Abstract
Abstract This article focuses on Shanghai as a case study and utilizes various factors such as points of interest, nighttime lights, land use, road networks, and Digital Elevation Model to examine the spatial distribution of population. A random forest model is constructed to decompose the population of streets in 2022 into a 100-m grid. The study then assesses the spatial accessibility of basic education resources using a cost-weighted distance method and evaluates the supply-demand match of these resources using an improved potential model. The findings reveal the following: (1) At the street level, the spatialization of population distribution achieves a superior fit (R 2 = 0.7679) with statistical data compared to the WorldPop dataset. The overall population distribution in Shanghai exhibits a spatial pattern characterized by “one main area, two sub-areas, and multiple scattered points,” effectively capturing the distribution characteristics. (2) The overall spatial accessibility of basic education resources in Shanghai is favorable, with 100% of residents able to reach the nearest primary school, junior high school, and high school within a 30-min travel time. However, significant urban–rural disparities are observed, as areas with dense facilities and well-developed transportation exhibit better accessibility. Streets with poorer accessibility tend to be concentrated in larger jurisdictional areas with abundant forests near the sea. (3) The main urban area of Shanghai and the districts of Songjiang and Fengxian demonstrate a relatively balanced supply and demand of basic education resources in several areas. However, there are still regions within these areas where resource allocation could be further strengthened.
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