Zone division and extraction of historic area based on big data

ABSTRACT

Although zoning has great potential in coordinating regional development and destination management, it is challenging to derive an optimal zoning method in the historic district. To address this challenge, this paper proposes a zone division method attempting to balance tourists’ and residents’ spatial demands and realizing urban historic area sustainable development. A 3-zones (Tourist active zone, Local community zone, and Buffer zone) plan is put forward based on a case study of the Qianmen area in Beijing, China. Then zone extraction is conducted with two kinds of big data, Points of Interests (POI) and Mobile Phone Signal (MPS). The Thiessen polygon-based method to divide the tourists’ concentrated area and a fishnet-based density method to distinguish the area of residents mainly living are used to help identify borderlines of different zones. A survey map for tourists and residents is used to verify the zone extraction results. Subsequently, zone management strategies are suggested for different zones improvement. This discussion contributes to overcoming the traditional methods’ defects in subarea-scale research with scientifically sound and practical.

KEYWORDS:

• Zone division
• zone extraction
• big data
• tourists and residents
• historic area
• China

Acknowledgements

The author gratefully acknowledges the financial support of the National Natural Science Foundation of China (NSFC) through grant number 41801139, and the Strategic Priority Research Program of the Chinese Academy of Sciences (CAS) through XDA23100302. Thanks for data support of China Unicom Co. Ltd and Yugang Fan from Microsoft, and the consultation of officials from Qianmen district office.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant number 40181173] and the Strategic Priority Research Program of the Chinese Academy of Sciences (CAS) through [XDA23100302].