**4. Conclusions**

In addition to exploring results obtained from case studies here presented, we intended to show why and how measures based on information entropy can contribute to understanding complexity of landscapes patterns and processes. As shown in the first example, He/Hmax, SDL, and LMC are complexity measures that represent useful tools for evaluating landscape patterns. He/Hmax allows identifying ordered and disordered targets, while SDL and LMC are related to intermediary heterogeneity patterns presented by landscape patches. Comparing the landscape metrics used here with the spectral decomposition methods proposed in Mustard and Sunshine [13], they prove to be quite efficient in comparing the complexity of the patterns of different patches as well as their variation over the entire landscape. Based on this example, the application of such metrics is proposed for multitemporal studies of landscape dynamics, for evaluating resilience and the degree of degradation of different fragments, for estimating the degree of the anthropic impact due to alterations on land usage, among other applications.

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In the second example, we highlight the use of these measures to evaluate complexity in climatic time series. Our future studies involve the application of these measures as alternatives for classical statistical analysis, using them to assess the influences of both natural processes, such as El Niño and La Niña, and those resulting from anthropic processes, such as the increase in temperature and frequency of extreme weather events, such as severe droughts and heavier rains.

## **Author details**

Sérgio Henrique Vannucchi Leme de Mattos<sup>1</sup> \*, Luiz Eduardo Vicente<sup>2</sup> , Andrea Koga Vicente<sup>2</sup> , Cláudio Bielenki Junior<sup>1</sup> , Maristella Cruz de Moraes<sup>1</sup> , Gabriele Luiza Cordeiro<sup>1</sup> and José Roberto Castilho Piqueira<sup>3</sup>

1 Environmental Complex Systems Laboratory, Department of Hydrobiology, Biological and Health Sciences Center, Federal University of São Carlos (UFSCar), São Carlos, SP, Brazil

2 ABC Platform, Embrapa Environment, Jaguariúna, SP, Brazil

3 Department of Telecommunications and Control Engineering, Polytechnic School of the University of Sao Paulo (USP), São Paulo, SP, Brazil

\*Address all correspondence to: sergiomattos@ufscar.br

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Metrics Based on Information Entropy to Evaluate Landscape Complexities DOI: http://dx.doi.org/10.5772/intechopen.96976*
