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首页> 外文期刊>Landscape Ecology >Modeling exurban development near Washington, DC, USA: comparison of a pattern-based model and a spatially-explicit econometric model
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Modeling exurban development near Washington, DC, USA: comparison of a pattern-based model and a spatially-explicit econometric model

机译:模拟美国华盛顿特区附近的郊区发展:基于模式的模型与空间明确的计量经济模型的比较

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摘要

The development of private rural lands can significantly fragment landscapes, with potentially negative consequences on ecosystem services. Models of land-use trends beyond the urban fringe are therefore useful for developing policy to manage these environmental effects. However, land-use change models have been primarily applied in urban environments, and it is unclear whether they can adequately predict exurban growth. This study compared the ability of two urban growth models to project exurban development in north-central Virginia and western Maryland over a 24-year period. Pattern-based urban growth models (such as SLEUTH) are widely used, but largely mimic patterns that emerge from historic conditions rather than allowing landowner decision-making to project change. In contrast, spatially-explicit econometric models (such as the complementary log-log hazard assessed in this study) model landowner choices as profit-maximizing behavior subject to market and regulatory constraints. We evaluated the two raster-based models by comparing model predictions to observed exurban conversion at pixel and county scales. The SLEUTH model was more successful at matching the total amount of new growth at the county scale than it was at the pixel scale, suggesting its most appropriate use in exurban areas is as a blunt instrument to forewarn potential coarse-scale losses of natural resources. The econometric model performed significantly better than SLEUTH at both scales, although it was not completely successful in fulfilling its promise of projecting changes that were sensitive to policy. The lack of significance of some policy variables may have resulted from insufficient variation in drivers over our study area or time period, but also suggests that drivers of land use change in exurban environments may differ from those identified for urban areas.
机译:私有农村土地的开发会严重破坏景观,对生态系统服务可能产生负面影响。因此,超出城市边缘的土地利用趋势模型对于制定管理这些环境影响的政策很有用。但是,土地利用变化模型主要应用于城市环境,目前尚不清楚它们是否能够充分预测城市外人口的增长。这项研究比较了两种城市增长模式预测24年内弗吉尼亚州中北部和马里兰州西部郊区发展的能力。基于模式的城市增长模型(例如SLEUTH)已被广泛使用,但很大程度上是模仿历史条件下出现的模式,而不是让土地所有者的决策来预测变化。相反,空间明晰的计量经济学模型(例如本研究中评估的互补对数对数风险)将土地所有者的选择建模为受市场和监管约束的利润最大化行为。我们通过将模型预测与以像素和县为单位的观察到的郊区转换进行了比较,评估了这两种基于栅格的模型。 SLEUTH模型在匹配县级范围内的新增长总量上比在像素级上更为成功,这表明在郊区地区最合适的使用是SLEUTH模型,它是一种预先预测潜在的自然资源大规模损失的钝器。计量经济学模型在两个方面的表现均显着优于SLEUTH,尽管它未能完全成功地实现预测对政策敏感的变更的承诺。在我们的研究区域或时间段内,驱动因素变化不足可能导致某些政策变量的重要性不足,但也表明,郊区环境中土地使用变化的驱动因素可能与城市地区的驱动因素有所不同。

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