Integrating Fragmented Heritage: Cluster Governance for Regional Conservation in Chaoshan, China

To address the long-standing fragmentation of regional cultural heritage, this study examined heritage cluster governance in the Chaoshan region of Guangdong, China. It identified cultural heritage clusters through a combined assessment of spatial aggregation intensity and conservation and revitalization potential for both tangible and intangible heritage. It then used circuit theory to construct cultural heritage corridors and reveal the spatial relationships among clusters. The results identified 12 heritage clusters at various levels, connected by 14 major corridors and 33 general corridors, forming a regional spatial pattern characterized by three core areas, multiple supporting nodes, and axial linkages. On this basis, the study proposes differentiated governance strategies for priority conservation and revitalization clusters, potential development and cultivation clusters, and basic conservation and monitoring clusters, and develops an analytical framework that links diagnosis, connectivity, and strategy. This study provides a spatial basis for the integrated conservation and revitalization of cultural heritage in the Chaoshan region, and can serve as a useful reference for heritage-rich regions seeking to move from fragmented protection toward coordinated regional governance.

Authors

Institutions

Publication Details

Journal
Journal of Resources and Ecology
Published
2026-10-27
DOI
https://doi.org/10.5814/j.issn.1674-764x.2026.05.018
Primary Topic
Cultural Heritage Management and Preservation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrating Fragmented Heritage: Cluster Governance for Regional Conservation in Chaoshan, China

Wang Ruijin, Jia Shanshan, Sun Ying
8 links
Journal of Resources and Ecology
Cultural Heritage Management and Preservation
article

Integrating Fragmented Heritage: Cluster Governance for Regional Conservation in Chaoshan, China

Wang Ruijin, Jia Shanshan, Sun Ying
article en

Abstract

To address the long-standing fragmentation of regional cultural heritage, this study examined heritage cluster governance in the Chaoshan region of Guangdong, China. It identified cultural heritage clusters through a combined assessment of spatial aggregation intensity and conservation and revitalization potential for both tangible and intangible heritage. It then used circuit theory to construct cultural heritage corridors and reveal the spatial relationships among clusters. The results identified 12 heritage clusters at various levels, connected by 14 major corridors and 33 general corridors, forming a regional spatial pattern characterized by three core areas, multiple supporting nodes, and axial linkages. On this basis, the study proposes differentiated governance strategies for priority conservation and revitalization clusters, potential development and cultivation clusters, and basic conservation and monitoring clusters, and develops an analytical framework that links diagnosis, connectivity, and strategy. This study provides a spatial basis for the integrated conservation and revitalization of cultural heritage in the Chaoshan region, and can serve as a useful reference for heritage-rich regions seeking to move from fragmented protection toward coordinated regional governance.

Journal of Resources and EcologyVol. 17(5)
Guangdong University Of Finances and Economics (CN), Southwest Forestry University (CN), East China Normal University (CN)
Openalex Percentile: Top 5%
Cultural Heritage Management and Preservation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon