气候变化领域集成服务门户(CCPortal): Urban climate zone classification using convolutional neural network and ground-level images

CCPortal

DOI	10.1177/0309133319837711
	Urban climate zone classification using convolutional neural network and ground-level images
	Xu, Guang 1; Zhu, Xuan 1; Tapper, Nigel 1; Bechtel, Benjamin 2
发表日期	2019
ISSN	0309-1333
EISSN	1477-0296
卷号	43 期号:3 页码:410-424
英文摘要	Urban climate risks have a wide range of impacts on the health of more than 50% of the world's population, which is a critical issue relating to climate change. To support urban climate study and categorise different urban environments and their atmospheric impacts in a consistent way, the Local Climate Zone (LCZ) classification scheme has been developed. The World Urban Database and Access Portal Tools project aims to map the LCZ of cities across the globe. However, previous classification approaches based on satellite images have limitations regarding the characterisation of three-dimensional features such as building heights. This study aims to apply convolutional neural networks to classify LCZ types based on ground-level images, which can provide more detail of the urban environments. Validation results have shown an overall accuracy of 69.6%. The new method outperformed previous satellite-based studies for classifying the LCZ types Compact Mid-rise, Sparsely Built, Heavy Industry, and Bare Rock or Paved.
WOS研究方向	Physical Geography ; Geology
来源期刊	PROGRESS IN PHYSICAL GEOGRAPHY-EARTH AND ENVIRONMENT
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/98607
作者单位	1.Monash Univ, 9 Rainforest Walk,Clayton Campus, Melbourne, Vic 3800, Australia; 2.Univ Hamburg, Hamburg, Germany
推荐引用方式 GB/T 7714	Xu, Guang,Zhu, Xuan,Tapper, Nigel,et al. Urban climate zone classification using convolutional neural network and ground-level images[J],2019,43(3):410-424.
APA	Xu, Guang,Zhu, Xuan,Tapper, Nigel,&Bechtel, Benjamin.(2019).Urban climate zone classification using convolutional neural network and ground-level images.PROGRESS IN PHYSICAL GEOGRAPHY-EARTH AND ENVIRONMENT,43(3),410-424.
MLA	Xu, Guang,et al."Urban climate zone classification using convolutional neural network and ground-level images".PROGRESS IN PHYSICAL GEOGRAPHY-EARTH AND ENVIRONMENT 43.3(2019):410-424.