Mapping wildland-urban interfaces at large scales integrating housing density and vegetation aggregation for fire prevention in the South of France

Lampin-Maillet, C.; Jappiot, Marielle; Long, M.; Bouillon, Christophe; Morge, D.; Ferrier, Jean-Paul

doi:10.1016/j.jenvman.2009.10.001

Cited by 170 publications

(118 citation statements)

References 22 publications

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“…For each object classified in C1, C3 and C6, category specific classification rules based on spectral and textural attributes (see Table 2), are used to distinguish the "artificial areas" class. For instance for objects that belong to the C3 category, a classification rule based on near infrared information is used to separate "vegetation objects" from "building objects", the latter being extremely small and isolated in this region [28]. Finally, manual classification processing is performed to reduce confusion between artificial objects and agricultural or semi-natural bare soil objects that have very similar spectral and textural behaviors.…”

Section: Procedures For Classification Of Rapideye Images Acquired In mentioning

confidence: 99%

An Object-Based Image Analysis Method for Monitoring Land Conversion by Artificial Sprawl Use of RapidEye and IRS Data

Dupuy

Barbe²,

Balestrat³

2012

Remote Sensing

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Abstract:In France, in the peri-urban context, urban sprawl dynamics are particularly strong with huge population growth as well as a land crisis. The increase and spreading of built-up areas from the city centre towards the periphery takes place to the detriment of natural and agricultural spaces. The conversion of land with agricultural potential is all the more worrying as it is usually irreversible. The French Ministry of Agriculture therefore needs reliable and repeatable spatial-temporal methods to locate and quantify loss of land at both local and national scales. The main objective of this study was to design a repeatable method to monitor land conversion characterized by artificial sprawl: (i) We used an object-based image analysis to extract artificial areas from satellite images; (ii) We built an artificial patch that consists of aggregating all the peripheral areas that characterize artificial areas. The "artificialized" patch concept is an innovative extension of the urban patch concept, but differs in the nature of its components and in the continuity distance applied; (iii) The diachronic analysis of artificial patch maps enables characterization of artificial sprawl. The method was applied at the scale of four departments (similar to provinces) along the coast of Languedoc-Roussillon, in the South of France, based on two satellite datasets, one acquired in 1996-1997 (Indian Remote Sensing) and the other in 2009 (RapidEye). In the four departments, we measured an increase in artificial areas of from 113,000 ha in 1997 to 133,000 ha in 2009, i.e., an 18% increase in 12 years. The package comes in the form of a 1/15,000 valid cartography, usable at the scale of a commune (the smallest territorial division used for administrative purposes in France) that can be adapted to departmental and regional scales. The method is reproducible in OPEN ACCESSRemote Sens. 2012, 4 405 homogenous spatial-temporal terms, so that it could be used periodically to assess changes in land conversion rates in France as a whole.

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Section: Procedures For Classification Of Rapideye Images Acquired In mentioning

confidence: 99%

An Object-Based Image Analysis Method for Monitoring Land Conversion by Artificial Sprawl Use of RapidEye and IRS Data

Dupuy

Barbe²,

Balestrat³

2012

Remote Sensing

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“…The United States Department of Agriculture (USDA) defined the WUI as the area "where humans and their development meet or intermix with wildland fuels" (Stewart et al, 2007); in this area, fires can spread readily among vegetation fuels and urban structures. Anthropogenic features, such as the distance to roads and houses, have a negative influence on the probability of forest fire occurrence, while population density positively affects it (Haight et al, 2004;Radeloff et al, 2005;Stewart et al, 2007;Hammer et al, 2009;Lampin-Maillet et al, 2010;Conedera et al, 2015). This trend has made these variables to be commonly considered the most important to elaborate in WUI maps.…”

Section: Introductionmentioning

confidence: 99%

“…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). Researchers have developed several geospatial mod-els for defining and mapping the WUI, taking into account all the above-mentioned factors.…”

Section: Introductionmentioning

confidence: 99%

“…Researchers have developed several geospatial mod-els for defining and mapping the WUI, taking into account all the above-mentioned factors. In Europe, Lampin-Maillet et al (2010) proposed an approach based on the combination of four types of buildings configuration and three classes of vegetation structure. Following this model, Bouillon et al (2012) developed WUImap, a software tool for mapping WUI in the Mediterranean region successfully applied in southeastern France, eastern Spain and Sardinia, Italy.…”

Section: Introductionmentioning

confidence: 99%

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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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“…Within the WUI fire can spread readily among vegetation fuels and urban structures. It is well known that anthropogenic features, such as the distance to roads and houses, negatively influence the probability of forest fire occurrence, while the population density positively affects it (Conedera et al, 2015;Haight et al, 2004;Hammer et al, 2009;Lampin-Maillet et al, 2010;Radeloff et al, 2005;Stewart et al, 2007), so that the spatial extension of the WUI is determined by these factors.…”

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confidence: 99%

Global assessment of land cover changes and rural-urban interface in Portugal

Tonini¹,

Parente²,

Pereira³

2017

Preprint

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Abstract. The wildland-/rural-urban interface (WUI/RUI) is a particularly important aspect of the fire regime. In Mediterranean basin most of the fires in this pyro region are caused by humans and the risk and consequences are particularly high due to the 10 close proximity to population, human infrastructures and urban areas. Population increase, urban growth and the rapid changes in land use incurred in Europe over the last 30 years has been unprecedented, especially nearby the metropolitan areas, and some of these trends are expected to continue. Associated to high socioeconomic development, Portugal experienced in the last decades significant land cover/land use changes (LCLUC), population dynamics and demographic trends in response to migration, rural abandonment, and ageing of rural population. This study aims to assess the evolution of RUI in Portugal, from 1990 to 2012, based 15 on LCLUC providing also a quantitative characterization of forest fires dynamics in relation to the burnt area. Obtained results disclose important LCLUC which spatial distribution is far from uniform within the territory. A significant increase in artificial surfaces is registered nearby the main metropolitan communities of the northwest and littoral-central and southern regions, whilst the abandonment of agricultural land nearby the inland urban areas leads to an increase of uncultivated semi-natural and forest areas. Within agricultural areas, heterogeneous patches suffered the greatest changes and are the main contributors to the increase 20 of urban areas. Moreover these are among the LCLU classes with higher burnt area, reasons why heterogeneous agricultural areas have been included in the definition of RUI. Finally, the mapped RUI's area, burnt area and burnt area within RUI allow to conclude that, form 1990 to 2012 in Portugal, RUI increased more than two thirds and total burnt area decreased one third. Nevertheless, burnt area within RUI doubled, which emphasize the significance of RUI for land and fire managers. This research provides a first quantitative global assessment of RUI in Portugal and presents an innovative analysis on the impact of land use changes on burnt 25 areas.

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Mapping wildland-urban interfaces at large scales integrating housing density and vegetation aggregation for fire prevention in the South of France

Cited by 170 publications

References 22 publications

An Object-Based Image Analysis Method for Monitoring Land Conversion by Artificial Sprawl Use of RapidEye and IRS Data

An Object-Based Image Analysis Method for Monitoring Land Conversion by Artificial Sprawl Use of RapidEye and IRS Data

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

Global assessment of land cover changes and rural-urban interface in Portugal

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