Spatio-Temporal Evolution and Driving Mechanisms of Linear Heritage Landscape Fragmentation Based on Heritage-Corrected Datasets: A Case Study of Nested Cumulative Buffer Zones of the Yangzhou Ancient Grand Canal

Urbanization-driven landscape fragmentation undermines the spatial continuity and cultural integrity of linear canal heritage. Traditional land-cover datasets often group heritage patches with general land-use classes, leading to systematic bias in fragmentation evaluation. Furthermore, analyses using a single buffer boundary fail to capture scale-dependent gradient changes along heritage corridors. Taking the Yangzhou Ancient Grand Canal, a representative living segment of the Grand Canal World Heritage Site, this study developed a heritage-corrected seven-class land-use raster dataset by defining heritage areas as an independent land-use category. Using multi-temporal datasets covering 2000–2025, we created three nested cumulative buffer zones (0–200 m, 0–1000 m, and 0–2000 m). Six landscape-fragmentation metrics were calculated in Fragstats 4.2. We constructed the comprehensive heritage-landscape fragmentation index (CHFI) via min–max normalization and the entropy-weight method. The Geodetector model was then applied to quantify both individual-factor explanatory power and interactive driving effects across multiple buffer scales. Our results identify 2010 as a critical turning point for fragmentation dynamics: fragmentation was partly reduced before 2010 but increased steadily afterwards. Fragmentation risks concentrate within the 0–200 m near-shore core zone; the composite index is diluted as the buffer expands from 0–200 m to 0–1000 m but stabilises thereafter. Fragmentation follows a dual-core driving pattern shaped by vegetation and impervious-surface conditions; fractional vegetation cover represents the most consistent dominant factor across all scales and time periods. Near-shore zones are jointly influenced by elevation and distance-to-river gradients, while outer buffer zones are mainly controlled by vegetation conditions. All factor interactions produce enhanced explanatory power. After 2010, near-shore areas underwent a phase shift toward strong multi-factor coupling. Fragmentation hotspots gradually became decoupled from heritage-site locations, suggesting heritage-related pressures act largely through combined factor effects rather than the direct influence of heritage sites themselves. This research offers a refined analytical framework for urban canal heritage and supports evidence-informed conservation and living-heritage revitalization.

Authors

Institutions

Publication Details

Journal
Land
Published
2026-10-29
DOI
https://doi.org/10.3390/land15112063
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spatio-Temporal Evolution and Driving Mechanisms of Linear Heritage Landscape Fragmentation Based on Heritage-Corrected Datasets: A Case Study of Nested Cumulative Buffer Zones of the Yangzhou Ancient Grand Canal

Ziyi Wan, Yanyan Wang, Xinyu Li
5 links
Land
Land Use and Ecosystem Services
article

Spatio-Temporal Evolution and Driving Mechanisms of Linear Heritage Landscape Fragmentation Based on Heritage-Corrected Datasets: A Case Study of Nested Cumulative Buffer Zones of the Yangzhou Ancient Grand Canal

Ziyi Wan, Yanyan Wang, Xinyu Li
article en

Abstract

Urbanization-driven landscape fragmentation undermines the spatial continuity and cultural integrity of linear canal heritage. Traditional land-cover datasets often group heritage patches with general land-use classes, leading to systematic bias in fragmentation evaluation. Furthermore, analyses using a single buffer boundary fail to capture scale-dependent gradient changes along heritage corridors. Taking the Yangzhou Ancient Grand Canal, a representative living segment of the Grand Canal World Heritage Site, this study developed a heritage-corrected seven-class land-use raster dataset by defining heritage areas as an independent land-use category. Using multi-temporal datasets covering 2000–2025, we created three nested cumulative buffer zones (0–200 m, 0–1000 m, and 0–2000 m). Six landscape-fragmentation metrics were calculated in Fragstats 4.2. We constructed the comprehensive heritage-landscape fragmentation index (CHFI) via min–max normalization and the entropy-weight method. The Geodetector model was then applied to quantify both individual-factor explanatory power and interactive driving effects across multiple buffer scales. Our results identify 2010 as a critical turning point for fragmentation dynamics: fragmentation was partly reduced before 2010 but increased steadily afterwards. Fragmentation risks concentrate within the 0–200 m near-shore core zone; the composite index is diluted as the buffer expands from 0–200 m to 0–1000 m but stabilises thereafter. Fragmentation follows a dual-core driving pattern shaped by vegetation and impervious-surface conditions; fractional vegetation cover represents the most consistent dominant factor across all scales and time periods. Near-shore zones are jointly influenced by elevation and distance-to-river gradients, while outer buffer zones are mainly controlled by vegetation conditions. All factor interactions produce enhanced explanatory power. After 2010, near-shore areas underwent a phase shift toward strong multi-factor coupling. Fragmentation hotspots gradually became decoupled from heritage-site locations, suggesting heritage-related pressures act largely through combined factor effects rather than the direct influence of heritage sites themselves. This research offers a refined analytical framework for urban canal heritage and supports evidence-informed conservation and living-heritage revitalization.

LandVol. 15(11)
Nanjing Forestry University (CN)
Ministry of Education of the People's Republic of China, Social Science Foundation of Jiangsu Province
Sustainable cities and communities, Life on land
Openalex Percentile: Top 17%
Land Use and Ecosystem Services
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