Impact of 2D/3D Landscape Pattern on Urban Ecological Environment Quality: Explainable Machine Learning Methods
Year: 2025
Type: conference-paper
Abstract: It is increasingly important to consider ecological environmental quality (EEQ) in urban design. However, urban expansion is increasingly vertical as well as horizontal. This paper proposes a new set of 2D/3D landscape morphology indicators and a new model for quantifying urban EEQ and applies these within a novel machine learning framework. The preliminary results show that: (1) there is a correlation between landscape morphology indicators and EEQ; (2) the proposed new model has improved accuracy and robustness; (3) a threshold for the landscape morphology indicators can be identified; (4) there are seasonal and scale effects. The above findings may help optimize urban spatial structure, and improve the EEQ in urban areas.
Authors: Zhou, Yinqiao, Carver, Steve, Gosal, Arjan, Comber, Alexis
Institution: University of Leeds
Language: English
Subfield: Building and Construction
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6912100372
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