The wildland–urban interface dynamics in the southeastern U.S. from 1990 to 2000

Zhang, Yangjian; He, Hong S.; Yang, Jian

doi:10.1016/j.landurbplan.2007.11.007

Cited by 40 publications

(16 citation statements)

References 24 publications

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“…For this purpose, we used the aggregation index (AI) Wang et al 2014); this index has been employed in previous WUI mapping studies (Lampin-Maillet et al 2010;Galiana-Martina et al 2011;Herrero-Corral et al 2012). This index provides a measure of the degree of the connectivity or aggregation of fuel dispersed within areas of non-fuel, and it also provides a proxy for the ease of fire spread across the landscape (Zhang et al 2008;Lampin-Maillet et al 2010).…”

Section: Fuels Datamentioning

confidence: 99%

“…Under less hazardous fuel conditions, the buffer value is decreased; e.g. a continuous mixedwood stand (fuel weight value of 2) would have twice the 'cost' in the cost distance procedure calculating the buffer distance, and thus would have a buffer width of 1200 m. We chose the 2400-m maximum buffer distance for two reasons; the first is that this distance is frequently used in WUI mapping literature (Haight et al 2004;Radeloff et al 2005;Hammer et al 2007;Stewart et al 2007;Theobald and Romme 2007;Zhang et al 2008;Platt 2010;Maranghides and Mell 2011;Bar-Massada et al 2013;Thomas and Butry 2014) because it is the federally accepted standard in the United States said to represent the distance a firebrand can travel from a wildland fire and ignite a structure (USDA and USDI 2001; though rigorous investigation into refining this potential spotting distance and structure ignition is required). The second reason is that it is an appropriate match to the spatial scale and the management applications of the interface maps in the present study, including values protection, fire management planning and fuels treatments.…”

Section: Interface Calculationmentioning

confidence: 99%

“…Many studies done in other countries (United States primarily, but also France, Spain, Australia) have not only mapped the current area of WUI up to a national scale (Radeloff et al 2005;Theobald and Romme 2007;LampinMaillet et al 2010;Galiana-Martina et al 2011;Herrero-Corral et al 2012;Chas-Amil et al 2013;Haas et al 2013;Chuvieco et al 2014;Price and Bradstock 2014;Thomas and Butry 2014), but have also mapped past changes in WUI Theobald and Romme 2007;Zhang et al 2008;Bouillon et al 2014;Fox et al 2015) and predicted future WUI changes (Theobald and Romme 2007). In Canada, there are only two published studies mapping the WUI, and both were done at a municipal scale.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Mapping Canadian wildland fire interface areas

Johnston

Flannigan

2018

Int. J. Wildland Fire

106

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Abstract. Destruction of human-built structures occurs in the 'wildland-urban interface' (WUI) -where homes or other burnable community structures meet with or are interspersed within wildland fuels. To mitigate WUI fires, basic information such as the location of interface areas is required, but such information is not available in Canada. Therefore, in this study, we produced the first national map of WUI in Canada. We also extended the WUI concept to address potentially vulnerable industrial structures and infrastructure that are not traditionally part of the WUI, resulting in two additional maps: a 'wildland-industrial interface' map (i.e. the interface of wildland fuels and industrial structures, denoted here as WUI-Ind) and a 'wildland-infrastructure interface' map (i.e. the interface of wildland fuels and infrastructure such as roads and railways, WUI-Inf). All three interface types (WUI, WUI-Ind, WUI-Inf) were defined as areas of wildland fuels within a variable-width buffer (maximum distance: 2400 m) from potentially vulnerable structures or infrastructure. Canada has 32.3 million ha of WUI (3.8% of total national land area), 10.5 million ha of WUI-Ind (1.2%) and 109.8 million ha of WUI-Inf (13.0%). The maps produced here provide a baseline for future research and have a wide variety of practical applications.

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Section: Fuels Datamentioning

confidence: 99%

Section: Interface Calculationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mapping Canadian wildland fire interface areas

Johnston

Flannigan

2018

Int. J. Wildland Fire

106

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“…This trend has made these variables to be commonly considered the most important to elaborate in WUI maps. Urbanization, and the consequent abandonment of rural areas, has caused the expansion of this interface, increasing the probability of wildfires to affect houses and infrastructures (Theobald and Romme, 2007;Zhang et al, 2008). There is strong evidence that the expansion of the urban and WUI areas has increased the fire density and related risk (Fox et al, 2015;Gallardo et al, 2016;Lampin-Maillet et al, 2010;Viedma et al, 2015), as well as the cost of protecting houses from fire (Pellizzaro et al, 2012b), and has an impact on biodiversity and ecosystems (Radeloff et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

Global assessment of rural–urban interface in Portugal related to land cover changes

Tonini

Parente

Pereira

2018

Nat. Hazards Earth Syst. Sci.

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Abstract. The rural-urban interface (RUI), known as the area where structures and other human developments meet or intermingle with wildland and rural area, is at present a central focus of wildfire policy and its mapping is crucial for wildfire management. In the Mediterranean Basin, humans cause the vast majority of fires and fire risk is particularly high in the proximity of infrastructure and of rural/wildland areas. RUI's extension changes under the pressure of environmental and anthropogenic factors, such as urban growth, fragmentation of rural areas, deforestation and, more in general, land use/land cover change (LULCC). As with other Mediterranean countries, Portugal has experienced significant LULCC in the last decades in response to migration, rural abandonment, ageing of population and trends associated with the high socioeconomic development. In the present study, we analyzed the LULCC occurring in this country in the 1990-2012 period with the main objective of investigating how these changes affected RUI's evolution. Moreover, we performed a qualitative and quantitative characterization of burnt areas within the RUI in relation to the observed changes. Obtained results disclose important LULCC and reveal their spatial distribution, which is far from uniform within the territory. A significant increase in artificial surfaces was registered near the main metropolitan communities of the northwest, littoral-central and southern regions, whilst the abandonment of agricultural land near the inland urban areas led to an increase in uncultivated semi-natural and forest areas. Within agricultural areas, heterogeneous patches suffered the greatest changes and were the main contributors to the increase in urban areas; moreover, this land cover class, together with forests, was highly affected by wildfires in terms of burnt area. Finally, from this analysis and during the investigated period, it appears that RUI increased in Portugal by more than two-thirds, while the total burnt area decreased by one-third; nevertheless, burnt area within RUI doubled, which emphasizes the significance of RUI monitoring for land and fire managers.

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“…An expanding wildland urban interface and fragmented landscape of forest and agricultural fields creates challenges for prescribed burn programs, including risk of escape to adjacent lands and conflicts over air pollutant emissions (Theobald and Romme, 2007;Marshall et al, 2008;Zhang et al, 2008). Even where prescribed fire is still possible, many Southern forests have missed several burn rotations and now have hazardous fuel accumulations that may require a combination of mechanical, herbicide and prescribed burning treatments to create conditions in which prescribed burning can be safely initiated (Brockway and Lewis, 1997;Heuberger and Putz, 2003;Brockway et al, 2009).…”

Section: Introductionmentioning

confidence: 99%