HUL values in practice: A character area designation model for the conservation of built heritage in less-developed regions

被引:6
作者
Ghanbari, Erfaneh [1 ]
Lotfi, Sahand [1 ]
Sholeh, Mahsa [1 ]
机构
[1] Shiraz Univ, Dept Urban Planning & Design, Shiraz, Iran
关键词
HUL values; Character area designation; Built heritage conservation; GIS-based zoning methodology; Heritage value assessment; Sustainable urban development; MANAGEMENT;
D O I
10.1016/j.culher.2024.08.010
中图分类号
K85 [文物考古];
学科分类号
0601 ;
摘要
This study endeavors to confront the challenge of adhering to international guidelines for Historic Urban Landscape (HUL) values and heritage conservation in developing nations, specifically focusing on Iran. Conventional reliance on basic buffer zone methodologies for safeguarding national monuments often leads to the oversight and subsequent deterioration of valuable structures, resulting in irreversible decay. This research introduces an innovative GIS-based zoning methodology alongside a comprehensive framework for assessing heritage values to mitigate these deficiencies. Grounded in seminal texts such as the Venice Charter (1964), Washington Charter (1987), and Vienna Memorandum (2005), this study extends the HUL approach to establish a cost-effective yet robust practical foundation. Through the Lar Old City case study, the research systematically integrates the Analytical Hierarchy Process (AHP) and Inverse Distance Weighting (IDW) within GIS to evaluate heritage values and map character areas. This approach facilitates regular assessments and promotes sustainable management of built heritage, demonstrating efficiency in resource allocation. The framework aims to bolster conservation efforts by embedding HUL values and advocating for sustainable urban development consistent with contemporary planning principles. The findings underscore this approach's practical significance and applicability, offering a comprehensive framework to bridge gaps in heritage conservation practices and safeguard cultural heritage for future generations. (c) 2024 Consiglio Nazionale delle Ricerche (CNR). Published by Elsevier Masson SAS. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
引用
收藏
页码:41 / 53
页数:13
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