Abstract
Urban areas involve different functions that attract individuals and fit personal needs. Understanding the distribution and combination of these functions in a specific district is significant for urban development in cities. Many researchers have already studied the methods of identifying the dominant functions in a district. However, the degree of collection and the representativeness of a function in a district are controlled not only by its number in the district but also by the number outside this district and a number of other functions. Thus, this study proposed a quantitative method to identify urban functions, using Fisher’s exact test and point of interest (POI) data, applied in determining the urban districts within the Sixth Ring Road in Beijing. To begin with, we defined a functional score based on three statistical features: the p-value, odds-ratio, and the frequency of each POI tag. The p-value and odds-ratio resulted from a statistical significance test, the Fisher’s exact test. Next, we ran a k-modes clustering algorithm to classify all urban districts in accordance with the score of each function and their combination in one district, and then we detected four different groups, namely, Work and Tourism Mixed-developed district, Mixed-developed Residential district, Developing Greenland district, and Mixed Recreation district. Compared with the other identifying methods, our method had good performance in identifying functions, except for transportation. In addition, the Coincidence Degree was used to evaluate the accuracy of classification. In our study, the total accuracy of identifying urban districts was 83.7%. Overall, the proposed identifying method provides an additional method to the various methods used to identify functions. Additionally, analyzing urban spatial structure can be simpler, which has certain theoretical and practical value for urban geospatial planning.
Highlights
Urban functions, such as residence, industries, transportation, and business, influence human activities [1]
It is worth noting that the combination of those functions that belong to the same district was a prerequisite for our identification and classification of urban districts
We discovered that urban functions are mostly mixed in a range of 1000 × 1000 square meters within the Sixth Ring Road of Beijing
Summary
Urban functions, such as residence, industries, transportation, and business, influence human activities [1]. It is natural that most of these functions do not appear individually as a single function in a particular area. Identifying urban functions and their combination precisely can give us a better opportunity to answer some important questions on the relationships between humans and urban environments, for example, in discovering different urban districts with different urban functions. Researchers [1,6,7,8,9,10,11] have conducted many studies on urban functions and districts that employ POIs, which are able to lead to a better understanding of individual-level and social-level utilization of urban space. POI data can help to understand land use planning, at the semantic level, and at the quantitative level
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