Urban functional area identification and spatial accessibility analysis based on big data

Jing Wang; Jinfeng Yan

doi:10.1117/12.3020981

19 January 2024 Urban functional area identification and spatial accessibility analysis based on big data

Jing Wang, Jinfeng Yan

Proceedings Volume 12980, Fifth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2023); 129800B (2024) https://doi.org/10.1117/12.3020981
Event: Fifth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2023), 2023, Lianyungang, China

Abstract

This paper selects Zhifu District of Yantai City as the study area, takes the traffic community formed by OSM data (road network) as the identification unit of functional areas, constructs the weight model of "influence-space area", and uses POI (point of interest) data and Sentinel-2A image data to identify functional areas. Based on the theory of space syntax, this paper analyzes the spatial accessibility of urban roads through the variables of integration degree and choice degree. The results showed that the northern Zhifu core street space accessibility is higher, with more perfect function types, south street space accessibility is poorer, and function type is relatively single, corresponding improving measures are put forward accordingly.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jing Wang and Jinfeng Yan "Urban functional area identification and spatial accessibility analysis based on big data", Proc. SPIE 12980, Fifth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2023), 129800B (19 January 2024); https://doi.org/10.1117/12.3020981

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