Regional assessment of urban impacts on landcover and open space finds a smart urban growth policy performs little better than business as usual

区域评估城市对土地覆盖和开放空间的影响发现,智慧城市增长政策的效果与维持现状相比并无太大优势。

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Abstract

Assessment of landscape change is critical for attainment of regional sustainability goals. Urban growth assessments are needed because over half the global population now lives in cities, which impact biodiversity, ecosystem structure and ecological processes. Open space protection is needed to preserve these attributes, and provide the resources humans need. The San Francisco Bay Area, California, is challenged to accommodate a population increase of 3.07 million while maintaining the region's ecosystems and biodiversity. Our analysis of 9275 km² in the Bay Area links historic trends for three measures: urban growth, protected open space, and landcover types over the last 70 years to future 2050 projections of urban growth and open space. Protected open space totaled 348 km² (3.7% of the area) in 1940, and expanded to 2221 km² (20.2%) currently. An additional 1038 km² of protected open space is targeted (35.1%). Urban area historically increased from 396.5 km² to 2239 km² (24.1% of the area). Urban growth during this time mostly occurred at the expense of agricultural landscapes (62.9%) rather than natural vegetation. Smart Growth development has been advanced as a preferred alternative in many planning circles, but we found that it conserved only marginally more open space than Business-as-usual when using an urban growth model to portray policies for future urban growth. Scenarios to 2050 suggest urban development on non-urban lands of 1091, 956, or 179 km², under Business-as-usual, Smart Growth and Infill policy growth scenarios, respectively. The Smart Growth policy converts 88% of natural lands and agriculture used by Business-as-usual, while Infill used only 40% of those lands. Given the historic rate of urban growth, 0.25%/year, and limited space available, the Infill scenario is recommended. While the data may differ, the use of an historic and future framework to track these three variables can be easily applied to other metropolitan areas.

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