Recreation is a basic human need and therefore must be considered in spatial planning, which requires spatially explicit mapping of the recreation suitability of a landscape. The current methods for this type of mapping have limitations: On one hand, widely used expert-based models for large scale suitability assessments often suffer from discrepancies between the mapped values from expert assessment and actual user preferences. On the other hand, elicitation of personal preferences of potential users is complex and time-consuming, and their applicability to larger scales is limited.

In this paper, we demonstrate the development of a spatially explicit model for the recreation suitability of the riverine zone that integrates the preferences of the users with an expert-based modeling process. First, we conducted an analytic hierarchy process (AHP) with experts to generate four different model variants based on physical variables. These model variants differ in terms of the strength of the influence of the variables on the recreation suitability. Second, an online survey was used to gather data on user preferences for various river sections with regard to recreation. A comparison of the expert model results with the preferences of the potential users shows a clear correlation between one model variant and the users’ preferences. This result suggests that it is possible to elaborate an expert model which corresponds to the preferences of users.

We made the model results available for the planning and development of the riverine zone in the canton of Zurich. To this end, they were integrated in a decision support platform together with other planning-relevant information.

娱乐是人类的基本需求，因此必须在空间规划中予以考虑，这需要在空间上对景观的休闲适应性进行显式映射。这种类型的映射的当前方法有局限性：一方面，广泛用于大规模适应性评估的基于专家的模型通常遭受专家评估的映射值与实际用户偏好之间的差异。另一方面，引起潜在用户的个人喜好是复杂且耗时的，并且它们在更大范围内的适用性受到限制。

在本文中，我们演示了针对河床带休闲适应性的空间显式模型的开发，该模型将用户的偏好与基于专家的建模过程相结合。首先，我们与专家进行了层次分析法（AHP），以基于物理变量生成四个不同的模型变体。这些模型变体在变量对娱乐适应性的影响强度方面有所不同。其次，使用在线调查来收集有关娱乐方面各个河流段的用户偏好的数据。专家模型结果与潜在用户偏好的比较表明，一个模型变体与用户偏好之间存在明显的相关性。

我们将模型结果提供给苏黎世州河流带的规划和开发。为此，它们与其他与规划相关的信息一起集成在决策支持平台中。