Jie Shao , Wei Yao , Lei Luo , Linzhou Zeng , Zhiyi He , Puzuo Wang , Xingjian Fu , Jianbo Qi , Huadong Guo
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引用次数: 0
Abstract
Green roofs constitute a critical component in enhancing urban sustainability and resilience, making the systematic assessment of roof greening initiatives a pivotal focus in urban research and planning. A thorough understanding of implementation priorities and potential benefits is essential for effectively promoting green roof adoption. As a multifaceted urban intervention, roof greening involves complex stakeholder coordination and requires comprehensive assessments across various urban development dimensions. Nevertheless, significant research gaps remain regarding the multi-criteria evaluation of building-level roof greening priorities and their associated benefits at urban scales. Here, using geospatial big data, we conduct an urban-scale assessment of roof greening at a single building level in Hong Kong from a sustainable development perspective. We identify that 85.3 % of buildings reveal potential and urgent demand for roof greening (average priority>0.6). We further find green roofs could increase greenspace coverage rate around buildings by 65.7 %, produce hundreds of millions (HK$) in economic benefits annually, and contribute to approximately 0.15 °C urban temperature reduction and 0.8 % annual carbon emission offsets. Our study offers a comprehensive assessment of roof greening, which could provide a reference for sustainable development in cities worldwide, from data utilization to solutions and findings.
期刊介绍:
Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing.
The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques.
RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.