Free Standard AU & NZ Shipping For All Book Orders Over $80!
Register      Login
International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE (Open Access)

Mesoscale spatiotemporal predictive models of daily human- and lightning-caused wildland fire occurrence in British Columbia

Khurram Nadeem A * , S. W. Taylor B E * , Douglas G. Woolford C and C. B. Dean D
+ Author Affiliations
- Author Affiliations

A University of Guelph, 50 Stone Road E, Guelph, ON N1G 2W1, Canada.

B Pacific Forestry Centre, Natural Resources Canada, 506 West Burnside Road, Victoria, BC V8Z 1M5, Canada.

C University of Western Ontario,1151 Richmond Street, London, ON N6A 3K7, Canada.

D University of Waterloo, 200 University Avenue W, Waterloo, ON N2L 3G1, Canada.

E Corresponding author. Email: steve.taylor@canada.ca

International Journal of Wildland Fire 29(1) 11-27 https://doi.org/10.1071/WF19058
Submitted: 9 April 2019  Accepted: 16 October 2019   Published: 24 December 2019

Journal Compilation © IAWF 2020 Open Access CC BY-NC-ND

Abstract

We developed three models of daily human- and lightning-caused fire occurrence to support fire management preparedness and detection planning in the province of British Columbia, Canada, using a lasso-logistic framework. Novel aspects of our work involve (1) using an ensemble of models that were created using 500 datasets balanced (through response-selective sampling) to have equal numbers of fire and non-fire observations; (2) the use of a new ranking algorithm to address the difficulty in interpreting variable importance in models with a large number of covariates. We also introduce the use of cause-specific average spatial daily fire occurrence, termed baseline risk, as a covariate for missing or poorly estimated factors that influence human and lightning fire occurrence. All three models have strong predictive ability, with areas under the Receiver Operator Characteristic curve exceeding 0.9.

Additional keywords: fire danger, fire occurrence modelling.


References

Alexander GW (1927) Lightning storms and forest fires in the state of Washington. Monthly Weather Review 55, 122–129.
Lightning storms and forest fires in the state of Washington.Crossref | GoogleScholarGoogle Scholar |

Beall HW (1934) A practical test of the accuracy of forest-fire hazard charts. Forestry Chronicle 10, 56–65.
A practical test of the accuracy of forest-fire hazard charts.Crossref | GoogleScholarGoogle Scholar |

Beaudoin A, Bernier PY, Guindon L, Villemaire P, Guo XJ, Stinson G, Bergeron T, Magnussen S, Hall RJ (2014) Mapping attributes of Canada’s forests at moderate resolution through kNN and MODIS imagery. Canadian Journal of Forest Research 44, 521–532.
Mapping attributes of Canada’s forests at moderate resolution through kNN and MODIS imagery.Crossref | GoogleScholarGoogle Scholar |

Beverly JL, Wotton BM (2007) Modelling the probability of sustained flaming: predictive value of fire weather index components compared with observations of site weather and fuel moisture conditions. International Journal of Wildland Fire 16, 161–173.
Modelling the probability of sustained flaming: predictive value of fire weather index components compared with observations of site weather and fuel moisture conditions.Crossref | GoogleScholarGoogle Scholar |

Brillinger DR, Preisler HK, Benoit JW (2003) Risk assessment: a forest fire example. In ‘Statistics and science: a Festschrift for Terry Speed’. pp. 177–196, Vol. 40 of IMS Lecture Notes Monograph Series, DR Goldstein, (ed), (Institute of Mathematical Statistics: Beachwood, OH, USA)10.1214/LNMS/1215091142.10.1214/LNMS/1215091142

Bruce D (1963) How many fires? Fire Control Notes 24, 45–51.

Burrows WR, King P, Lewis PJ, Kochtubajda B, Snyder B, Turcotte V (2002) Lightning occurrence patterns over Canada and adjacent United States from lightning detection network observations. Atmosphere-ocean 40, 59–80.
Lightning occurrence patterns over Canada and adjacent United States from lightning detection network observations.Crossref | GoogleScholarGoogle Scholar |

Byon E, Shrivastava AK, Ding Y (2010) A classification procedure for highly imbalanced class sizes. IIE Transactions 42, 288–303.
A classification procedure for highly imbalanced class sizes.Crossref | GoogleScholarGoogle Scholar |

Camp PE, Krawchuk MA (2017) Spatially varying constraints of human-caused fire occurrence in BC, Canada. International Journal of Wildland Fire 26, 219–229.
Spatially varying constraints of human-caused fire occurrence in BC, Canada.Crossref | GoogleScholarGoogle Scholar |

Chen C, Liaw A, Breiman L (2004) Using random forest to learn imbalanced data. Technical report #666, Department of Statistics, University of California. (Berkeley, CA, USA).

Costafreda-Aumedes S, Comas C, Vega-Garcia C (2017) Human-caused fire occurrence modelling in perspective: a review. International Journal of Wildland Fire 26, 983–998.
Human-caused fire occurrence modelling in perspective: a review.Crossref | GoogleScholarGoogle Scholar |

Crosby JS (1954) Probability of fire occurrence can be predicted. USDA Forest Service, Central States Forest Experiment Station, Technical Paper 143. (Columbus, OH, USA)

Cunningham AA, Martell DL (1973) A stochastic model for the occurrence of man-caused forest fires. Canadian Journal of Forest Research 3, 282–287.
A stochastic model for the occurrence of man-caused forest fires.Crossref | GoogleScholarGoogle Scholar |

De Smith MJ, Goodchild MF, Longley PA (2015) ‘Geospatial analysis’, 5th edn. (Matador: Leicester, UK)

Deville P, Linard C, Martin S, Gilbert M, Stevens FR, Gaughan A, Blondel VD, Tatem AJ (2014) Dynamic population mapping using mobile phone data. Proceedings of the National Academy of Sciences of the United States of America 111, 15888–15893.
Dynamic population mapping using mobile phone data.Crossref | GoogleScholarGoogle Scholar | 25349388PubMed |

Dockendorff D, Spring K (2005) The Canadian Lightning Detection Network – Novel approaches for performance measurement and network management. In ‘WMO technical conference on instruments and methods of observation (TECO-2005)’, 4–7 May 2005, Bucharest, Romania. pp. 62–67, Instruments and Observing Methods, Report No. 82. (World Meteorological Organization: Geneva, Switzerland)

Friedman J, Hastie T, Tibshirani R (2010) Regularization paths for generalized linear models via coordinate descent. Journal of Statistical Software 33, 1–22.
Regularization paths for generalized linear models via coordinate descent.Crossref | GoogleScholarGoogle Scholar | 20808728PubMed |

Gilbert DE, Zala C (1987) A reliability study of the lightning-locating network in BC. Canadian Journal of Forest Research 17, 1060–1065.
A reliability study of the lightning-locating network in BC.Crossref | GoogleScholarGoogle Scholar |

Gillis MD, Omule AY, Brierley T (2005) Monitoring Canada’s forests: the National Forest Inventory. Forestry Chronicle 81, 214–221.
Monitoring Canada’s forests: the National Forest Inventory.Crossref | GoogleScholarGoogle Scholar |

Haixiang G, Yijing L, Shang J, Mingyun G, Yuanyue H, Bing G (2017) Learning from class-imbalanced data: review of methods and applications. Expert Systems with Applications 73, 220–239.
Learning from class-imbalanced data: review of methods and applications.Crossref | GoogleScholarGoogle Scholar |

Hand DJ (2012) Assessing the performance of classification methods. International Statistical Review 80, 400–414.
Assessing the performance of classification methods.Crossref | GoogleScholarGoogle Scholar |

Hardy CC, Hardy CE (2007) Fire danger rating in the United States of America: an evolution since 1916. International Journal of Wildland Fire 16, 217–231.
Fire danger rating in the United States of America: an evolution since 1916.Crossref | GoogleScholarGoogle Scholar |

Hornby LG (1936) Fire control planning in the northern Rocky Mountain region. USDA Forest Service, Northern Rocky Mountain Forest and Range Experiment Station. (Missoula, MT, USA).

Hosmer DW, Lemeshow S (2000) ‘Applied logistic regression’, 2nd edn. (Wiley: New York, NY, USA).

Jackson AW (1968) Weather forecasting applied to forest fire protection in BC. Canadian Department of Transportation Meteorological Branch, Technical Memorandum Tec-693. (Ottawa, ON, Canada).

Janz B, Nimchuk N (1985) The 500 mb anomaly chart: a useful fire management tool. In ‘8th conference on fire and forest meteorology’, 29 April–2 May, 1985, Detroit, MI. (Eds LR Donoghue, RE Martin) pp. 233–238. (Society of American Foresters: Bethesda, MD, USA).

Johnston LM, Flannigan MD (2018) Mapping Canadian wildland fire interface areas. International Journal of Wildland Fire 27, 1–14.
Mapping Canadian wildland fire interface areas.Crossref | GoogleScholarGoogle Scholar |

Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y (1996) The NCEP/NCAR 40-year reanalysis project. Bulletin of the American Meteorological Society 77, 437–472.
The NCEP/NCAR 40-year reanalysis project.Crossref | GoogleScholarGoogle Scholar |

Latham D, Williams E (2001) Lightning and forest fires. In ‘Forest fires’. (Eds EA Johnson, K Miyanishi) pp. 375–418. (Academic Press: San Diego, CA, USA).

Lawson BD, Armitage OB (1997) Ignition probability equations for some Canadian fuel types. Report to the Canadian Committee on Forest Fire Management. Ember Research Services Ltd. (Victoria, BC, Canada).

Lawson BD, Armitage OB (2008) Weather guide for the Canadian Forest Fire Danger Rating System. Canadian Forest Service, Northern Forestry Centre. (Edmonton, AB, Canada).

Lee BS, Alexander ME, Hawkes BC, Lynham TJ, Stocks BJ, Englefield P (2002) Information systems in support of wildland fire management decision making in Canada. Computers and Electronics in Agriculture 37, 185–198.
Information systems in support of wildland fire management decision making in Canada.Crossref | GoogleScholarGoogle Scholar |

Lee S, Lee H, Abeel P, Ng A (2006) Efficient L1 – regularized logistic regression. In ‘Proceedings of the 21st national conference on artificial intelligence (AAAI-06)’, 16–20 July, Boston, MA. AAAI-06, pp. 401–408. A Cohn (ed), (American Association for Artificial Intelligence Press, Palo Alto, CA).

Magnussen S, Taylor SW (2012) Prediction of daily lightning-and human-caused fires in BC. International Journal of Wildland Fire 21, 342–356.
Prediction of daily lightning-and human-caused fires in BC.Crossref | GoogleScholarGoogle Scholar |

Melrose GP, Holmgren W (1932) Lightning and forest fires in the southern interior region of BC. Forestry Chronicle 8, 158–170.
Lightning and forest fires in the southern interior region of BC.Crossref | GoogleScholarGoogle Scholar |

Mesinger F, DiMego G, Kalnay E, Mitchell K (2006) North American regional reanalysis. Bulletin of the American Meteorological Society 87, 343–360.
North American regional reanalysis.Crossref | GoogleScholarGoogle Scholar |

Meyn A, Schmidtlein S, Taylor SW, Girardin MP, Thonicke K, Cramer W (2010) Spatial variation of trends in wildfire and summer drought in BC, Canada, 1920–2000. International Journal of Wildland Fire 19, 272–283.
Spatial variation of trends in wildfire and summer drought in BC, Canada, 1920–2000.Crossref | GoogleScholarGoogle Scholar |

Mills GA, McCaw L (2010) Atmospheric stability environments and fire weather in Australia – extending the Haines Index. CAWCR Technical Report No. 20. (CSIRO and the Bureau of Meteorology, Melbourne, Vic., Australia).

Moore RD, Spittlehouse DL, Whitfield PH, Stahl K (2010) Weather and climate. In ‘Compendium of forest hydrology and geomorphology in BC’. (Eds RG Pike, TE Redding, RD Moore, RD Winkler, KD Bladon) pp. 47–84. (BC Ministry of Forests and Range, Research Branch and FORREX Forest Research Extension Partnership: Victoria and Kamloops, BC, Canada).

Nimchuk N (1983) Wildfire behavior associated with upper ridge breakdown. Alberta Ministry of Energy and Natural Resources, Forest Service, ENR Report T/50. (Edmonton, AB, Canada).

Noble DV (1926) Relative humidity and the incidence of forest fires. American Meteorological Society Bulletin 7, 74–77.

Noggle RC, Krider EP, Vance DL, Barker KB (1976) A lightning direction finding system for forest fire detection. In ‘The 4th national conference fire and forest meteorology’, 16–18 November 1976, St Louis, MO. (Eds DH Baker, MA Fosberg) USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, General Technical Report RM-32, pp. 31–36. (Fort Collins, CO, USA).

Nychka D, Furrer R, Paige J, Sain S (2017) R package ‘fields’ version 9.6: Tools for spatial data. Available at https://www.rdocumentation.org/packages/fields/versions/9.6 (Verified 12 November 2019)10.5065/D6W957CT

Preisler HK, Westerling AL (2007) Statistical model for forecasting monthly large wildfire events in western United States. Journal of Applied Meteorology and Climatology 46, 1020–1030.
Statistical model for forecasting monthly large wildfire events in western United States.Crossref | GoogleScholarGoogle Scholar |

Preisler HK, Brillinger DR, Burgan RE, Benoit JW (2004) Probability-based models for estimation of wildfire risk. International Journal of Wildland Fire 13, 133–142.
Probability-based models for estimation of wildfire risk.Crossref | GoogleScholarGoogle Scholar |

Preisler HK, Burgan RE, Eidenshink JC, Klaver JM, Klaver RW (2009) Forecasting distributions of large federal-lands fires utilizing satellite and gridded weather information. International Journal of Wildland Fire 18, 508–516.
Forecasting distributions of large federal-lands fires utilizing satellite and gridded weather information.Crossref | GoogleScholarGoogle Scholar |

Saari E (1923) Kuloista etupäässä Suomen vationmetsiä silmällä pitäen (Forest fires in Finland with special reference to the state forest. Statistical investigation). Acta Forestalia Fennica 26, 1–143.

Schoenberg FP (2016) A note on the consistent estimation of spatial-temporal point process parameters. Statistica Sinica 2, 861–879.
A note on the consistent estimation of spatial-temporal point process parameters.Crossref | GoogleScholarGoogle Scholar |

Show SB, Kotok EI (1923) Forest fires in California 1911–1920 – An analytical study. Department Circular 243. USDA. (Washington, DC, USA).

Simard AJ, Valenzuela J (1972) A climatological summary of the Canadian Forest Fire Weather Index. Canada Department of the Environment, Canadian Forestry Service, Forest Fire Research Institute, Information Report Number FF-X-34. (Ottawa, ON, Canada).

Stahl K, Moore RD, McKendry IG (2006) The role of synoptic-scale circulation in the linkage between large-scale ocean atmosphere indices and winter surface climate in British Columbia, Canada. International Journal of Climatology 26, 541–560.
The role of synoptic-scale circulation in the linkage between large-scale ocean atmosphere indices and winter surface climate in British Columbia, Canada.Crossref | GoogleScholarGoogle Scholar |

Statistics Canada (2012) GeoSuite, reference guide. Census year 2011. Ministry of Industry, Statistics Canada, Catalogue no. 92–150-G. (Ottawa, ON, Canada).

Statistics Canada (2015) Road network file, reference guide. Ministry of Industry, Statistics Canada, Catalogue no. 92–500-G. (Ottawa, ON, Canada).

Stull R (2015) ‘Practical meteorology: an algebra-based survey of atmospheric science.’ (University of BC: Vancouver, BC, Canada).

Taylor SW, Alexander ME (2006) Science, technology, and human factors in fire danger rating: the Canadian experience. International Journal of Wildland Fire 15, 121–135.
Science, technology, and human factors in fire danger rating: the Canadian experience.Crossref | GoogleScholarGoogle Scholar |

Taylor SW, Woolford DG, Dean CB, Martell DL (2013) Wildfire prediction to inform management: statistical science challenges. Statistical Science 28, 586–615.
Wildfire prediction to inform management: statistical science challenges.Crossref | GoogleScholarGoogle Scholar |

Tibshirani R (1996) Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society. Series B. Methodological 58, 267–288.
Regression shrinkage and selection via the lasso.Crossref | GoogleScholarGoogle Scholar |

Toth Z, Desmarais J-G, Brunet G, Zhu Y, Verret R, Wobus R, Hogue R, Cui B (2005) The North American Ensemble Forecast System (NAEFS). Geophysical Research Abstracts 7, 02501

Van Wagner CE (1987) Development and structure of the Canadian Forest Fire Weather Index System. Canadian Forestry Service, Forest Technology Report 35. (Ottawa, ON, Canada)

Vermote E, Justice C, Csiszar I, Eidenshink J, Myneni R, Baret F, Masuoka E, Wolfe R, Claverie M, NOAA CDR Program (2014) NOAA Climate Data Record (CDR) of Normalized Difference Vegetation Index (NDVI), Version 4. (NOAA National Climatic Data Center). Available at https://data.nodc.noaa.gov/cgi-bin/iso?id=gov.noaa.ncdc:C00813# (Verified 12 November 2019). 10.7289/V5PZ56R6

Vilar L, Woolford DG, Martell DL, Martn MP (2010) A model for predicting human-caused wildfire occurrence in the region of Madrid, Spain. International Journal of Wildland Fire 19, 325–337.

Wang H, Boissel J-P, Nony P (2009) Revisiting the relationship between baseline risk and risk under treatment. Emerging Themes in Epidemiology 6, Article 1
Revisiting the relationship between baseline risk and risk under treatment.Crossref | GoogleScholarGoogle Scholar | 19222846PubMed |

Wang X, Wotton BM, Cantin AS, Parisien MA, Anderson K, Moore B, Flannigan MD (2017) cffdrs: an R package for the Canadian Forest Fire Danger Rating System. Ecological Processes 6, Article 5
cffdrs: an R package for the Canadian Forest Fire Danger Rating System.Crossref | GoogleScholarGoogle Scholar |

Wiken EB (1986) ‘Terrestrial ecozones of Canada.’ (Environment Canada, Lands Directorate: Ottawa, ON, Canada)

Woolford DG, Braun WJ (2007) Convergent data sharpening for the identification and tracking of spatial temporal centers of lightning activity. Environmetrics 18, 461–479.
Convergent data sharpening for the identification and tracking of spatial temporal centers of lightning activity.Crossref | GoogleScholarGoogle Scholar |

Woolford DG, Bellhouse DR, Braun WJ, Dean CB, Martell DL, Sun J (2011) A spatiotemporal model for people-caused forest fire occurrence in the Romeo Malette forest. Journal of Environmental Statistics 2, 2–16.

Wotton BM (2009) Interpreting and using outputs from the Canadian Forest Fire Danger Rating System in research applications. Environmental and Ecological Statistics 16, 107–131.
Interpreting and using outputs from the Canadian Forest Fire Danger Rating System in research applications.Crossref | GoogleScholarGoogle Scholar |

Wotton BM, Flannigan MD (1993) Length of the fire season in a changing climate. Forestry Chronicle 69, 187–192.
Length of the fire season in a changing climate.Crossref | GoogleScholarGoogle Scholar |

Wotton BM, Martell DL (2005) A lightning fire occurrence model for Ontario. Canadian Journal of Forest Research 35, 1389–1401.
A lightning fire occurrence model for Ontario.Crossref | GoogleScholarGoogle Scholar |

Wotton BM, Stocks BJ, Martell DL (2005) An index for tracking sheltered forest floor moisture within the Canadian Forest Fire Weather Index System. International Journal of Wildland Fire 14, 169–182.
An index for tracking sheltered forest floor moisture within the Canadian Forest Fire Weather Index System.Crossref | GoogleScholarGoogle Scholar |

Xi DX, Taylor SW, Woolford DG, Dean CB (2019) Statistical models of key components of wildfire risk. Annual Review of Statistics and its Applications 6, 197–222.
Statistical models of key components of wildfire risk.Crossref | GoogleScholarGoogle Scholar |

Youden WJ (1950) Index for rating diagnostic tests. Cancer 3, 32–35.
Index for rating diagnostic tests.Crossref | GoogleScholarGoogle Scholar | 15405679PubMed |