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Technical Brief

Computational Analysis of the U.S. Forest Fires

[+] Author and Article Information
António M. Lopes

UISPA-LAETA/INEGI,
Faculty of Engineering,
University of Porto,
Rua Dr. Roberto Frias,
Porto 4200-465, Portugal
e-mail: aml@fe.up.pt

J. A. Tenreiro Machado

Department of Electrical Engineering,
Institute of Engineering,
Polytechnic of Porto,
R. Dr. António Bernardino de Almeida, 431,
Porto 4249-015, Portugal
e-mail: jtm@isep.ipp.pt

1Corresponding author.

Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTATIONAL AND NONLINEAR DYNAMICS. Manuscript received June 29, 2016; final manuscript received December 28, 2016; published online January 24, 2017. Assoc. Editor: Bogdan I. Epureanu.

J. Comput. Nonlinear Dynam 12(4), 044503 (Jan 24, 2017) (5 pages) Paper No: CND-16-1311; doi: 10.1115/1.4035672 History: Received June 29, 2016; Revised December 28, 2016

This paper analyses forest fires (FF) in the U.S. during 1984–2013, based on data collected by the monitoring trends in burn severity (MTBS) project. The study adopts the tools of dynamical systems to tackle information about space, time, and size. Computational visualization methods are used for reducing the information dimensionality and to unveil the relationships embedded in the data.

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Figures

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Fig. 1

Voronoi tessellation for K = 20 and geographical location of the events (dots) for the period 1984–2013

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Fig. 2

Cross-correlation functions between FF and weather variables temperature rT (smooth line) and precipitation rP (noisy line) versus time delay, for cell V1, during period 1984–2013

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Fig. 3

Time delays for the maximum cross correlation between FF and temperature τT (top values) and FF and precipitation τP (bottom values) for the 20 Voronoi cells

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Fig. 4

Characterization of cell V1: FF data series x1(t) (bottom line); entropy s1(k) for α = 0.7 (top line)

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Fig. 5

The three-dim MDS map for the Canberra index Cij

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Fig. 6

Assessing the quality of the MDS for the Canberra index Cij: (a) Shepard plot for the three-dim plot and (b) stress plot

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Fig. 7

The three-dim MDS map with the superimposed object, for the Canberra index Cij

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Fig. 8

Original series, si(k) (filled circles), model ŝi(k) (continuous line), and forecast values (nonfilled circles), for the period 1984–2018 and clusters: (a) A and (b) B

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Fig. 9

Original series, s1(k) (filled circles), model ŝ1(k) (continuous line), and forecast values (nonfilled circles) for cell V1 and period 1984–2018

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