Identification of Urban Functional Areas and Their Mixing Degree Using Point of Interest Analyses

Li, Ya; Liu, Chunxia; Li, Yuechen

doi:10.3390/land11070996

Cited by 24 publications

(15 citation statements)

References 29 publications

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“…This subjectivity in POI reclassification undermines the objectivity and consistency of the results. Additionally, the weighting system used to compensate for the inherent lack 45,62,69 of spatial scale characteristics in point-type spatial data like POI data is also an important consideration. Conventional weight values are assigned based on manual experience or expert judgment.…”

Section: Discussionmentioning

confidence: 99%

Accurate Identification of Micro-scale Urban Functional Zones from the Perspective of Dialectical Materialism

Zhang

2023

Preprint

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With the advancement of global urbanization, accurate identification of urban functional zones has become a crucial task for the high-quality development of cities. Traditional methods that rely on POI data are insufficient to accurately identify micro-scale urban functional zones. Thus, this study proposes a novel method for identifying urban functional zones based on VOI (Volume of Interest) data and applies it to a small region in Hong Kong for comparative research. Subsequently, the identification accuracy of the two methods is assessed using a confusion matrix and the Kappa Coefficient. The results show that the VOI data contains richer and more comprehensive urban spatial information compared to POI data, enabling a superior representation of connections and influences among different zones within cities. The study can be applied to analyse micro-scale urban functional zones in other cities, providing a new perspective for the in-depth research.

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Section: Discussionmentioning

confidence: 99%

Accurate Identification of Micro-scale Urban Functional Zones from the Perspective of Dialectical Materialism

Zhang

2023

Preprint

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“…In this paper, we use the importance function to calculate the weights of each type of POI, as shown in Equation 1. MDA normalization can help to eliminate the effect of imbalance between POI data, making the importance scores more reliable and comparable as shown in Equation 2 [11] .…”

Section: Random Forest Algorithmmentioning

confidence: 99%

Identification and spatio-temporal characterization of urban functional areas based on POI data

Peng,

Yang,

Cai

et al. 2024

Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023)

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Accurate identification of urban functional areas is of great significance to the scientific management and intelligent services of cities. Aiming at the problems of low accuracy and subjectivity of current identification methods, a quantitative identification method combining random forest and frequency density algorithm is proposed. Firstly, the frequency density calculation method is constructed by assigning weights to 19 POI types through random forest, and then the spatiotemporal feature analysis is performed on the distribution of urban functional areas identified in 2016 and 2021, respectively; secondly, the influence of rank scaling is considered, and Jingjiang Palace Street is used as an example for functional area identification; finally, a test set is selected for validation and comparison experiments. The results show that the accuracy rate of the method in this paper reaches 85.55%.

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“…Moreover, they revised the information entropy model to develop spatial entropy and temporal entropy. Li et al 24 typically applied random forest to determine the weights of POI, then they used the urban function calculation model to identify single dominant functional areas and information entropy to calculate the mixing degree of urban functions. Although some scholars investigated the identification of mixed-use functional areas and their mixing degree, the identification and analysis of mixed-use urban functions are not in-depth.…”

Section: Introductionmentioning

confidence: 99%

Identification and prediction of mixed-use functional areas supported by POI data in Jinan City of China

Zheng

Wang

Shang

et al. 2023

Sci Rep

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The urban development of China is changing from incremental expansion to stock renewal mode. The study of urban functional areas has become one of the important fundamental works in current urban renewal and high-quality urban development. In recent years, big spatiotemporal data has been well applied in the urban function field. However, the study of spatial–temporal evolution characteristics and forecasting optimization for mixed-use urban functional areas has not been examined well. Thus, in this study, we proposed a new approach that applies a revised information entropy method to analyze the degrees of mixing for urban functional areas. We applied our approach in Jinan City, Shandong Province as the study area. We used Point-of-Interest, OpenStreetMap and other datasets to identify the mixed-use urban functional areas in Jinan. Then, the CA–Markov model simulated the urban layout in 2025. The results showed that: (1) the combination of road network and kernel density method has the highest accuracy of identifying urban functional areas. (2)The mixing degree model is constructed by using the improved information entropy, which makes up for the shortcoming of identifying the mixed functional areas simply by the frequency ratio of POI data. (3) The “residence and business” functional area has the highest proportion in the central area of Jinan from 2015 to 2020, and the total area of mixed-use unban functional areas continuously increased during this period. (4) The total area of the central area in Jinan has significantly increased in 2025. The optimization of urban functions should expand mixed-use functional areas and increase the proportion of infrastructure. Also, Jinan should improve the efficiency of space development.

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Identification of Urban Functional Areas and Their Mixing Degree Using Point of Interest Analyses

Cited by 24 publications

References 29 publications

Accurate Identification of Micro-scale Urban Functional Zones from the Perspective of Dialectical Materialism

Accurate Identification of Micro-scale Urban Functional Zones from the Perspective of Dialectical Materialism

Identification and spatio-temporal characterization of urban functional areas based on POI data

Identification and prediction of mixed-use functional areas supported by POI data in Jinan City of China

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