Analysis of the spatio-temporal characteristics of intercity travel based on SVD and complex network: take Bohai Rim City Group as an example

Wang, Zifan; Nie, Wanjie; Lin, Tinglan

doi:10.1117/12.2627839

Cited by 2 publications

(4 citation statements)

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“…The third finding is that the Non-negative Matrix Factorization (NMF) can intuitively extract the potential intercity mobility patterns. This fills in the gaps that other decomposition methods leave, producing less interpretable results as given in [20,21]. This study provides a systematic workflow to characterize the intercity mobility patterns for the GBA in China, especially from the perspective of intercity population mobility flow.…”

Section: Discussionmentioning

confidence: 97%

“…Based upon time-series intercity mobility flow matrix, we use a rank reduction algorithm to identify the potential intercity mobility patterns. The regular rank reduction algorithms, such as PCA (principal component analysis) [33], ICA (independent component analysis) [34], and SVD (singular value decomposition) [12,20,21] have been widely used to extract a low number of latent components from high-dimensional data. However, traditional rank reduction algorithms can not guarantee the non-negativity of the results, even when the input initial matrix elements are all positive, leading to interpretability issues.…”

Section: Intercity Mobility Pattern Recognitionmentioning

confidence: 99%

“…However, such a method mainly analyzes the intercity patterns from the average level at a certain time or stage and fails to effectively characterize the dynamic variations of urban connection. To deal with this issue, existing studies have used singular value decomposition (SVD) [20,21] to characterize the main intracity and intercity mobility patterns. However, one concern is that the obtained decomposition results are not strictly non-negative, leading to interpretability issues.…”

Section: Introductionmentioning

confidence: 99%

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Characterizing Intercity Mobility Patterns for the Greater Bay Area in China

Yin

2022

IJGI

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Understanding intercity mobility patterns is important for future urban planning, in which the intensity of intercity mobility indicates the degree of urban integration development. This study investigates the intercity mobility patterns of the Greater Bay Area (GBA) in China. The proposed workflow starts by analyzing intercity mobility characteristics, proceeds to model the spatial-temporal heterogeneity of intercity mobility structures, and then identifies the intercity mobility patterns. We first conduct a complex network analysis, based on weighted degrees and the PageRank algorithm, to measure intercity mobility characteristics. Next, we calculate the Normalized Levenshtein Distance for Population Mobility Structure (NLPMS) to quantify the differences in intercity mobility structures, and we use the Non-negative Matrix Factorization (NMF) to identify intercity mobility patterns. Our results showed an evident ‘Core-Periphery’ differentiation characterized by intercity mobility, with Guangzhou and Shenzhen as the two core cities. An obvious daily intercity commuting pattern was found between Guangzhou and Foshan, and between Shenzhen and Dongguan cities at working time. This pattern, however, changes during the holidays. This is because people move from the core cities to peripheral cities at the beginning of holidays and return at the end of holidays. This study concludes that Guangzhou and Foshan have formed a relatively stable intercity mobility pattern, and the Shenzhen–Dongguan–Huizhou metropolitan area has been gradually formed.

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Section: Discussionmentioning

confidence: 97%

Section: Intercity Mobility Pattern Recognitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Characterizing Intercity Mobility Patterns for the Greater Bay Area in China

Yin

2022

IJGI

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“…Te outcome of this study can be useful for the development of policies that can potentially help fulfll the mobility needs of city inhabitants. From the perspective of complex network theory, Wang et al [40] explored the spatial structure characteristics of intercity travel patterns during National Day, identifying aspects such as the "small world" phenomenon and a core-periphery radial structure. In addition, Kiashemshaki et al [41] utilized ego-centric networks to model the travel patterns of Finnish cities, studying shifts in mobility patterns during the COVID-19 pandemic.…”

Section: Introductionmentioning

confidence: 99%

Expressway Usage Pattern Analysis Based on Tollgate Data: A Case Study of the Shandong Province, China

Wang,

Ding,

Wang

et al. 2023

Journal of Advanced Transportation

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Expressway transportation is an essential part of regional development. An efficient expressway system can enhance cities’ connectivity and coordinate long-distance trips between urban areas. Understanding how travel demand affects the flow of expressways is crucial to designing an efficient expressway management system. However, congested expressways are substantial obstacles to unimpeded expressway travel. Here, we explore the relationship between demand origin locations and congested expressways. We extract the time-varying OD demand matrix from empirical tollgate data collected in Shandong province, China. The incremental traffic assignment method is introduced to obtain the traffic flow of expressway road segments. It was found that congested expressways were generated due to only a few origin locations. In addition, expressway congestion during peak hours could be effectively alleviated by controlling the travel demand of these origin locations. Therefore, the proposed method can provide a novel perspective for expressway management.

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Analysis of the spatio-temporal characteristics of intercity travel based on SVD and complex network: take Bohai Rim City Group as an example

Cited by 2 publications

References 1 publication

Characterizing Intercity Mobility Patterns for the Greater Bay Area in China

Characterizing Intercity Mobility Patterns for the Greater Bay Area in China

Expressway Usage Pattern Analysis Based on Tollgate Data: A Case Study of the Shandong Province, China

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