Copula in Wildfire Analysis: A Systematic Literature Review

Mohamad Khoirun Najib, Sri Nurdiati, Ardhasena Sopaheluwakan



Copula model is a method that can be implemented in various study fields, including analyzing wildfires. The copula distribution function gives a simple way to define joint distribution between two or more random variables. This study aims to review the application of copula in the analysis of wildfires using a Systematic Literature Review (SLR) and provide insight into research opportunities related to the application in Indonesia. The results show there are very few articles using the copula model in the analysis of wildfires. However, the increasing number of article citations each year shows the importance of such article research and has contributed to wildfire analysis development. In that article, 50% of studies applied the copula model to direct wildfire analysis (using fire data) in Canada, Portugal, and the US. Meanwhile, the other 50% use the copula model for indirect wildfire analysis (not using fire data) in Canada and the European region. The outcome of the presented review will provide the latest research positions and future research opportunities on the application of copula in the analysis of wildfires in Indonesia.

Keywords: copula; wildfire; systematic literature review.



Model copula merupakan metode yang dapat diimplementasikan pada berbagai bidang penelitian, salah satunya pada analisis kebakaran hutan. Fungsi sebaran copula memberikan cara yang mudah untuk mendefinisikan sebaran peluang bersama antara dua peubah acak atau lebih. Tujuan penelitian ini mengulas penerapan model copula tersebut pada analisis kebakaran hutan dalam studi literatur menggunakan Systematic Literature Review (SLR) serta memberikan peluang riset ke depan terkait implementasinya pada analisis kebakaran hutan di Indonesia. Hasil penelitian menunjukkan bahwa model copula pada analisis kebakaran hutan masih sangat sedikit. Namun, peningkatan jumlah sitasi artikel tiap tahun menunjukkan pentingnya penelitian tersebut dan memiliki kontribusi pada perkembangan analisis kebakaran hutan. Pada artikel tersebut, sebanyak 50% penelitian menerapkan model copula pada analisis kebakaran secara langsung (menggunakan data kebakaran) di Kanada, Portugal, dan Amerika. Sementara, sebanyak 50% lainnya menerapkan model copula pada analisis kebakaran secara tak langsung (tidak menggunakan data kebakaran), yaitu di Kanada dan kawasan Eropa. Hasil tinjauan memberikan posisi riset terkini serta usulan riset ke depan mengenai penerapan model copula untuk analisis kebakaran hutan dan lahan di Indonesia.

Kata kunci: copula; kebakaran hutan; studi literatur sistematik.



copula; wildfire; systematic literature review.


E. Aflahah, R. Hidayati, and R. Hidayat, “Pendugaan hotspot sebagai indikator kebakaran hutan di Kalimantan berdasarkan faktor iklim,” J. Pengelolaan Sumberd. Alam dan Lingkung., vol. 9, no. 2, pp. 405–418, 2019, doi: 10.29244/jpsl.9.2.405-418.

MENLHK, “Rekapitulasi Luas Kebakaran Hutan dan Lahan (Ha) Per Provinsi Di Indonesia Tahun 2016-2021,” 2021. (accessed Aug. 11, 2021).

J. Miettinen, C. Shi, and S. C. Liew, “Fire Distribution in Peninsular Malaysia, Sumatra and Borneo in 2015 with Special Emphasis on Peatland Fires,” Environ. Manage., vol. 60, no. 4, pp. 747–757, 2017, doi: 10.1007/s00267-017-0911-7.

BMKG, “Climate Index for Suitability of Hotspots Occurence in ASEAN Regions,” 2021. (accessed Aug. 11, 2021).

S. Madadgar, M. Sadegh, F. Chiang, E. Ragno, and A. AghaKouchak, “Quantifying increased fire risk in California in response to different levels of warming and drying,” Stoch. Environ. Res. Risk Assess., vol. 34, no. 12, pp. 2023–2031, 2020, doi: 10.1007/s00477-020-01885-y.

C. Schölzel and P. Friederichs, “Multivariate non-normally distributed random variables in climate research - Introduction to the copula approach,” Nonlinear Process. Geophys., vol. 15, no. 5, pp. 761–772, 2008, doi: 10.5194/npg-15-761-2008.

K. Aas, “Pair-copula constructions for financial applications: A review,” Econometrics, vol. 4, no. 4, 2016, doi: 10.3390/econometrics4040043.

A. J. Patton, “A review of copula models for economic time series,” J. Multivar. Anal., vol. 110, pp. 4–18, 2012, doi: 10.1016/j.jmva.2012.02.021.

Z. Hao and V. P. Singh, “Review of dependence modeling in hydrology and water resources,” Prog. Phys. Geogr., vol. 40, no. 4, pp. 549–578, 2016, doi: 10.1177/0309133316632460.

F. D. Wihartiko, S. Nurdiati, A. Buono, and E. Santosa, “Blockchain dan Kecerdasan Buatan dalam Pertanian : Studi Literatur,” J. Teknol. Inf. dan Ilmu Komput., vol. 8, no. 1, p. 177, 2021, doi: 10.25126/jtiik.0814059.

Y. Xiao and M. Watson, “Guidance on Conducting a Systematic Literature Review,” J. Plan. Educ. Res., vol. 39, no. 1, pp. 93–112, 2019, doi: 10.1177/0739456X17723971.

R. Jane, L. Cadavid, J. Obeysekera, and T. Wahl, “Multivariate statistical modelling of the drivers of compound flood events in South Florida,” Nat. Hazards Earth Syst. Sci., pp. 1–30, 2020, doi: 10.5194/nhess-2020-82.

M. Sklar, “Fonctions de Répartition àn Dimensions et Leurs Marges,” Publ. L’Institut Stat. L’Université Paris, vol. 8, pp. 229–231, 1959.

P. Laux, S. Vogl, W. Qiu, H. R. Knoche, and H. Kunstmann, “Copula-based statistical refinement of precipitation in RCM simulations over complex terrain,” Hydrol. Earth Syst. Sci., vol. 15, no. 7, pp. 2401–2419, 2011, doi: 10.5194/hess-15-2401-2011.

R. B. Nelsen, An Introduction to Copulas. New York: Springer, 2006.

Z. Li, Q. Shao, Q. Tian, and L. Zhang, “Copula-based drought severity-area-frequency curve and its uncertainty, a case study of Heihe River basin, China,” Hydrol. Res., vol. 51, no. 5, pp. 867–881, 2020, doi: 10.2166/nh.2020.173.

X. Wei, H. Zhang, V. P. Singh, C. Dang, S. Shao, and Y. Wu, “Coincidence probability of streamflow in water resources area, water receiving area and impacted area: Implications for water supply risk and potential impact of water transfer,” Hydrol. Res., vol. 51, no. 5, pp. 1120–1135, 2020, doi: 10.2166/nh.2020.106.

F. A. A. Aldhufairi, R. G. M. Samanthi, and J. H. Sepanski, “New families of bivariate copulas via unit Lomax distortion,” Risks, vol. 8, no. 4, p. 106, 2020, doi: 10.3390/risks8040106.

C. Genest, A. C. Favre, J. Béliveau, and C. Jacques, “Metaelliptical copulas and their use in frequency analysis of multivariate hydrological data,” Water Resour. Res., vol. 43, no. 9, 2007, doi: 10.1029/2006WR005275.

Z. Hao and V. P. Singh, “Integrating entropy and copula theories for hydrologic modeling and analysis,” Entropy, vol. 17, no. 4, pp. 2253–2280, 2015, doi: 10.3390/e17042253.

O. Orcel, P. Sergent, and F. Ropert, “Trivariate copula to design coastal structures,” Nat. Hazards Earth Syst. Sci., vol. 21, no. 1, pp. 239–260, 2020, doi: 10.5194/nhess-2020-80.

D. Sirikanchanarak, J. Liu, S. Sriboonchitta, and J. Xie, “Analysis of transmission and co-movement of rice export prices between Thailand and Vietnam,” in Studies in Computational Intelligence, vol. 622, Cham: Springer, 2016, pp. 333–346.

L. Zhang and V. P. Singh, “Symmetric Archimedean Copulas,” in Copulas and their Applications in Water Resources Engineering, Cambridge University Press, 2019, pp. 123–171.

B. Yan and L. Chen, “Coincidence probability of precipitation for the middle route of South-to-North water transfer project in China,” J. Hydrol., vol. 499, pp. 19–26, 2013, doi: 10.1016/j.jhydrol.2013.06.040.

H. Du, Y. Wang, K. Liu, and L. Cheng, “Exceedance probability of precipitation for the Shuhe to Futuan Water Transfer Project in China,” Environ. Earth Sci., vol. 78, no. 7, pp. 1–12, 2019, doi: 10.1007/s12665-019-8207-2.

M. H. Afshar, A. U. Sorman, and M. T. Yilmaz, “Conditional copula-based spatial-temporal drought characteristics analysis-A case study over Turkey,” Water (Switzerland), vol. 8, no. 10, 2016, doi: 10.3390/w8100426.

M. H. Afshar, A. Ü. Şorman, F. Tosunoğlu, B. Bulut, M. T. Yilmaz, and A. Danandeh Mehr, “Climate change impact assessment on mild and extreme drought events using copulas over Ankara, Turkey,” Theor. Appl. Climatol., vol. 141, no. 3–4, pp. 1045–1055, 2020, doi: 10.1007/s00704-020-03257-6.

F. Tosunoğlu, G. Salvadori, and M. Yilmaz, “Multivariate assessment of low-flow hazards via copulas: The case study of the Çoruh basin (turkey),” Water (Switzerland), vol. 12, no. 10, 2020, doi: 10.3390/w12102848.

C. Manning, M. Widmann, E. Bevacqua, A. F. Van Loon, D. Maraun, and M. Vrac, “Soil moisture drought in Europe: A compound event of precipitation and potential evapotranspiration on multiple time scales,” J. Hydrometeorol., vol. 19, no. 8, pp. 1255–1271, 2018, doi: 10.1175/JHM-D-18-0017.1.

H. Singh, F. J. Pirani, and M. R. Najafi, “Characterizing the temperature and precipitation covariability over Canada,” Theor. Appl. Climatol., vol. 139, no. 3–4, pp. 1543–1558, 2020, doi: 10.1007/s00704-019-03062-w.

D. D. Z. Xi, C. B. Dean, and S. W. Taylor, “Modeling the duration and size of extended attack wildfires as dependent outcomes,” Environmetrics, vol. 31, no. 5, 2020, doi: 10.1002/env.2619.

A. Tilloy, B. Malamud, H. Winter, and A. Joly-Laugel, “Evaluating the efficacy of bivariate extreme modelling approaches for multi-hazard scenarios,” Nat. Hazards Earth Syst. Sci., pp. 1–39, 2020, doi: 10.5194/nhess-2020-28.

J. Zscheischler and E. M. Fischer, “The record-breaking compound hot and dry 2018 growing season in Germany,” Weather Clim. Extrem., vol. 29, 2020, doi: 10.1016/j.wace.2020.100270.

S. Nurdiati, A. Sopaheluwakan, and P. Septiawan, “Spatial and Temporal Analysis of El Niño Impact on Land and Forest Fire in Kalimantan and Sumatra,” Agromet, vol. 35, no. 1, pp. 1–10, 2021, doi: 10.29244/j.agromet.35.1.1-10.

S. Nurdiati, F. Bukhari, M. T. Julianto, M. K. Najib, and N. Nazria, “Heterogeneous Correlation Map Between Estimated ENSO And IOD From ERA5 And Hotspot In Indonesia,” Jambura Geosci. Rev., vol. 3, no. 2, pp. 65–72, 2021, doi: 10.34312/jgeosrev.v3i2.10443.

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DOI: 10.15408/inprime.v3i2.22131


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