Quantifying how landscape composition and configuration affect urban land surface temperatures using machine learning and neutral landscapes-Reference-Cited by-同舟云学术

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Quantifying how landscape composition and configuration affect urban land surface temperatures using machine learning and neutral landscapes

Published:2019-07 Issue: Volume:76 Page:80-90
ISSN:0198-9715
Container-title:Computers, Environment and Urban Systems
language:en
Short-container-title:Computers, Environment and Urban Systems

Author:

Osborne Patrick E.,Alvares-Sanches Tatiana

Funder

Engineering and Physical Sciences Research Council

Transforming the Engineering of Cities to Deliver Societal and Planetary Wellbeing

City-Wide Analysis to Propel Cities towards Resource Efficiency and Better Wellbeing;

Publisher

Elsevier BV

Subject

Urban Studies,General Environmental Science,Ecological Modelling,Geography, Planning and Development

Reference64 articles.

1. Gap-filling restoration methods for ETM + sensor images;Ali;Iraqi J. Sci.,2013

2. Heat waves in the United States: Mortality risk during heat waves and effect modification by heat wave characteristics in 43 U.S. communities;Anderson;Environmental Health Perspectives,2011

3. Effects of city expansion on heat stress under climate change conditions;Argueso;PLoS One,2015

4. Survey of emissivity variability in thermography of urban areas;Artis;Remote Sensing of Environment,1982

5. Assessing the effect of green cover spatial patterns on urban land surface temperature using landscape metrics approach;Asgarian;Urban Ecosyst,2015

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