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Assessment of the relation between land use and carbon emission in Eindhoven, the Netherlands

Author:
Wang, Gengzhe, Han, Qi, de vries, Bauke
Source:
Journal of environmental management 2019 v.247 pp. 413-424
ISSN:
0301-4797
Subject:
algorithms, buildings, carbon, case studies, climate change, cluster analysis, green infrastructure, greenhouse gas emissions, land cover, land use, landscapes, planning, probability, residential areas, residential housing, retail marketing, roads, terraces, Netherlands
Abstract:
The impact of the urban morphology on greenhouse gas emission is one of the key issues on global climate change. Since the urban form is directly related to the spatial distribution of urban land use, it is necessary to investigate the relation between carbon emission and different land use categories. In this paper, the city of Eindhoven (230,000 inhabitants) was used as a case study. According to the main road network, the entire city is divided into 6754 irregular patterns. Agglomerative cluster analysis was conducted to classify the patterns into 14 valid land use categories based on their land use function and land cover composition namely: agriculture, transport, retail trade, green space (with 3 sub-categories), residential (with 7 sub-categories), and others. The random forest algorithm was applied to select the significant features and to measure the relation between land use and carbon emission. The results have shown the importance of various landscape metrics on the carbon emission in each land use category. The most significant landscape metric is selected to describe the impact of spatial attributes on carbon emission. The outcomes show the carbon emission distribution of each land use category in the city. The retail trade and residential land use categories contribute a large proportion of carbon emission, terrace houses produce more carbon emission than other residential building categories. The combination of mid-rise buildings and low-rise buildings has a higher probability to produce more carbon emission. The assessment results can provide important support for the low carbon city spatial planning.
Agid:
6483891