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Fire Technology
Erschienen in: Fire Technology 1/2024

17.10.2023

Fractal and Spectral Analysis of Recent Wildfire Scars in Greece

verfasst von: Iulian-Alin Rosu, Manolis Grillakis, Athanasios Papadopoulos, Maricel Agop, Apostolos Voulgarakis

Erschienen in: Fire Technology | Ausgabe 1/2024

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Abstract

Fire plays an important role in the complex physical interactions between the processes which define our planet’s environments, and wildfires are considered to have a negative and unwanted effect, owing to the destruction of ecosystems and property that they often produce. In this paper, fractal and spectral methods are used to analyze the spatial characteristics of four wildfire scars of recent wildfires in the area of Greece. The fractal dimension, spatial noise and Hurst exponent of each of the chosen wildfire scar boundaries are calculated, and the results are discussed in connection to the real features of the wildfires. The results indicate that the fractal dimension can be used to adjust the fire line length by accounting for inherent roughness in the scar boundary, to define one of two types of propagation patterns that a wildfire exhibited, and to estimate the viability of plant recolonization in the wildfire area—furthermore, wildfire boundary spatial noise has been found to manifest similarities with pink noise, which is supported by the Hurst exponent analysis. The objective is to exemplify the effectiveness of such techniques for analyzing various characteristics of wildfire scars and active wildfires such as propagation patterns, fractality and spatial unpredictability, and for the qualitative determination of wildfire-related environmental factors.
Vorheriger Artikel An Improved YOLOv5s Fire Detection Model
Nächster Artikel Socio-spatial Inequities of Fire and Rescue Services in Sweden: An Analysis of Real and Estimated Response Times

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Literatur
1.
Chandler C, Cheney P, Thomas P, Trabaud L, Williams D (1983) Fire in forestry, Volume 1: forest fire behavior and effects, Volume 2: Forest fire management and organization. John Wiley & Sons, Inc
2.
Pyne SJ (1984) Introduction to wildland fire: fire management in the United States. John Wiley & Sons
3.
Johnson EA, Johnson EA (1996) Fire and vegetation dynamics: studies from the North American boreal forest. Cambridge University Press
4.
Mangeon S, Voulgarakis A, Gilham R, Harper A, Sitch S, Folberth G (2016) INFERNO: a fire and emissions scheme for the UK met office’s Unified model. Geosci Model Dev 9(8):2685–2700CrossRef
5.
Wang D, Guan D, Zhu S, Kinnon MM, Geng G, Zhang Q et al (2021) Economic footprint of California wildfires in 2018. Nat Sustain 4(3):252–260CrossRef
6.
Reid CE, Brauer M, Johnston FH, Jerrett M, Balmes JR, Elliott CT (2016) Critical review of health impacts of wildfire smoke exposure. Environ Health Perspect 124(9):1334–1343CrossRef
7.
Voulgarakis A, Field RD (2015) Fire influences on atmospheric composition, air quality and climate. Curr Pollut Rep 1(2):70–81CrossRef
8.
Lasslop G, Coppola AI, Voulgarakis A, Yue C, Veraverbeke S (2019) Influence of fire on the carbon cycle and climate. Curr Clim Change Rep 5(2):112–123CrossRef
9.
Navarro G, Caballero I, Silva G, Parra PC, Vázquez Á, Caldeira R (2017) Evaluation of forest fire on Madeira Island using Sentinel-2A MSI imagery. Int J Appl Earth Obs Geoinf 58:97–106
10.
Filipponi F (2019) Exploitation of sentinel-2 time series to map burned areas at the national level: a case study on the 2017 Italy wildfires. Remote Sensing 11(6):622CrossRef
11.
De Santis A, Chuvieco E (2007) Burn severity estimation from remotely sensed data: performance of simulation versus empirical models. Remote Sens Environ 108(4):422–435CrossRef
12.
Mac Kay G, Jan N (1984) Forest fires as critical phenomena. J Phys A 17:L757–L760CrossRef
13.
Mohajane M, Costache R, Karimi F, Pham QB, Essahlaoui A, Nguyen H et al (2021) Application of remote sensing and machine learning algorithms for forest fire mapping in a Mediterranean area. Ecol Indic 129:107869CrossRef
14.
Hazewinkel M, ed. (2001) [1994] Lebesgue dimension. In: Encyclopedia of mathematics. Springer Science Business Media B.V./Kluwer Academic Publishers
15.
Mandelbrot BB (1983) The fractal geometry of nature, vol 173. WH Freeman, New York, p 51
16.
17.
Gouyet JF (1996) Physics and fractal structures. Springer Verlag
18.
Brothers HJ (2007) Structural scaling in Bach’s cello suite no. 3. Fractals 15(01):89–95CrossRef
19.
Tan CO, Cohen MA, Eckberg DL, Taylor JA (2009) Fractal properties of human heart period variability: physiological and methodological implications. J Physiol 587(15):3929–3941CrossRef
20.
Hu S, Cheng Q, Wang L, Xie S (2012) Multifractal characterization of urban residential land price in space and time. Appl Geogr 34:161–170CrossRef
21.
Taylor RP, Micolich AP, Jonas D (2006) Revisiting Pollock’s drip paintings (Reply). Nature 444(7119):E10–E11CrossRef
22.
Johnson GD, Tempelman A, Patil GP (1995) Fractal based methods in ecology: a review for analysis at multiple spatial scales. Coenoses 10:123–131
23.
Drossel B, Schwabl F (1992) Self-organized critical forest-fire model. Phys Rev Lett 69:1629–1632CrossRef
24.
Sahimi H (1994) Applications of percolation theory. Taylor and Francis, LondonCrossRef
25.
Bakhshaii A, Johnson EA (2019) A review of a new generation of wildfire–atmosphere modeling. Can J For Res 49(6):565–574CrossRef
26.
Caldarelli G, Frondoni R, Gabrielli A, Montuori M, Retzlaff R, Ricotta C (2001) Percolation in real wildfires. Europhys Lett 56(4):510CrossRef
27.
Kuramoto Y (1978) Diffusion-induced chaos in reaction systems. Prog Theor Phys Suppl 64:346–367CrossRef
28.
Sivashinsky GI (1977) Nonlinear analysis of hydrodynamic instability in laminar flames—I: derivation of basic equations. Acta Astronaut 4(11):1177–1206MathSciNetCrossRef
29.
Linan A (1974) The asymptotic structure of counterflow diffusion flames for large activation energies. Acta Astronaut 1(7–8):1007–1039CrossRef
30.
Watson N, Morgan G, Rolland D (1983) The bright plantation fire, November 1982: Australian forests commission, Victoria. Rep. 19
31.
McAlpine RS, Wotton BM (1993) The use of fractal dimension to improve wildland fire perimeter predictions. Can J For Res 23(6):1073–1077CrossRef
32.
Ricotta C, Retzlaff R (2000) Self-similar spatial clustering of wildland fires: the example of a large wildfire in Spain. Int J Remote Sens 21(10):2113–2118CrossRef
33.
Litton CD, Perera IE (2014) Modeling the optical properties of combustion-generated fractal aggregates. Fuel 130:215–220CrossRef
34.
Barr BW, Ezekoye OA (2013) Thermo-mechanical modeling of firebrand breakage on a fractal tree. Proc Combust Inst 34(2):2649–2656CrossRef
35.
Jun F, Xueming S, Hongyong Y, Xin Z (2004) Self-preserving size distribution of fire soot fractal coagulation in flaming combustion. J Fire Sci 22(1):53–68CrossRef
36.
Bak P, Tang C, Wiesenfeld K (1987) Self-organized criticality: an explanation of the 1/f noise. Phys Rev Lett 59(4):381CrossRef
37.
O’Brien KP, Weissman MB (1992) Statistical signatures of self-organization. Phys Rev A 46(8):R4475CrossRef
38.
Press WH (1978) Flicker noises in astronomy and elsewhere. Comments Astrophys 7:103–119
39.
Handel PH, Chung AL (1993) Noise in physical systems and 1/f fluctuations (No. CONF-930866-). AIP, New York
40.
Adak O, Rosenthal E, Meisner J, Andrade EF, Pasupathy AN, Nuckolls C et al (2015) Flicker noise as a probe of electronic interaction at metal–single molecule interfaces. Nano Lett 15(6):4143–4149CrossRef
41.
Field DJ (1987) Relations between the statistics of natural images and the response properties of cortical cells. Josa a 4(12):2379–2394CrossRef
42.
Bassingthwaighte JB, Liebovitch LS, West BJ (1994) Fractal physiology. Oxford University Press, New YorkCrossRef
43.
Jensen HJ (1998) Self-organized criticality. Cambridge University Press, CambridgeCrossRef
44.
Van Orden GC, Holden JG, Turvey MT (2003) Self-organization of cognitive performance. J Exp Psychol Gen 132:331–350CrossRef
45.
Moon W, Agarwal S, Wettlaufer JS (2018) Intrinsic pink-noise multidecadal global climate dynamics mode. Phys Rev Lett 121(10):108701CrossRef
46.
Ovchinnikov IV (2016) Introduction to supersymmetric theory of stochastics. Entropy 18(4):108CrossRef
47.
Bonabeau E, Theraulaz G, Dorigo M, Theraulaz G, Marco DDRDF (1999) Swarm intelligence: from natural to artificial systems (No. 1). Oxford University PressCrossRef
48.
Tarnopolski M (2016) On the relationship between the Hurst exponent, the ratio of the mean square successive difference to the variance, and the number of turning points. Physica A 461:662–673CrossRef
49.
Xavier Viegas D (1998) Forest fire propagation. Phil Trans R Soc Lond Ser A 356(1748):2907–2928CrossRef
50.
Williams FA (1982) Urban and wildland fire phenomenology. Prog Energy Combust Sci 8(4):317–354CrossRef
51.
Chigier N (1981) Energy, combustion and environment. McGraw-Hill, New York
52.
Drysdale D (1992) An introduction to fire dynamics. Wiley, Chichester
53.
Telesca L, Song W (2011) Time-scaling properties of city fires. Chaos, Solitons Fractals 44(7):558–568CrossRef
54.
Hurst HE (1951) Long-term storage capacity of reservoirs. Trans Am Soc Civ Eng 116(1):770–799CrossRef
55.
Hurst HE, Black RP, Simaika YM (1965) Long-term storage: an experimental study. Constable, London
56.
Ba R, Song W, Lovallo M, Lo S, Telesca L (2020) Analysis of multifractal and organization/order structure in Suomi-NPP VIIRS normalized difference vegetation index series of wildfire affected and unaffected sites by using the multifractal detrended fluctuation analysis and the Fisher-Shannon analysis. Entropy 22(4):415CrossRef
57.
Lu J, Zhou T, Li B, Wu C (2018) Scale analysis and correlation study of wildfire and the meteorological factors that influence it. Math Prob Eng 2018:1–10
58.
de Benicio RB, Stošić T, De Figueirêdo PH, Stošić BD (2013) Multifractal behavior of wild-land and forest fire time series in Brazil. Physica A 392(24):6367–6374CrossRef
59.
Kenkel NC, Walker DJ (1996) Fractals in the biological sciences. Coenoses: 77–100
60.
Leonard SW, Bennett AF, Clarke MF (2014) Determinants of the occurrence of unburnt forest patches: potential biotic refuges within a large, intense wildfire in south-eastern Australia. For Ecol Manage 314:85–93CrossRef
61.
62.
Saberi AA (2011) Fractal structure of a three-dimensional Brownian motion on an attractive plane. Phys Rev E 84(2):021113CrossRef
63.
Millers S, Childers D (2012) Probability and random processes. Academic Press, p 373
64.
Falconer K (2004) Fractal geometry: mathematical foundations and applications. John Wiley & Sons
65.
66.
Balabana E, Lub S (2018) Color of noise: comparative analysis of sub-periodic variation in empirical Hurst exponent across foreign currency changes and their pairwise differences
67.
Schroeder M (2009) Fractals, chaos, power laws: minutes from an infinite paradise. Courier Corporation
68.
Alhagyan M (2022) The effects of incorporating memory and stochastic volatility into GBM to forecast exchange rates of Euro. Alex Eng J 61(12):9601–9608CrossRef
69.
Akhrif A, Romanos M, Domschke K, Schmitt-Boehrer A, Neufang S (2018) Fractal analysis of BOLD time series in a network associated with waiting impulsivity. Front Physiol 9:1378CrossRef
70.
Struik DJ (2014) A source book in mathematics, 1200–1800, vol 445. Princeton University Press
71.
72.
73.
74.
75.
76.
77.
© European Union, Copernicus Land Monitoring Service 2018, European Environment Agency (EEA)
78.
79.
© Meteostat, weather and climate database, weather data provided by NOAA, Deutscher Wetterdienst and environment Canada, data available under CC-BY-NC-4.0 and WMO resolution 40. https://​meteostat.​net/​en/​
80.
Ministerio de Agricultura y Pesca Alimentación y Medio Ambiente (MAPAMA) Estadística General de Incendios Forestales. Memoria 2017, 32
81.
Camia A, Durrant T, San-Miguel Ayanz J (2013) Harmonized classification scheme of fire causes in the EU adopted for the European fire database of EFFIS. Scientific and Technical Research Report for UN, Luxemburg
82.
Kuznetsov GV, Baranovskiy NV (2013) Focused sun’s rays and forest fire danger: new concept. In Remote sensing of clouds and the atmosphere XVIII; and optics in atmospheric propagation and adaptive systems XVI (Vol. 8890). SPIE, pp. 286–291.
Metadaten
Titel
Fractal and Spectral Analysis of Recent Wildfire Scars in Greece
verfasst von
Iulian-Alin Rosu
Manolis Grillakis
Athanasios Papadopoulos
Maricel Agop
Apostolos Voulgarakis
Publikationsdatum
17.10.2023
Verlag
Springer US
Erschienen in
Fire Technology / Ausgabe 1/2024
Print ISSN: 0015-2684
Elektronische ISSN: 1572-8099
DOI
https://doi.org/10.1007/s10694-023-01497-2

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