially varying multivariate relationships. Int J Geogr Inf Sci 24(9):1367–1389

    Article  Google Scholar 

  • Huang JY, Zhou QM, Wu ZF (2016) Delineating urban fringe area by land cover information entropy: an empirical study of Guangzhou-Foshan metropolitan area China. ISPRS Int J Geoinf 5(5):1–12

    Google Scholar 

  • Huettner DA (1976) Net energy analysis: an economic assessment. Science 192(4235):101–104

    Article  CAS  PubMed  Google Scholar 

  • Johnson GD, Myers WL, Patil GP, Taillie C (2001) Characterizing watershed-delineated landscapes in Pennsylvania using conditional entropy profiles. Landscape Ecol 16(7):597–610

    Article  Google Scholar 

  • Kaufman M (2002) Principles of thermodynamics. CRC Press, Boca Raton

    Book  Google Scholar 

  • Li ZL (2007) Algorithmic foundation of multi-scale spatial representation. CRC Press, Boca Raton

    Google Scholar 

  • McGarigal K, Cushman SA (2005) The gradient concept of landscape structure. In: Wiens JA, Moss MR (eds) Issues and perspectives in landscape ecology. Cambridge University Press, Cambridge

    Google Scholar 

  • Newman PW (1999) Sustainability and cities: extending the metabolism model. Landsc Urban Plan 44(4):219–226

    Article  Google Scholar 

  • Niu FQ, Zhu DH, Cheng CX (2006) Map information theories and adaptive visualization of electronic map in feature class-based zooming. In: Gong JY and Zhang JX (eds) Geoinformatics 2006: geospatial information science, Wuhan, China. Proceedings of SPIE, 28–29 Oct 2006 vol 6420. SPIE, Bellingham, WA, p 64200L

  • Nowosad J (2018) BELG: Boltzmann entropy of a landscape gradient. GitHub.io, https://r-spatialecology.github.io/belg/articles/belg1.html Accessed 11 Nov 2018

  • O’Neill RV, Johnson AR, King AW (1989) A hierarchical framework for the analysis of scale. Landscape Ecol 3(3):193–205

    Article  Google Scholar 

  • Phillips JD (2005) Entropy analysis of multiple scale causality and qualitative causal shifts in spatial systems. Prof Geogr 57(1):83–93

    Google Scholar 

  • Roy BN (2002) Fundamentals of classical and statistical thermodynamics. John Wiley & Sons, Hoboken

    Google Scholar 

  • Ruiz M, López F, Páez A (2012) Comparison of thematic maps using symbolic entropy. Int J Geogr Inf Sci 26(3):413–439

    Article  Google Scholar 

  • Serway RA, Jewett JW (2009) Physics for scientists and engineers with modern physics. Brooks/Cole Publishing Company, Pacific Grove

    Google Scholar 

  • Shannon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27(3):379–423

    Article  Google Scholar 

  • Sugihakim R, Alatas H (2016) Application of a Boltzmann-entropy-like concept in an agent-based multilane traffic model. Phys Lett A 380(1):147–155

    Article  CAS  Google Scholar 

  • Vranken I, Baudry J, Aubinet M, Visser M, Bogaert J (2015) A review on the use of entropy in landscape ecology: heterogeneity, unpredictability, scale dependence and their links with thermodynamics. Landscape Ecol 30(1):51–65

    Article  Google Scholar 

  • Wu JG (2006) Landscape ecology, cross-disciplinarity, and sustainability science. Landscape Ecol 21:1–4

    Article  CAS  Google Scholar 

  • Wu JG (2013) Key concepts and research topics in landscape ecology revisited: 30 years after the Allerton Park workshop. Landscape Ecol 28(1):1–11

    Article  CAS  Google Scholar 

  • Zaccarelli N, Li BL, Petrosillo I, Zurlini G (2013) Order and disorder in ecological time-series: introducing normalized spectral entropy. Ecol Ind 28:22–30

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by the Research Grants Council of Hong Kong (No. PolyU 152219/18E). The first author is also supported in part by National Natural Science Foundation of China (No. 41771537), National Key Research and Development Plan of China (No. 2017YFB0504102), and the high-performance computing service from the Center for Geodata and Analysis, Faculty of Geographical Science, Beijing Normal University.

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Correspondence to Zhilin Li.

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Gao, P., Li, Z. Aggregation-based method for computing absolute Boltzmann entropy of landscape gradient with full thermodynamic consistency. Landscape Ecol 34, 1837–1847 (2019). https://doi.org/10.1007/s10980-019-00854-3

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