The application of a high-density street-level air temperature observation network (HiSAN): The relationship between air temperature, urban development, and geographic features-Reference-Cited by-同舟云学术

The application of a high-density street-level air temperature observation network (HiSAN): The relationship between air temperature, urban development, and geographic features

Published:2019-10 Issue: Volume:685 Page:710-722
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Chen Yu-Cheng,Liao Yu-Jie,Yao Chun-Kuei,Honjo Tsuyoshi,Wang Chi-Kuei,Lin Tzu-Ping^ORCID

Funder

Ministry of Science and Technology of Taiwan

Publisher

Elsevier BV

Subject

Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference53 articles.

1. A comparison of thermal comfort conditions in four urban spaces by means of measurements and modelling techniques;Acero;Build. Environ.,2015

2. Application of climatic guidelines to urban planning: the example of Lisbon (Portugal);Alcoforado;Landsc. Urban Plan.,2009

3. Global to city scale urban anthropogenic heat flux: model and variabilityInt;Allen;J. Climatol.,2011

4. Impervious surface coverage: the emergence of a key environmental indicator;Arnold;J. Am. Plan. Assoc.,1996

5. Urbanization and warming of phoenix (Arizona, USA): impacts, feedbacks and mitigation;Baker;Urban Ecosyst,2002

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