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Abstract

Reliable interpretation of fire pattern indicators is essential for wildland fire origin investigations, yet experimental validation is scarce. Damage Differential in the context of this study refers to the measurable changes in combustible and noncombustible objects after fire exposure, enabling the comparison and contrast of fire-caused effects on different faces or zones of artifacts, as described in NWCG PMS 412 (2025, 2016, 2005) and NFPA 921. The principle was quantifiably applied using image analysis and statistical methods (ANOVA) to evaluate directional reliability under controlled wind and fuel conditions. Our approach aims to reduce subjective interpretation by linking observed damage to specific fire dynamics and environmental factors. This study presents laboratory-scale wind tunnel experiments evaluating the directional behavior of commonly used indicators. Statistical analysis using ANOVA revealed that wind speed, fuel load, and artifact orientation each had a significant influence on fire indicators (p < 0.001). Findings show that while indicators can yield reproducible directional cues, their reliability is bounded by specific interactions between fire intensity and airflow conditions. A complementary field-scale study is underway to evaluate fire patterns in operational settings, thereby strengthening the scientific basis for evidence-based wildland fire investigations.

Keywords

Wildland fires NWCG PMS 412 NFPA 921 forensic science damage differential fire pattern indicators statistical analysis

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References

NWCG. Guide to wildland fire origin and cause determination. PMS 412. Boise, ID: National Wildfire Coordinating Group, 2016, https://www.nwcg.gov/publications/412 (accessed 13 July 2025).

NWCG. Guide to wildland fire origin and cause determination. PMS 412 (March 2025). Boise, ID: National Wildfire Coordinating Group, 2025, https://www.nwcg.gov/publications/412 (accessed 13 July 2025).

Maranghides

Mell

Hawks

, et al. Preliminary data collected from the camp fire reconnaissance. NIST technical note 2128, December. Gaithersburg, MD: National Institute of Standards and Technology, 2020.

CTIF. 911 down: 36 dead as Hawaiian residents jump in ocean for rescue when large wildfires burn both islands. International Association of Fire and Rescue Services (CTIF), 2023, https://www.ctif.org/news/911-down-36-dead-hawaiian-residents-jump-ocean-rescue-when-large-wildfires-burn-both-islands

Alexander

Smith

Thomas

Global synthesis of quantification of fire behaviour characteristics in forests and shrublands: recent progress. Curr Forest Rep 2025; 11: 8.

Gorbett

Meacham

Wood

, et al. Use of damage in fire investigation: a review of fire patterns analysis, research and future direction. Fire Sci Rev 2015; 4: 4.

Simeoni

Owens

Christiansen

, et al. A preliminary study of wildland fire pattern indicator reliability following an experimental fire. J Fire Sci 2017; 35(5): 359–378.

Parker

Babrauskas

Validation of NWCG wildfire directional indicators in test burns in coastal California. Fire 2024; 7(5): 5.

Danckwerts

Physical evidence of fire and burn patterns. In: Forensic fire analysis, 1st ed. 2022, pp. 143–190. DOI: 10.1007/978-3-030-92847-3.

10.

National Fire Protection Association. NFPA: 921: guide for fire explosion investigations. Quincy, MA: National Fire Protection Association, 2021.

11.

Martin

Hamman

ST.

Ignition patterns influence fire severity and plant communities in Pacific Northwest, USA, Prairies. Fire Ecol 2016; 12(1): 88–102.

12.

NWCG. Wildfire origin & cause determination handbook (PMS 412-1). Boise, ID: National Wildfire Coordinating Group, 2005.

13.

Nelson

Jr . An effective wind speed for models of fire spread. Int J Wildland Fire 2002; 11(3–4): 153–161.

14.

Abouali

Viegas

Raposo

JR.

Analysis of the wind flow and fire spread dynamics over a sloped–ridgeline hill. Combust Flame 2021; 234: 111724.

15.

Madrzykowski

Fleischmann

. Fire pattern repeatability: a laboratory study on gypsum wallboard. NIST technical report, 2010, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=906657

16.

Singh

Ziazi

Simeoni

. Intermittent fireline behaviour over porous vegetative media in different crossflow conditions. Int J Wildland Fire 2023; 32(4): 368–378.

17.

Yang

, et al. Integrating earth observation data into the tri-environmental evaluation of the economic cost of natural disasters: a case study of 2025 LA wildfire. 2025, https://arxiv.org/abs/2505.01721

18.

Mueller

Campbell-Lochrie

Walker-Ravena

, et al. Flame spread and combustion dynamics in pine litter under unsteady wind conditions. In: Viegas

Ribeiro

(eds) Advances in forest fire research 2022. Coimbra: University of Coimbra, 2022, pp. 1469–1476.

19.

Sikkink

Lutes

Keane

RE.

Field guide for identifying fuel loading models. General technical report RMRS-GTR-225. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 2009, https://www.fs.usda.gov/rm/pubs/rmrs_gtr225

20.

Schemel

Simeoni

Biteau

, et al. A calorimetric study of wildland fuels. Exp Therm Fluid Sci 2008; 32: 1381–1389.

21.

Bowman

DMJS

Haverkamp

Rann

, et al. Differential demographic filtering by surface fires: How fuel type and fuel load affect sapling mortality of an obligate seeder savanna tree. J Ecology 2017; 105(4): 1113–1124.

22.

Riahi

Development of tools for smoke residue and deposition analysis, Final report, NIJ award no. 2007-DN-BX-K236. U.S. Department of Justice, Office of Justice Programs, National Institute of Justice 2012, https://www.ojp.gov/pdffiles1/nij/grants/238725.pdf

23.

Riahi

Beyler

Measurement and prediction of smoke deposition from a fire against a wall. Fire Safe Sci 2011; 10: 641–654.

24.

Riahi

Beyler

Hartman

. Wall smoke deposition from a hot smoke layer. Fire Technol 2013; 49(2): 395–409.

25.

Hasnain

Sezer

Kozhumal

SP.

Predicting thermal response of gypsum board under various heat flux configurations: a three-dimensional mathematical model. SSRN Electr J 2024. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4926085

26.

Otsu

A threshold selection method from gray-level histograms. IEEE T Syst Man Cybernet 1979; 9(1): 62–66.

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Reliability of fire indicators based on the damage differential principle in wildland fire investigation: A laboratory approach

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