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中国农学通报 ›› 2010, Vol. 26 ›› Issue (16): 199-205.

• 林学 园艺 园林 • 上一篇    下一篇

RAGA-PPE模型在城市滨水绿地景观效果评价中的应用

张翼飞 于崧 鲁萍 车代弟   

  • 收稿日期:2010-04-19 修回日期:2010-05-14 出版日期:2010-08-20 发布日期:2010-08-20
  • 基金资助:
    东北农业大学创新团队项目

Effect evaluation of urban waterfront green space landscape based on application of RAGA-PPE model

  • Received:2010-04-19 Revised:2010-05-14 Online:2010-08-20 Published:2010-08-20

摘要: 基于人们对城市滨水绿地景观的关注日益加强,本文提出将RAGA-PPE模型(基于加速遗传算法的投影寻踪等级评价模型)应用到城市滨水绿地景观效果的评价中,将多维数据指标转换成低维子空间,通过寻求最优投影方向来计算投影函数值,建立多元数据分类与评价模型,从而根据投影值的大小进行景观评价。以大庆市为研究对象,构建了大庆市滨水绿地景观效果的评价指标体系及等级标准,并对5个城市滨水绿地的景观效果进行评价。评价结果表明:大庆市东风湖的等级值为1.5561,景观效果较好;万宝湖、滨州湖的等级值分别为3.3425和3.3427,景观效果一般;乘风湖的等级值为3.6491,景观效果较差;黎明湖的等级值为4.7159,景观效果差。评价结果与公众主观感觉基本一致,该模型具有较高的评价精度,适用于城市滨水绿地景观效果的分析评价,避免了传统方法存在的不足,为具有模糊、不确定性高维数据的景观综合评价提供了新的思路与方法。

关键词: 产区, 产区, 香料烟, 化学成分, 感官质量

Abstract: With the increasing people concerning bout the urban waterfront green space landscape, the RAGA-PPE model was applied to the effect evaluation of urban waterfront green space landscape. We changed the multi-dimension data into low-dimension space and searched for the optimum projection direction to get the projection function value, then established the classification of multiple-unit data and evaluating model, which can evaluate landscape effect according to the size of the projection value. Daqing City was taken as the research object, effect evaluation index system and grade standard for waterfront green space landscape were built and effect evaluation was carried out on five urban waterfront green space landscapes. The results of evaluation showed that the score of “apt” for Dongfeng Lake was 1.5561, and the scores of “intermediate” for Wanbao Lake and Binzhou Lake were 3.3425 and 3.3427, respectively, while the score of “poor” for Chengfeng Lake was 3.6491, and the score of “very poor” for Dawn Lake was 4.7159. The evaluation results were basically consistent with the public feedback, suggesting that the model suitable for effect evaluation of urban waterfront green space landscape because of its higher accuracy. It also provided new method for dealing with the landscape comprehensive evaluation which has fuzzy and uncertain data by avoiding some deficiencies in traditional methods.