论文标题
偏远的细粒度，多才多艺的索引，以表征位置级别的乡村
A fine-grained, versatile index of remoteness to characterize place-level rurality
论文作者
论文摘要
农村城市分类对于分析整个农村城市连续性的地理，人口，环境或社会经济过程至关重要。但是，现有的县级分类可能会忽略乡村县内部的变化，如果感兴趣的规模处于地位级别或更精细的情况下，这可能会出现问题。此外，随着时间的流逝，现有的农村城市分类通常是不一致的，因此阻碍了对农村地区动态的长期分析。我们开发了一种基于距离的方法来基于简单的输入数据生成位置级别的远程估计。我们根据1980年至2010年美国的位置级别人口数据创建远程指数。所提出的指数可推广到数据筛选环境和较早的时间段，并基于给定位置与不同人口最接近的地方的距离，并允许对农村 - 郊区流程的良好粒度，时间一致的分析。
Rural-urban classifications are essential for analyzing geographic, demographic, environmental, or socioeconomic processes across the rural-urban continuum. However, existing county-level classifications may ignore the within-county variations of rurality, which can be problematic if the scale of interest is at the place-level or finer. Moreover, existing rural-urban classification are often inconsistent over time and thus, impede the long-term analysis of rural-urban dynamics. We developed a distance-based method to generate place-level remoteness estimates based on simple input data. We create our remoteness index based on place-level population data for the U.S. from 1980 to 2010. The proposed index is generalizable to data-scarce environments and earlier time periods and is based on the distances of a given place to the nearest places of different population sizes, and allows for fine-grained, temporally consistent analyses of rural-urban processes.
