Identification of urban functions enhancement and weakening based on urban land use conversion: A case study of Changchun, China

Zhou, Guozhong; Li, Chenggu; Zhang, Jing

doi:10.1371/journal.pone.0234522

Cited by 12 publications

(6 citation statements)

References 39 publications

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“…Indeed, the flows we observe mainly represent the activity-oriented mobility behaviors of the population in the considered metropolitan area, involving not only people displacements, but also their interaction with the frequented zones in a city. This brings our approach close to the rich literature on urban functions and urban functionality [58]. However, our approach is fundamentally different from classical studies in urban planning and geographical information science.…”

Section: Dataset Modeling and Methodologymentioning

confidence: 83%

Data-driven Mobility Analysis and Modeling: Typical and Confined Life of a Metropolitan Population

Fanticelli

Rabenjamina

Viana

et al. 2022

ACM Trans. Spatial Algorithms Syst.

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The idea of using mobile phone data to understand the impact of the Covid-19 pandemic and that of the sanitary constraints associated with it on human mobility imposed itself as evidence in most countries. This work uses spatiotemporal aggregated mobile phone data provided by a major French telecom operator, covering a geographical region centered on Paris for early 2020, i.e., periods before and during the first French lockdown. An essential property of this data is its fine-grained spatial resolution, which, to the best of our knowledge, is unique in the COVID-related mobility literature. Contrarily to regions or country-wide resolution, it describes population mobility flows among zones ranging from \(0.025~\texttt {km}^2 \) to \(5.40~\texttt {km}^2 \) , corresponding to 326 aggregated zones over the total area of \(93.76~\texttt {km}^2 \) of the city of Paris. We perform a data-driven mobility investigation and modeling to quantify (in space and time) the population attendance and visiting flows in different urban areas. Second, when looking at periods both before and during the lockdown, we quantify the consequences of mobility restrictions and decisions on an urban scale. For this, per zone, we define a so-called signature , which captures behaviors in terms of population attendance in the corresponding geographical region (i.e., their land use) and allows us automatically detect activity, residential, and outlier areas. We then study three different types of graph centrality , quantifying the importance of each zone in a time-dependent weighted graph according to the habits in the mobility of the population. Combining the three centrality measures, we compute per zone of the city, its impact-factor , and employ it to quantify the global importance of zones according to the population mobility. Our results firstly reveal the population’s daily zone preferences in terms of attendance and mobility, with a high concentration on business and touristic zones. Second, results show that the lockdown mobility restrictions significantly reduced visitation and attendance patterns on zones, mainly in central Paris, and considerably changed the mobility habits of the population. As a side effect, most zones identified as mainly having activity-related population attendance in typical periods became residential-related zones during the lockdown, turning the entire city into a residential-like area. Shorter distance displacement restrictions imposed by the lockdown increased visitation to more “local” zones, i.e., close to the population’s primary residence. Decentralization was also favored by the paths preferences of the still-moving population. On the other side, “jogging activities” allowing people to be outside their residences impacted parks visitation, increasing their visitation during the lockdown. By combining the impact factor and the signatures of the zones, we notice that areas with a higher impact factor are more likely to maintain regular land use during the lockdown.

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Section: Dataset Modeling and Methodologymentioning

confidence: 83%

Data-driven Mobility Analysis and Modeling: Typical and Confined Life of a Metropolitan Population

Fanticelli

Rabenjamina

Viana

et al. 2022

ACM Trans. Spatial Algorithms Syst.

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“…Zhen et al discussed the comprehensive situation in Hebei Province based on the flows of urban economy, transportation, information, and finance between cities in the provinces in China [14]. Zhou et al analyzed the enhancement and weakening of urban functions and their spatial differences based on overlay analysis and transition matrix [15]. Chai et al discussed the differences in urban functions among the cities in the economic belt of the Yangtze River.…”

Section: Urban Functionmentioning

confidence: 99%

Analyzing the Direction of Urban Function Renewal Based on the Complex Network

Cheng,

Luo

2023

Sustainability

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Urban function renewal is essential for modern megacities’ urban planning and economic developments. This paper investigates the urban function renewal in Shenzhen, China based on a complex network method. According to the points of interest and the location quotient, the dominant urban functions in each district are discussed. After computing conditional probability, the interdependence of urban functions is analyzed. The complex networks of the functions and the corresponding clusters are presented to examine the relationship and the overall features of the functions, and the features of the function clusters, respectively. The average degree and average weighted degree of the main function categories of the functions are computed to explore the features of the function classification. The urban functions’ renewal potential index is calculated to show the potential of the non-dominant functions renewing to the dominant ones in the coming years. The difficulty index of the urban function renewal in each district is presented, and the difficulty degree of the original d-ominant function group renewing to a new one is obtained. The results show that more dominant urban functions have a significant probability of being dominant ones in a district; the functions of hotels and life services are essential in the planning and development in Shenzhen; and the districts with better economic levels have greater values of the difficulty of the urban function renewal. Then, the function renewal direction in Shenzhen is analyzed, and some policy implications are given.

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“…This method breaks through the limitations of traditional optical microscopes by using synthetic aperture, optimization theory, and other related technologies to obtain high-resolution images using low-magnification objective lenses. Based on the advantages of FPM, in just a few years of development, it has been applied in many fields, such as bioimaging of living samples [ 15 ], cell detection [ 16 ], cell counting [ 17 , 18 ], and digital pathology [ 19 ]. In recent years, FPM has been improved in terms of implementation methods [ 20 , 21 , 22 ], imaging performance [ 23 , 24 , 25 ], and reconstruction efficiency [ 26 , 27 , 28 ].…”

Section: Related Workmentioning

confidence: 99%

Peripheral Blood Leukocyte Detection Based on an Improved Detection Transformer Algorithm

Li,

Fang,

Wang

et al. 2023

Sensors

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The combination of a blood cell analyzer and artificial microscopy to detect white blood cells is used in hospitals. Blood cell analyzers not only have large throughput, but they also cannot detect cell morphology; although artificial microscopy has high accuracy, it is inefficient and prone to missed detections. In view of the above problems, a method based on Fourier ptychographic microscopy (FPM) and deep learning to detect peripheral blood leukocytes is proposed in this paper. Firstly, high-resolution and wide-field microscopic images of human peripheral blood cells are obtained using the FPM system, and the cell image data are enhanced with DCGANs (deep convolution generative adversarial networks) to construct datasets for performance evaluation. Then, an improved DETR (detection transformer) algorithm is proposed to improve the detection accuracy of small white blood cell targets; that is, the residual module Conv Block in the feature extraction part of the DETR network is improved to reduce the problem of information loss caused by downsampling. Finally, CIOU (complete intersection over union) is introduced as the bounding box loss function, which avoids the problem that GIOU (generalized intersection over union) is difficult to optimize when the two boxes are far away and the convergence speed is faster. The experimental results show that the mAP of the improved DETR algorithm in the detection of human peripheral white blood cells is 0.936. In addition, this algorithm is compared with other convolutional neural networks in terms of average accuracy, parameters, and number of inference frames per second, which verifies the feasibility of this method in microscopic medical image detection.

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Identification of urban functions enhancement and weakening based on urban land use conversion: A case study of Changchun, China

Cited by 12 publications

References 39 publications

Data-driven Mobility Analysis and Modeling: Typical and Confined Life of a Metropolitan Population

Data-driven Mobility Analysis and Modeling: Typical and Confined Life of a Metropolitan Population

Analyzing the Direction of Urban Function Renewal Based on the Complex Network

Peripheral Blood Leukocyte Detection Based on an Improved Detection Transformer Algorithm

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