The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Integrating fire behavior and pedestrian mobility models to assess potential risk to humans from wildfires within the U.S.–mexico border zone
Abstract
Wildfires create a risk to pedestrians traveling through rural areas, because they might not be aware of the presence of a wildfire or its direction and rate of spread until is too late to successfully evacuate. In wildland areas of southern San Diego County, immigrants crossing the U.S.–Mexico border and border security agents are particularly at risk to wildfires. The objective of this study is to develop a framework of analysis and associated tools for examining the combined behavior of wildfires and pedestrian mobility to assess the potential threat of fire to pedestrians in wildland areas. Outputs from a geographic information system (GIS) overlay model for determining potentially dangerous fire zones, the Wildland–Urban Interface Evacuation (WUIVAC) model, and a model of pedestrian mobility in wildland areas were combined to generate wildfire risk to pedestrian maps. The key technical contributions of the study are the development and testing of the pedestrian mobility model and the framework and logic for integrating the results of three GIS-based models. The applied geography contribution is the testing of two scenarios of high risk from wildfires to pedestrians within the U.S.–Mexico border zone of San Diego County, California. The study results show that the travel times calculated by the pedestrian mobility model appear to be realistic and are affected by the terrain and vegetation characteristics of a study site, whereas the evacuation trigger buffers (ETBs) from WUIVAC are mostly influenced by the wind speed and direction parameters of the FlamMap fire spread model. A moderate fire danger to pedestrians in the most remote wildland locations of the study area is determined. The scenario test results suggest that if a wildfire occurs within 2 km (extreme southwesterly winds) or 6 km (extreme northeasterly wind) of pedestrians in the worst case location within the San Diego border region they would likely not have a sufficient amount of time to reach a nearby safety zone.
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The presence, abundance, structure, and distribution of vegetation have major limiting effects on the ease with which one can move through a landscape.
“The presence, abundance, structure, and distribution of vegetation also have major limiting effects on the ease with which one can move through a landscape20–22.”
From A singular, broadly-applicable model for estimating on- and off-path walking travel rates using airborne lidar data (2024) · cites this paper as [20]
Taller shrubs and trees can impact movement in ways ranging from avoidance to impedance.
“Taller shrubs and trees can impact movement in a variety of ways, ranging from avoidance (i.e., moving around obstacles deemed impassible) to impedance (i.e., moving through passible vegetation but being physically restrained by it).”
From A singular, broadly-applicable model for estimating on- and off-path walking travel rates using airborne lidar data (2024) · cites this paper as [20]
Shorter vegetation at or near the ground surface can affect foot placement and alter gait.
“Shorter vegetation at or near the ground surface (i.e., grasses, forbs, shrubs) can affect foot placement and alter gait.”
From A singular, broadly-applicable model for estimating on- and off-path walking travel rates using airborne lidar data (2024) · cites this paper as [20]
Citations
Cites
A note on two problems in connexion with graphs
Dijkstra, E. (1959) · Numerische Mathematik · doi:10.1007/bf01386390 · Cited by 24,351
The Shuttle Radar Topography Mission
Farr, T. G., Rosen, P. A., Caro, E., Crippen, R., Duren, R., Hensley, S., Kobrick, M., Paller, M., Rodriguez, E., Roth, L., et al. (2007) · Reviews of Geophysics · doi:10.1029/2005rg000183 · Cited by 8,927
Fire as a global ‘herbivore’: the ecology and evolution of flammable ecosystems
BOND, W., & KEELEY, J. (2005) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2005.04.025 · Cited by 2,484
A mathematical model for predicting fire spread in wildland fuels
Rothermel, R. C. (1972) · doi:10.2737/int-rp-115 · Cited by 2,247
Gamon, J. A., Field, C. B., Goulden, M. L., Griffin, K. L., Hartley, A. E., Joel, G., Peñuelas, J., & Valentini, R. (1995) · Ecological Applications · doi:10.2307/1942049 · Cited by 1,088
(1996) · Choice Reviews Online · doi:10.5860/choice.34-0916 · Cited by 1,061
Aids to determining fuel models for estimating fire behavior
Anderson, H. E. (1982) · doi:10.2737/int-gtr-122 · Cited by 1,008
DeBano, L. F., Neary, D. G., & Ffolliott, P. F. (1998) · Cited by 989
A tabu search heuristic for the static multi-vehicle dial-a-ride problem
Cordeau, J., & Gilbert Laporte, A. (2003) · Transportation Research Part B Methodological · doi:10.1016/s0191-2615(02)00045-0 · Cited by 732
Human influence on California fire regimes
Syphard, A. D., Radeloff, V. C., Keeley, J. E., Hawbaker, T. J., Clayton, M. K., Stewart, S. I., & Hammer, R. B. (2007) · Ecological Applications · doi:10.1890/06-1128.1 · Cited by 661
Lee, X. U. (1997) · Agricultural and Forest Meteorology · doi:10.1016/s0168-1923(97)00032-4 · Cited by 567
Succession after Fire in the Chaparral of Southern California
Hanes, T. L. (1971) · Ecological Monographs · doi:10.2307/1942434 · Cited by 511
A network flow model for lane-based evacuation routing
Cova, T. J., & Johnson, J. P. (2003) · Transportation Research Part A Policy and Practice · doi:10.1016/s0965-8564(03)00007-7 · Cited by 483
Self-citationFire Mosaics in Southern California and Northern Baja California
Minnich, R. A. (1983) · Science · doi:10.1126/science.219.4590.1287 · Cited by 403
Microsimulation of Neighborhood Evacuations in the Urban–Wildland Interface
Cova, T. J., & Johnson, J. P. (2002) · Environment and Planning A Economy and Space · doi:10.1068/a34251 · Cited by 246
Self-citationIntroduction to Wildland Fire: Fire Management in the United States
Pyne, S. J. (1984) · Medical Entomology and Zoology · Cited by 175
Fuel Treatments at the Wildland-Urban Interface: Common Concerns in Diverse Regions
Winter, G., Vogt, C. A., & Fried, J. S. (2002) · Journal of Forestry · doi:10.1093/jof/100.1.15 · Cited by 140
Lessons from the October 2003 wildfires in Southern California.
Keeley, J. E., Fotheringham, C. J., & Moritz, M. A. (2004) · Journal of Forestry · doi:10.1093/jof/102.7.26 · Cited by 133
Setting Wildfire Evacuation Trigger Points Using Fire Spread Modeling and GIS
Cova, T. J., Dennison, P. E., Kim, T. H., & Moritz, M. A. (2005) · Transactions in GIS · doi:10.1111/j.1467-9671.2005.00237.x · Cited by 123
Self-citationModeling of marginal burning state of fire spread in live chaparral shrub fuel bed
Zhou, X., Shankar Mahalingam, A., & Weise, D. R. (2005) · Combustion and Flame · doi:10.1016/j.combustflame.2005.05.013 · Cited by 99
Wolshon, B., & Marchive, E. (2007) · Journal of Urban Planning and Development · doi:10.1061/(asce)0733-9488(2007)133:1(73 · Cited by 79
WUIVAC: a wildland-urban interface evacuation trigger model applied in strategic wildfire scenarios
Dennison, P. E., Cova, T. J., & Mortiz, M. A. (2006) · Natural Hazards · doi:10.1007/s11069-006-9032-y · Cited by 77
Self-citationMcMichael, C. E., Hope, A. S., Roberts, D. A., & Anaya, M. (2004) · International Journal of Remote Sensing · doi:10.1080/01431160410001726067 · Cited by 71
Modeling Small Area Evacuation: Can Existing Transportation Infrastructure Impede Public Safety?
Church, R. L., & Sexton, R. (2002) · Cited by 64
Henry, M. C., & Hope, A. S. (1998) · International Journal of Remote Sensing · doi:10.1080/014311698214208 · Cited by 57
Minnich, R. A. (1987) · Annals of the Association of American Geographers · doi:10.1111/j.1467-8306.1987.tb00183.x · Cited by 37
Radke, J., Cova, T., SHERIDAN, M. F., Troy, A. R., Mu, L., & Johnson, R. (1999) · Cited by 35
Self-citationThe Wildland-Urban Interface: Introduction and Overview
Ewert, A. (1993) · Journal of Leisure Research · doi:10.1080/00222216.1993.11969905 · Cited by 33
Exploratory Map Animation for Post-Event Analysis of Wildfire Protective Action Recommendations
Kim, T. H., Cova, T. J., & Brunelle, A. R. (2006) · Natural Hazards Review · doi:10.1061/(asce)1527-6988(2006)7:1(1 · Cited by 24
Self-citationEnvironmental Impacts of Illegal Immigration on the Cleveland National Forest in California
McIntyre, D. L., & Weeks, J. R. (2002) · The Professional Geographer · doi:10.1111/0033-0124.00338 · Cited by 20
A directional path distance model for raster distance mapping
Zhan, C., Menon, S., & Gao, P. (1993) · Lecture notes in computer science · doi:10.1007/3-540-57207-4_29 · Cited by 19
Travel Rates of Alberta Wildland Firefighters Using Escape Routes
Alexander, M., Baxter, G., & Dakin, G. (2005) · Cited by 11
Flagged first, then by citations
Research works printed but not linked: 12
- ArcGIS, Version 9.2
- Beighley M., 1995, Fire Management Notes, 55, 22
- 2003, End of year final report
- Butler, B. W., Cohen, J. D., Putnam, T., Bartlette, R. A. and Bradshaw, L. S. A method for evaluating the effectiveness of firefighter escape routes. Proceedings of 2000 International Wildfire Safety Summit. Edited by: Butler, B. W. and Shannon, K. pp.42–53. Montana City, MT: International Association of Wildland Fire.
- 2003, The 2003 San Diego County fire siege: Fire safety review
- 2003, Planning a hike
- Cova T., 2002, A, 34, 2211
- Finney M., 2007, FlamMap
- 2004, Fire Protection and Assessment Program
- 2005, Fire Protection and Assessment Program
- Radke J., 2000, URISA Journal, 102, 15
- 2001, Schweizer Wanderwege, Federation Suisse de tourisme pedestre, Ente svizzero pro sentieri [Walking time estimates for trails]
Cited by
Sorted by citations
Wood, N. J., & Schmidtlein, M. C. (2012) · Natural Hazards · doi:10.1007/s11069-011-9994-2 · Cited by 133
Li, D., Cova, T. J., & Dennison, P. E. (2018) · Fire Technology · doi:10.1007/s10694-018-0771-6 · Cited by 93
Self-citationEvacuation models and disaster psychology
Vorst, H. C. M. (2010) · Procedia Engineering · doi:10.1016/j.proeng.2010.07.004 · Cited by 81
Warning Triggers in Environmental Hazards: Who Should Be Warned to Do What and When?
Cova, T. J., Dennison, P. E., Li, D., Drews, F. A., Siebeneck, L. K., & Lindell, M. K. (2016) · Risk Analysis · doi:10.1111/risa.12651 · Cited by 62
Self-citationA household-level approach to staging wildfire evacuation warnings using trigger modeling
Li, D., Cova, T. J., & Dennison, P. E. (2015) · Computers Environment and Urban Systems · doi:10.1016/j.compenvurbsys.2015.05.008 · Cited by 59
Self-citationSiam, M. R. K., Wang, H., Lindell, M. K., Chen, C., Vlahogianni, E. I., & Axhausen, K. W. (2022) · Transportation Research Part D Transport and Environment · doi:10.1016/j.trd.2021.103147 · Cited by 58
Campbell, M. J., Dennison, P. E., & Butler, B. W. (2017) · International Journal of Wildland Fire · doi:10.1071/wf17031 · Cited by 42
Self-citationEvaluating dynamic wildfire evacuation trigger buffers using the 2003 Cedar Fire
Larsen, J. C., Dennison, P. E., Cova, T. J., & Jones, C. (2010) · Applied Geography · doi:10.1016/j.apgeog.2010.05.003 · Cited by 42
Self-citationWildland firefighter entrapment avoidance: Modelling evacuation triggers
Fryer, G. K., Dennison, P. E., & Cova, T. J. (2013) · International Journal of Wildland Fire · doi:10.1071/wf12160 · Cited by 41
Self-citationAssessment of social vulnerability to forest fire and hazardous facilities in Germany
Fekete, A., & Nehren, U. M. (2023) · International Journal of Disaster Risk Reduction · doi:10.1016/j.ijdrr.2023.103562 · Cited by 39
Population Response to Earthquakes and Earthquake Early Warnings in Mexico
Vaiciulyte, S., Novelo-Casanova, D. A., Husker, A. L., & Garduño-González, A. B. (2021) · International Journal of Disaster Risk Reduction · doi:10.1016/j.ijdrr.2022.102854 · Cited by 24
Using reverse geocoding to identify prominent wildfire evacuation trigger points
Li, D., Cova, T. J., & Dennison, P. E. (2017) · Applied Geography · doi:10.1016/j.apgeog.2017.05.008 · Cited by 21
Self-citationWhy do we need a national address point database to improve wildfire public safety in the U.S.?
Li, D., Cova, T. J., Dennison, P. E., Wan, N., Nguyen, Q. C., & Siebeneck, L. K. (2019) · International Journal of Disaster Risk Reduction · doi:10.1016/j.ijdrr.2019.101237 · Cited by 18
Self-citationPedestrian evacuation modelling of a Canadian West Coast community from a near-field Tsunami event
Cheff, I., Nistor, I., & Palermo, D. (2018) · Natural Hazards · doi:10.1007/s11069-018-3487-5 · Cited by 17
Unraveling hurricane Ian’s Impact: A multiscale analysis of mobility networks in Florida
Wang, J., & Hu, Y. (2024) · Transportation Research Part D Transport and Environment · doi:10.1016/j.trd.2024.104482 · Cited by 14
Zhang, D., Huang, G., Li, H., Deng, Q., & Gao, X. (2023) · Applied Sciences · doi:10.3390/app13010609 · Cited by 11
Zheng, A., Ba, R., Jiang, W., Chen, Z., He, M., Hua, Y., Zhu, S., Zhu, J., Liu, G., Zhu, Z., et al. (2025) · Journal of Safety Science and Resilience · doi:10.1016/j.jnlssr.2025.100252 · Cited by 9
Campbell, M. J., Cutler, S. L., & Dennison, P. E. (2024) · Scientific Reports · doi:10.1038/s41598-024-71359-6 · Cited by 7
Self-citationCelikbas, B., Tufekci-Enginar, D., Dogan, G. G., Kolat, C., Santini, M., Annunziato, A., Necmioglu, O., Yalciner, A. C., & Suzen, M. L. (2023) · Natural Hazards · doi:10.1007/s11069-023-06034-6 · Cited by 5
Chambers, S. N., & Miranker, M. (2022) · The Professional Geographer · doi:10.1080/00330124.2022.2081223 · Cited by 4
An open-source software system for setting wildfire evacuation triggers
Li, D., Cova, T. J., & Dennison, P. E. (2015) · ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management (EM-GIS) · doi:10.1145/2835596.2835600 · Cited by 4
Self-citationSocial vulnerability gaps: Dynamics of the unsheltered homeless and wildfire hazards
Zheng, Z., Murray, A. T., Sweeney, S. H., & Arabadjis, S. D. (2025) · Applied Geography · doi:10.1016/j.apgeog.2025.103648 · Cited by 2
Recent Research Trends in Disaster Studies: Human Geographical Perspective
Soda, R. (2015) · Geographical Studies · doi:10.7886/hgs.90.16 · Cited by 2
Strategy for Effective Evacuation of Pedestrians Using GIS and GPS Measurements
Polakis, N., & Tsouchlaraki, A. (2022) · Journal of Geographic Information System · doi:10.4236/jgis.2022.145027 · Cited by 2
Reynolds, R. (2017) · Libraries and Cultural Resources (University of Calgary) · doi:10.11575/prism/27316 · Cited by 1
Cutler, S. L., Campbell, M. J., Brewer, S. C., & Dennison, P. E. (2026) · GIScience & Remote Sensing · doi:10.1080/15481603.2026.2626632
Self-citationFryer, G. K. (2012) · J. Willard Marriott Library · doi:10.26053/0h-yj7h-8300
Adaptive path planning for arriving at firelines in dynamic wildfires and complex landscapes
Zeren, G., Yu, B., Zhu, J., & Jiang, W. (2025) · Safety Emergency Science · doi:10.26599/ses.2025.9590004
Metadata
- Authors
- Anguelova, Z., Stow, D. A., Kaiser, J., Dennison, P. E., & Cova, T.
- Affiliations
- San Diego State University (US)
- Venue
- The Professional Geographer
- Publisher
- Informa UK Limited
- Published
- 2010-03-31
- Volume
- 62
- Issue
- 2
- Pages
- 230-247
- ISSN
- 0033-0124 (ISSN-L)
- 1467-9272
- OpenAlex
- W2024569331
- Cited by
- 29
- References
- 32
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 3 · 2023: 3 · 2022: 3 · 2021: 1 · 2019: 1 · 2018: 2 · 2017: 3 · 2016: 1 · 2015: 3 · 2013: 1 · 2012: 1
- FWCI
- 7.21
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Professional Geographer (publishedVersion)
- Topics
- Social Sciences › Safety Research › Evacuation and Crowd Dynamics
- Social Sciences › Sociology and Political Science › Disaster Management and Resilience
- Physical Sciences › Environmental Science › Global and Planetary Change › Fire effects on ecosystems
- Keywords
- fire spread modeling, FlamMap, San Diego County, immigrants, travel time, wind speed and direction, safety zones
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