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Study on Functional Zoning Method of National Park Based on MCDA: The Case of the Proposed “Ailaoshan-Wuliangshan” National Park

Study on Functional Zoning Method of National Park Based on MCDA: The Case of the Proposed... In a national park master plan, functional zoning plays a key role in developing differentiated zoning controls that achieve multiple park construction objectives. In this study, a geographical attribute code and basic zoning elements are developed for the proposed “Ailaoshan-Wuliangshan” National Park, followed by the development of spatial multi-criteria sets and weight sets to determine the suitability of the land. Next, we use a clustering algorithm and conflict unit prioritization to allocate space for multi-target units to get the preliminary zoning schemes, and then identify stable units and unstable units through sensitivity analysis. Ultimately, the functional zoning of the National Park was determined. According to the results, the proposed “Ailaoshan-Wuliangshan” National Park can be divided into nine types of 164 landscape units; the highest land suitability values of each zone showed the traits of differentiation and aggregation in spatial distribution; there are 97 stable units and 67 unstable units; approximately 62.83% and 37.17% of the total park area can be divided into core conservation area (primary sensitive area and secondary sensitive area) and general control area (ecological activity area and ecological control area). By implementing a comprehensive assessment and decision-making process, the defined functional zones are precise and simple to recognize on the ground, and they adhere to the area proportions needed by national standards. Furthermore, the functional zoning is clustered, which avoids the fragmentation of the zoning results causing difficulties in management, and serves as a point of reference for the functional zoning approaches used in other proposed national parks in China. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Land Multidisciplinary Digital Publishing Institute

Study on Functional Zoning Method of National Park Based on MCDA: The Case of the Proposed “Ailaoshan-Wuliangshan” National Park

Study on Functional Zoning Method of National Park Based on MCDA: The Case of the Proposed “Ailaoshan-Wuliangshan” National Park

Land , Volume 11 (11) – Oct 23, 2022

Abstract

In a national park master plan, functional zoning plays a key role in developing differentiated zoning controls that achieve multiple park construction objectives. In this study, a geographical attribute code and basic zoning elements are developed for the proposed “Ailaoshan-Wuliangshan” National Park, followed by the development of spatial multi-criteria sets and weight sets to determine the suitability of the land. Next, we use a clustering algorithm and conflict unit prioritization to allocate space for multi-target units to get the preliminary zoning schemes, and then identify stable units and unstable units through sensitivity analysis. Ultimately, the functional zoning of the National Park was determined. According to the results, the proposed “Ailaoshan-Wuliangshan” National Park can be divided into nine types of 164 landscape units; the highest land suitability values of each zone showed the traits of differentiation and aggregation in spatial distribution; there are 97 stable units and 67 unstable units; approximately 62.83% and 37.17% of the total park area can be divided into core conservation area (primary sensitive area and secondary sensitive area) and general control area (ecological activity area and ecological control area). By implementing a comprehensive assessment and decision-making process, the defined functional zones are precise and simple to recognize on the ground, and they adhere to the area proportions needed by national standards. Furthermore, the functional zoning is clustered, which avoids the fragmentation of the zoning results causing difficulties in management, and serves as a point of reference for the functional zoning approaches used in other proposed national parks in China.

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Multidisciplinary Digital Publishing Institute
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ISSN
2073-445X
DOI
10.3390/land11111882
Publisher site
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Abstract

In a national park master plan, functional zoning plays a key role in developing differentiated zoning controls that achieve multiple park construction objectives. In this study, a geographical attribute code and basic zoning elements are developed for the proposed “Ailaoshan-Wuliangshan” National Park, followed by the development of spatial multi-criteria sets and weight sets to determine the suitability of the land. Next, we use a clustering algorithm and conflict unit prioritization to allocate space for multi-target units to get the preliminary zoning schemes, and then identify stable units and unstable units through sensitivity analysis. Ultimately, the functional zoning of the National Park was determined. According to the results, the proposed “Ailaoshan-Wuliangshan” National Park can be divided into nine types of 164 landscape units; the highest land suitability values of each zone showed the traits of differentiation and aggregation in spatial distribution; there are 97 stable units and 67 unstable units; approximately 62.83% and 37.17% of the total park area can be divided into core conservation area (primary sensitive area and secondary sensitive area) and general control area (ecological activity area and ecological control area). By implementing a comprehensive assessment and decision-making process, the defined functional zones are precise and simple to recognize on the ground, and they adhere to the area proportions needed by national standards. Furthermore, the functional zoning is clustered, which avoids the fragmentation of the zoning results causing difficulties in management, and serves as a point of reference for the functional zoning approaches used in other proposed national parks in China.

Journal

LandMultidisciplinary Digital Publishing Institute

Published: Oct 23, 2022

Keywords: national park; functional zoning; landscape unit; multi-criteria decision analysis

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