GIS-based revision of a WUDAPT Local Climate Zones map of Bern, Switzerland

IF 3.9 Q2 ENVIRONMENTAL SCIENCES City and Environment Interactions Pub Date : 2024-01-01 DOI:10.1016/j.cacint.2023.100135
Noémie Wellinger , Moritz Gubler , Flurina Müller , Stefan Brönnimann
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Abstract

Urban areas are particularly affected by heatwaves through the intensification of heat stress by the urban heat island effect. For effective climate change adaptation, information about microscale surface cover, structures, and human activity in cities is needed to depict the underlying causes of urban heat stress. The framework of “Local Climate Zones” (LCZs) classifies and standardizes urban areas based on such characteristics. To date, most LCZ mapping workflows use satellite imagery as input. The resulting maps may lack some important details, and thus benefit from the use of additional geodata. We introduce a novel approach that combines the geodata of urban canopy parameters with the remote sensing-based LCZ map of Bern, Switzerland. City-specific urban canopy parameters are calculated and used to adjust established value ranges, if necessary. The most common misclassification patterns are identified and misclassified pixels are corrected using a decision tree and k-nearest-neighbor algorithm. Results show that the conformity with the urban canopy parameter values markedly increased, especially in the distinction of water surfaces, non-built areas, and building height. However, for high-resolution LCZ maps, this also leads to unnecessary heterogeneity, which may require further postprocessing. Given sufficiently available urban canopy parameter data, the proposed workflow is simple and easily adaptable for other cities. It could prove useful in urban climate studies and city planning to enhance an existing LCZ map in a contextualized manner quickly.

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以地理信息系统为基础修订瑞士伯尔尼 WUDAPT 地方气候带地图
由于城市热岛效应加剧了热压力,城市地区受热浪的影响尤为严重。为有效适应气候变化,需要有关城市微观地表覆盖、结构和人类活动的信息,以描述城市热压力的根本原因。地方气候区"(LCZ)框架根据这些特征对城市地区进行分类和标准化。迄今为止,大多数 LCZ 制图工作流程都使用卫星图像作为输入。由此绘制的地图可能缺少一些重要细节,因此需要使用额外的地理数据。我们引入了一种新方法,将城市树冠参数的地理数据与基于遥感技术的瑞士伯尔尼低碳区地图相结合。我们计算了城市特有的冠层参数,并在必要时用于调整既定的数值范围。利用决策树和 k-最近邻算法识别出最常见的错误分类模式并纠正错误分类像素。结果表明,与城市冠层参数值的一致性明显提高,尤其是在区分水面、非建筑区和建筑高度方面。然而,对于高分辨率 LCZ 地图,这也会导致不必要的异质性,可能需要进一步的后处理。如果有足够的城市冠层参数数据,建议的工作流程就会很简单,并且很容易适用于其他城市。在城市气候研究和城市规划中,它可能会被证明是有用的,能以符合实际情况的方式快速增强现有的低纬度区地图。
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来源期刊
City and Environment Interactions
City and Environment Interactions Social Sciences-Urban Studies
CiteScore
6.00
自引率
3.00%
发文量
15
审稿时长
27 days
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