科研之友
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摘要
Service area research is one of the pivotal topics in Urban Geography. This article first put forward a model of urban population estimation. And on the basis we measured the size and distribution of population in downtown Shanghai, China. The population model was confirmed well by the traditional survey model. Then we extracted a 1-month actual-time data set contains geo-location by collecting in Sina Weibo data, and generated Voronoi diagram by these data which denoted the service patches. We assigned population to each patch. Second part, we proposed a shortest distance algorithm, a minimum time algorithm and an improved p-median algorithm, took advantages of these three methods to divide the service area of metro stations based on patches. Subsequently, we computed the service population in each service area. Last, we took metro line 1 and 2 as examples to research the relationship among 3 location-allocation methods in detail. The results showed that: The spatial distribution of population of the core city in Shanghai emerged a descending trend from center to periphery clearly. All indicators (including area, population, distance and time) in central city within inner ring road have changed little compared with the region between inner and outer ring road. Yet the improved p-median algorithm has a certain effect of optimization. It presented a scientific and rational travel scheme for citizens cost smallest price to select better starting metro station. The study results should contribute to theoretical and technical support for location-allocation of public service facilities.
