Assessing the Trends and Dynamics of Landscape Pattern Change in the Trang An Mixed World Heritage Site, Ninh Binh Province
Main Article Content
Abstract
The Trang An Landscape Complex, Vietnam's first mixed heritage site and Southeast Asia's, currently faces these challenges. This study applies spatiotemporal analysis to clarify the ongoing conflict between conserving natural and cultural landscapes and urbanizing heritage areas. The methodology involves classifying LULC over twenty years from 2004 to 2024 using Landsat satellite images, analyzing landscape fragmentation with metrics such as Area metrics (LM1), Density metrics (LM2), Shape metrics (LM3), and Connectivity metrics (LM4), and assessing the impacts of socioeconomic development on the Outstanding Universal Value (OUV). The LULC classification achieved overall accuracies of 85.93% to 87.96%, with Kappa coefficients ranging from 0.83 to 0.86. The results show that the core zone has maintained large patches and ecological integrity, while the buffer zone faces increasing fragmentation pressure, undermining landscape protection efforts and increasing the risk of pattern disruption. Furthermore, the results reveal distinct spatiotemporal trends in landscape dynamics, characterized by increasing patch density, shape complexity, and fragmentation intensity in the buffer zone, accompanied by a gradual decline in landscape connectivity over time. By explicitly linking long-term landscape pattern dynamics with heritage zoning, this study provides empirical evidence to support adaptive conservation and spatial planning strategies for mixed World Heritage sites under rapid urbanization. This comprehensive framework offers an effective decision-support tool for planning and guiding sustainable urban development at World Heritage sites amid ongoing urbanization challenges.
Keywords:
Remote sensing, Landscape pattern, Urbanization, World Heritage conservation, Trang An Landscape Complex.
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https://doi.org/10.25073/2588-1094/vnuees.5069 (in Vietnamese).
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Vol. 38, No. 3, 2022, pp. 32-44,
https://doi.org/10.25073/2588-1094/vnuees.4815 (in Vietnamese).
[20] P. V. Dong, B. Q. Thanh, N. Q. Huy, V. H. Anh, P. V. Manh, Application of Deep Learning Algorithm to Build an Automated Cloud Segmentation Model Based on Open Data Cube Framework, VNU Journal of Science: Earth and Environmental Science, Vol. 36, No. 4, 2020, pp. 8-16, https://doi.org/10.25073/2588-1094/vnuees.4441 (in Vietnamese).
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https://doi.org/10.1038/s41598-023-40564-0.
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https://doi.org/10.1016/j.rse.2019.111354.
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https://doi.org/10.1016/j.ecolind.2024.112888.
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https://doi.org/10.1016/j.ecolind.2024.112120.