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Design+                                         Evaluation of recreational suitability of urban waterfront green spaces



              Factors affecting the recreational suitability of urban   relevant practitioners were invited to score and evaluate,
            waterfront green spaces are diverse and multifaceted. For   and the indicators were revised and sorted out based on
            example, Xia  et al.  noted in their research that visual   their opinions. The requirements for expert selection were
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            environmental elements, such as vegetation and water   as follows: first, having engaged in the study or research
            bodies, can enhance the recreational experience. Mingde   of this field for 5 years or more and second, having rich
            and Jiayi  analysis of the factors influencing the vitality of   practical experience and a certain understanding of related
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            waterfront  spaces  identified location  and  accessibility as   research. The Likert scale method was used to evaluate the
            the primary driving factors. Based on the literature review,   primary election indicators according to five evaluation
            the factors influencing the recreational suitability of urban   levels of “important, relatively important, generally
            waterfront green spaces were discussed from various   important, less important, and not important,” and their
            perspectives, including space, environment, facility,   values were assigned as “5, 4, 3, 2, and 1 point,” respectively
            activity, and image.                               (Appendix  1). The experts proposed corresponding
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              By referencing the recreational suitability evaluation   rectification suggestions according to their opinions.
            systems for urban wetlands, comprehensive parks, and   After integration and modification, a recreation suitability
            urban green open spaces constructed by Yang,  Zhang and   evaluation system for urban waterfront green spaces
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            Chen,  Sun,  Liu et al.,  and others, and incorporating   comprising  six  target  layers,  12  primary  indexes,  and
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            Lang’s  research on the evaluation index systems for   43 secondary indexes was established.
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            waterfront  space  characteristics,  along  with  expert   2.2.2. Determination of indicator weights
            consultations, a total of 52 indicators were predominantly
            selected from six categories:                      After the preliminary construction of the evaluation
            (i)  Environmental elements: Ultraviolet rays, temperature,   system for the recreation suitability of urban waterfront
               air  humidity,  air  quality,  rainfall,  wind  speed,  water   green spaces, it is necessary to calculate the weight
               quality, noise, and environmental sanitation.   values of the sub-indicators at each level. The AHP 38-41
            (ii)  Landscape elements: Plant landscape, landform   and the nine-level scale scoring standard were used
               landscape, revetment landscape, water body      to construct the importance judgment matrix of
               landscape, rock landscape, skyline landscape, garden   indicators at each level. The weight questionnaires for
               path landscape, small architecture, historical and   the factor level, first-level indicator, and second-level
               cultural relics, and facility landscape.        indicator  were  designed  respectively.  In  this  study,  the
            (iii)  Resource elements: Plant diversity, greening coverage,   weight calculation of evaluation indicators was directly
               topography and landforms, water resources, cultural   obtained using the AHP calculation in the “Wen Juan
               monuments, local customs, festival activities, and   Xing” website (https://www.wjx.cn/). By constructing
               science education.                              questionnaires with the AHP model in Wen Juan Xing,
            (iv)  Facility elements: Signage completeness, category   the system was broken down into different levels, and
               comprehensiveness, usage status, maintenance    the importance of indicators was compared pairwise to
               status, comfort level, distribution status, diversity of   build a judgment matrix. Then, through operations such
               recreational facilities, interest level of recreational   as solving for the maximum eigenvalue and performing
               facilities, management status of recreational facilities,   weighted summation, the final weight of each indicator
               safety of recreational facilities, safety of water-friendly   was  determined.  The relevant calculation  formula  is
               facilities, interest level of water-friendly facilities, and   presented in Equations I and II:
               rationality of water-friendly facilities.             1    ( AW)
            (v)  Recreational experience elements: Diversity of   λ max  =  n ∑ n i=1  W  i                (I)
               recreational spaces, comfort of recreational spaces,           i
               safety of recreational spaces, water-friendliness of   λ  − n
               recreational spaces, diversity of recreational activities,   CI.. =  max                    (II)
                                                                      n −1
               participation in recreational activities, attractiveness
               of recreational activities, and entertainment value of   where λ max  is the maximum eigenvalue, n is the number
               water-friendly experiences.                     of dimensions, and  AW is the product of the judgment
            (vi)  Location and transportation elements: Geographical   matrix and the normalized weights.
               location, visitor arrival distance, internal transportation   Data from 30 experts and relevant practitioners were
               conditions, and external transportation conditions.  collected to calculate the indicator weights and perform
              The primary election indicators were screened using   a consistency check for each level. The principal model is
            the Delphi method. Thirty professional teachers and   illustrated in Figure 4.


            Volume 2 Issue 3 (2025)                         5                            doi: 10.36922/DP025110020
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