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A comparison of nighttime lights data for urban energy research: Insights from scaling analysis in the US system of cities

机译:夜间照明数据用于城市能源研究的比较:美国城市系统的规模分析得出的见解

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Urban areas contribute to about 75% of global fossil fuel CO_2 emissions and are a primary driver of climate change. If greenhouse gas emissions for the top 20 emitting urban areas were aggregated into a one country, it would rank third behind China and the US. With urban areas forecasted to triple between 2010 and 2030 and urban population expected to increase by more than 2.5 billion, sustainable development will require a better understanding of how different types of urbanization affect energy use. However, there is a scarcity of data on energy use at the urban level that are available globally. Nighttime light satellite data have been shown to be related to energy use, but to date there has not been a systematic comparison of how well different sources of nighttime light data and their derived products can proxy electricity use. This paper fills this gap. First, we perform a comparative analysis of different types of nighttime light satellite data to proxy for electricity use for US cities. Second, we examine how the different types of nighttime light satellite data scale with the size of urban settlements and connect these findings to recent theoretical advances in scaling. We find that (1) all measures of nighttime light and urban electricity use in the US are strongly correlated and (2) different nighttime light-derived data can measure distinct urban energy characteristics such as energy infrastructure volume versus energy use. Our results do not show a clear best nighttime light proxy for total electricity consumption, despite of the use of higher spatial and temporal resolution data.
机译:城市地区约占全球化石燃料CO_2排放量的75%,是气候变化的主要驱动力。如果将排放量排名前20的城市地区的温室气体排放量汇总到一个国家中,它将排在中国和美国之后的第三位。预计到2010年至2030年,城市面积将增加两倍,而城市人口预计将增加25亿,可持续发展将需要更好地了解不同类型的城市化如何影响能源使用。但是,全球缺乏可用的城市能源使用数据。夜间光卫星数据已显示与能源使用有关,但迄今为止,尚未对夜间光数据的不同来源及其派生产品可替代电能的使用情况进行系统比较。本文填补了这一空白。首先,我们对不同类型的夜间照明卫星数据进行比较分析,以替代美国城市的用电情况。其次,我们研究了不同类型的夜间照明卫星数据如何随城市居住区的规模扩展,并将这些发现与扩展规模方面的最新理论进展联系起来。我们发现(1)在美国,所有夜间照明与城市用电量的测量指标都具有高度相关性;(2)不同的夜间照明数据可以测量不同的城市能源特征,例如能源基础设施量与能源使用。尽管使用了更高的时空分辨率数据,我们的结果也没有显示出总电量的最佳最佳夜间照明替代品。

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