title: Applying the grey assessment to the evaluation system of ecological green space on greening projects in Taiwan.
abstract: This study is designed to develop an alternative evaluation method for ecological green space. It offers criteria for identifying ecological green space on building sites. The grey decision-making method is applied to assess the greening project at the first step. The evaluation items are rebuilt by the analytic hierarchy process (AHP) method at the second step. The range of standard values and the weighting values are also obtained by AHP. Grey classes are identified using the whitening weight function of the grey number. The evaluation system of the ecological green space is framed by grey clusters. We considered the factors of building environment and the scale of building sites in the ecological greenery of green building sites.This study proposes a new model to solve the problems hard to be quantified. Especially for those ecological benefits are too close to decide. Architects and landscape architects can input the engineering data and the design information into the ecological greenery assessment system. The identification and assessment system of green space is fit for Taiwan area. We will obtain the best greening project by the maximum value of absolute degree of grey incidence (max{epsilon(ij)}) in grey-decision making. The maximum value of synthetic clustering coefficient (max{sigma(k)}) in grey clustering assessment reflects the quality and variation of green space.
authors: Department of Architecture, China University of Technology, Taipei 116, Taiwan.
authors: Li-Wei
authors: LW
authors: Lin
authors: Chui-Hui
authors: CH
authors: Chen
authors: Hsueh-Cherng
authors: HC
authors: Chang
authors: Tzu-Chun
authors: TC
authors: Chen
mesh_terms: D002947:Cities; D003247:Conservation of Natural Resources; D003657:Decision Making; D017753:Ecosystem; D004738:Engineering; D004777:Environment; D004779:Environment Design; D005069:Evaluation Studies as Topic; D006801:Humans; D013624:Taiwan