Analysis of Spatiotemporal Dynamics and Driving Mechanisms of Cultural Heritage Distribution Along the Jiangnan Canal, China

Runmo Liu, Dan Meng (), Ming Wang, Huili Gong and Xiaojuan Li
Additional contact information
Runmo Liu: College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
Dan Meng: College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
Ming Wang: College of History, Capital Normal University, Beijing 100048, China
Huili Gong: College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
Xiaojuan Li: College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China

Sustainability, 2025, vol. 17, issue 11, 1-25

Abstract: As a crucial component of the Beijing–Hangzhou Grand Canal’s hydraulic engineering, the Jiangnan Canal has historically played a pivotal role in China’s development as a key hydraulic infrastructure. This water conservancy project, connecting northern and southern water systems, not only facilitated regional economic integration but also nurtured unique cultural landscapes along its course. The Jiangnan Canal and its adjacent cities were selected as the study area to systematically investigate 334 tangible cultural heritage (TCH) sites and 420 intangible cultural heritage (ICH) elements. Through integrated Geographical Information System (GIS) spatial analyses—encompassing nearest neighbor index, kernel density estimation, standard deviation ellipse assessment, multi-ring buffer zoning, and Geodetector modeling, the spatiotemporal distribution features of cultural heritage were quantitatively characterized, with a focus on identifying the underlying driving factors shaping its spatial configuration. The analysis yields four main findings: (1) both TCH and ICH exhibit significant spatial clustering patterns across historical periods, with TCH distribution displaying an axis-core structure centered on the canal, whereas ICH evolved from dispersed to clustered configurations. (2) The center of gravity of TCH is primarily around Taihu Lake, while that of ICH is mainly on the south side of Taihu Lake, and the direction of distribution of both is consistent with the direction of the canal. (3) Multi-ring buffer analysis indicates that 77.2% of TCH and 49.8% of ICH clusters are concentrated within 0–10 km of the canal, demonstrating distinct spatial patterns: TCH exhibits a gradual canal-dependent density decrease with distance, whereas ICH reveals multifactorial spatial dynamics. (4) Human activity factors, particularly nighttime light intensity, are identified as predominant drivers of heritage distribution patterns, with natural environmental factors exerting comparatively weaker influence. These findings provide empirical support for developing differentiated conservation strategies for canal-related cultural heritage. The methodology offers replicable frameworks for analyzing heritage corridors in complex historical landscapes, contributing to both applied conservation practices and theoretical advancements in cultural geography.

Keywords: tangible cultural heritage; intangible cultural heritage; GIS; the Jiangnan Canal; spatiotemporal distribution; influencing factors; geodetector (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/17/11/5026/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/11/5026/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:11:p:5026-:d:1668429

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().