Abstract：Poor mountainous regions in China suffer from economic underdevelopment, inconvenient transportation, scattered population distribution, and fast-changing residential spatial pattern. These make the study of spatial distribution changes of primary and secondary schools in these regions critical for improving education equality. By using the case of Song County in the poor mountainous region of western Henan Province, this study acquired long-term school data (1997, 2007, and 2015) , and analyzed the changes in spatial pattern and spatial accessibility of these schools employing the trend surface analysis technique and gravity model. The results show that: (1) Primary and secondary schools in Song County were partially concentrated in areas with some terrain conditions. Primary schools were found more in the hilly and low-mountainous areas, and secondary schools concentrated in the hilly areas. (2) School merges decreased the total number of institutions and the differences in the number of schools among different villages, and the trend line became flat gradually. (3) The Cv value of the Voronoi model shows that schools followed an aggregated distribution pattern, and the degree of aggregation decreased as the number of schools decreased. The schools were mainly found in a region spreading from northeast to southwest in the northern part of the county, forming two narrow distribution bands along the two main roads (S247 and G311) . (4) School accessibilities were spatially varied in 2015. The longest distance to school was 160 times that of the shortest distance to school. Villages that had more than 10 km distance to schools were all found in the mid-mountainous and low-mountainous areas, constituting 26.1% of the total number. (5) Terrain, transportation, population, economy, and government policy were all influential to the distribution of educational resources in Song County.
Keyword：primary and secondary schools; spatial pattern; spatial accessibility; poor mountainous area; Song County;
【source】Progress in Geography 2018Vol.37