Convection–Diffusion Model for the Prediction of Anthropogenically-Initiated Wildfire Ignition

Ravi Sadasivuni; Shanti Bhushan; William H. Cooke

doi:10.1007/s13753-014-0034-1

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Article Navigation > International Journal of Disaster Risk Science > 2014 > 5(4): 274-295

Ravi Sadasivuni, Shanti Bhushan, William H. Cooke. Convection–Diffusion Model for the Prediction of Anthropogenically-Initiated Wildfire Ignition[J]. International Journal of Disaster Risk Science, 2014, 5(4): 274-295. doi: 10.1007/s13753-014-0034-1

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Ravi Sadasivuni, Shanti Bhushan, William H. Cooke. Convection–Diffusion Model for the Prediction of Anthropogenically-Initiated Wildfire Ignition[J]. International Journal of Disaster Risk Science, 2014, 5(4): 274-295. doi: 10.1007/s13753-014-0034-1

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Convection–Diffusion Model for the Prediction of Anthropogenically-Initiated Wildfire Ignition

doi: 10.1007/s13753-014-0034-1

1 Department of Geosciences, Mississippi State University, Starkville, MS 39759, USA;
2 Center for Advance Vehicular Systems, Mississippi State University, Starkville, MS 39759, USA

Available Online: 2021-04-26

Abstract

Abstract

A spatial interaction model to predict anthropogenically-initiated accidental and incendiary wildfire ignition probability is developed using fluid flow analogies for human movement patterns. Urban areas with large populations are identified as the sites of global influencing factors, and are modeled as the gravity term. The transportation corridors are identified as local influencing factors, and are modeled using fluid flow analogy as diffusion and convection terms. The model is implemented in ArcGIS, and applied for the prediction of wildfire hazard distribution in southeastern Mississippi. The model shows 87 % correlation with historic data in the winter season, whereas the previously developed gravity model shows only 75 % correlation. The normalized error for convection–diffusion model predictions is about 5 % in the winter season, whereas the gravity model shows an error of 7 %. The proposed model is robust as it couples a multi-criteria behavioral pattern within a single dynamic equation to enhance predictive capability. At the same time, the proposed model is more costly than the gravity model as it requires evaluation of distance from intermodal transportation corridors, transportation corridor density, and traffic volume maps. Nonetheless, the model is developed in a modular fashion, such that either global or local terms can be neglected if required.
- Anthropogenic-fire,
- Convection–diffusion model,
- Fire ignition potential,
- Mississippi,
- Wildfire hazard

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References(52)

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