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Understanding Spatial Dependency Among Spatial Interactions

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Spatial Data and Intelligence (SpatialDI 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14619))

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Abstract

Spatial dependency exhibits special regularities in spatial interactions. Measuring spatial dependency among spatial interactions can help discover interesting interaction patterns and clusters. Although some metrics have been set up, it is still unclear what potentially affects the presence of spatial dependency among spatial interactions. Thus, we propose an analytical framework to better understand spatial dependency among spatial interactions. First, we define spatial weight matrix for spatial interactions, and then extend Moran’s I and LISA to spatial interactions. Second, we test factors such as first-order spatial autocorrelation and distance decay effect that influence the degree of spatial dependency among spatial interactions. Third, we construct a spatial econometric model for spatial interaction to demonstrate the significance of spatial dependency. The proposed analytical framework is applied in synthetic data and Beijing taxi flows. Results show that the spatial dependency among spatial interactions is positively correlated to the first-order spatial autocorrelation, which is affected by the distance decay effect under a gravity model. Incorporating spatial dependency into a spatial econometric interaction model can also improve its performance.

Supported by the National Natural Science Foundation of China (grant no. 41971331).

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Authors and Affiliations

  1. Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing, 100871, China

    Yong Gao, Haohan Meng & Yu Liu

  2. State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

    Tao Pei

Authors
  1. Yong Gao
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  2. Haohan Meng
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  3. Tao Pei
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  4. Yu Liu
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Corresponding author

Correspondence to Yong Gao .

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Editors and Affiliations

  1. Renmin University of China, Beijing, China

    Xiaofeng Meng

  2. Nanjing Normal University, Nanjing, China

    Xueying Zhang

  3. Beijing University of Chemical Technology, Beijing, China

    Danhuai Guo

  4. Nanjing Normal University, Nanjing, China

    Di Hu

  5. Huazhong University of Science and Technology, Wuhan, China

    Bolong Zheng

  6. Hefei University of Technology, Hefei, China

    Chunju Zhang

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Gao, Y., Meng, H., Pei, T., Liu, Y. (2024). Understanding Spatial Dependency Among Spatial Interactions. In: Meng, X., Zhang, X., Guo, D., Hu, D., Zheng, B., Zhang, C. (eds) Spatial Data and Intelligence. SpatialDI 2024. Lecture Notes in Computer Science, vol 14619. Springer, Singapore. https://doi.org/10.1007/978-981-97-2966-1_3

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  • DOI: https://doi.org/10.1007/978-981-97-2966-1_3

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-2965-4

  • Online ISBN: 978-981-97-2966-1

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