Loading…

Daytime Thermal Anisotropy of Urban Neighbourhoods: Morphological Causation

Surface temperature is a key variable in boundary-layer meteorology and is typically acquired by remote observation of emitted thermal radiation. However, the three-dimensional structure of cities complicates matters: uneven solar heating of urban facets produces an “effective anisotropy” of surface...

Full description

Saved in:
Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2016, Vol.8 (2), p.108
Main Authors: Krayenhoff, E., Voogt, James
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c330t-157858ab5bc25b7e4d07bb7619ddc160cdecdba142b53e2371d69f3521e994813
cites cdi_FETCH-LOGICAL-c330t-157858ab5bc25b7e4d07bb7619ddc160cdecdba142b53e2371d69f3521e994813
container_end_page
container_issue 2
container_start_page 108
container_title Remote sensing (Basel, Switzerland)
container_volume 8
creator Krayenhoff, E.
Voogt, James
description Surface temperature is a key variable in boundary-layer meteorology and is typically acquired by remote observation of emitted thermal radiation. However, the three-dimensional structure of cities complicates matters: uneven solar heating of urban facets produces an “effective anisotropy” of surface thermal emission at the neighbourhood scale. Remotely-sensed urban surface temperature varies with sensor view angle as a consequence. The authors combine a microscale urban surface temperature model with a thermal remote sensing model to predict the effective anisotropy of simplified neighbourhood configurations. The former model provides detailed surface temperature distributions for a range of “urban” forms, and the remote sensing model computes aggregate temperatures for multiple view angles. The combined model’s ability to reproduce observed anisotropy is evaluated against measurements from a neighbourhood in Vancouver, Canada. As in previous modeling studies, anisotropy is underestimated. Addition of moderate coverages of small (sub-facet scale) structure can account for much of the missing anisotropy. Subsequently, over 1900 sensitivity simulations are performed with the model combination, and the dependence of daytime effective thermal anisotropy on diurnal solar path (i.e., latitude and time of day) and blunt neighbourhood form is assessed. The range of effective anisotropy, as well as the maximum difference from nadir-observed brightness temperature, peak for moderate building-height-to-spacing ratios (H/W), and scale with canyon (between-building) area; dispersed high-rise urban forms generate maximum anisotropy. Maximum anisotropy increases with solar elevation and scales with shortwave irradiance. Moreover, it depends linearly on H/W for H/W < 1.25, with a slope that depends on maximum off-nadir sensor angle. Decreasing minimum brightness temperature is primarily responsible for this linear growth of maximum anisotropy. These results allow first order estimation of the minimum effective anisotropy magnitude of urban neighbourhoods as a function of building-height-to-spacing ratio, building plan area density, and shortwave irradiance. Finally, four “local climate zones” are simulated at two latitudes. Removal of neighbourhood street orientation regularity for these zones decreases maximum anisotropy by 3%–31%. Furthermore, thermal and radiative material properties are a weaker predictor of anisotropy than neighbourhood morphology. This study is the
doi_str_mv 10.3390/rs8020108
format article
fullrecord <record><control><sourceid>doaj_cross</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_330e38f55fb440089a4df0a4fefdd538</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_330e38f55fb440089a4df0a4fefdd538</doaj_id><sourcerecordid>oai_doaj_org_article_330e38f55fb440089a4df0a4fefdd538</sourcerecordid><originalsourceid>FETCH-LOGICAL-c330t-157858ab5bc25b7e4d07bb7619ddc160cdecdba142b53e2371d69f3521e994813</originalsourceid><addsrcrecordid>eNpNkMtOwzAQRS0EElXpgj_IlkVg_GpsdlV5VRTYtOvIz8ZVWld2usjfEyiqmM2MrnTPSAehWwz3lEp4SFkAAQziAo0IVKRkRJLLf_c1muS8hWEoxRLYCL0_qb4LO1esGpd2qi1m-5Bjl-KhL6Iv1kmrffHpwqbR8ZiaGG1-LD5iOjSxjZtghsZcHbPqQtzfoCuv2uwmf3uM1i_Pq_lbufx6Xcxny9JQCl2JeSW4UJprQ7iuHLNQaV1NsbTW4CkY64zVCjOiOXWEVthOpaecYCclE5iO0eLEtVFt60MKO5X6OqpQ_wYxbWqVumBaVw8PHRWec68ZAxBSMetBMe-8tZyKgXV3YpkUc07On3kY6h-p9Vkq_QZ-5mmi</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Daytime Thermal Anisotropy of Urban Neighbourhoods: Morphological Causation</title><source>Publicly Available Content Database</source><source>IngentaConnect Journals</source><creator>Krayenhoff, E. ; Voogt, James</creator><creatorcontrib>Krayenhoff, E. ; Voogt, James</creatorcontrib><description>Surface temperature is a key variable in boundary-layer meteorology and is typically acquired by remote observation of emitted thermal radiation. However, the three-dimensional structure of cities complicates matters: uneven solar heating of urban facets produces an “effective anisotropy” of surface thermal emission at the neighbourhood scale. Remotely-sensed urban surface temperature varies with sensor view angle as a consequence. The authors combine a microscale urban surface temperature model with a thermal remote sensing model to predict the effective anisotropy of simplified neighbourhood configurations. The former model provides detailed surface temperature distributions for a range of “urban” forms, and the remote sensing model computes aggregate temperatures for multiple view angles. The combined model’s ability to reproduce observed anisotropy is evaluated against measurements from a neighbourhood in Vancouver, Canada. As in previous modeling studies, anisotropy is underestimated. Addition of moderate coverages of small (sub-facet scale) structure can account for much of the missing anisotropy. Subsequently, over 1900 sensitivity simulations are performed with the model combination, and the dependence of daytime effective thermal anisotropy on diurnal solar path (i.e., latitude and time of day) and blunt neighbourhood form is assessed. The range of effective anisotropy, as well as the maximum difference from nadir-observed brightness temperature, peak for moderate building-height-to-spacing ratios (H/W), and scale with canyon (between-building) area; dispersed high-rise urban forms generate maximum anisotropy. Maximum anisotropy increases with solar elevation and scales with shortwave irradiance. Moreover, it depends linearly on H/W for H/W &lt; 1.25, with a slope that depends on maximum off-nadir sensor angle. Decreasing minimum brightness temperature is primarily responsible for this linear growth of maximum anisotropy. These results allow first order estimation of the minimum effective anisotropy magnitude of urban neighbourhoods as a function of building-height-to-spacing ratio, building plan area density, and shortwave irradiance. Finally, four “local climate zones” are simulated at two latitudes. Removal of neighbourhood street orientation regularity for these zones decreases maximum anisotropy by 3%–31%. Furthermore, thermal and radiative material properties are a weaker predictor of anisotropy than neighbourhood morphology. This study is the first systematic evaluation of effective anisotropy magnitude and causation for urban landscapes.</description><identifier>ISSN: 2072-4292</identifier><identifier>EISSN: 2072-4292</identifier><identifier>DOI: 10.3390/rs8020108</identifier><language>eng</language><publisher>MDPI AG</publisher><subject>effective anisotropy ; microscale urban climate model ; neighbourhood geometry ; surface structure ; surface temperature ; thermal remote sensing ; urban form</subject><ispartof>Remote sensing (Basel, Switzerland), 2016, Vol.8 (2), p.108</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c330t-157858ab5bc25b7e4d07bb7619ddc160cdecdba142b53e2371d69f3521e994813</citedby><cites>FETCH-LOGICAL-c330t-157858ab5bc25b7e4d07bb7619ddc160cdecdba142b53e2371d69f3521e994813</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,4022,27922,27923,27924</link.rule.ids></links><search><creatorcontrib>Krayenhoff, E.</creatorcontrib><creatorcontrib>Voogt, James</creatorcontrib><title>Daytime Thermal Anisotropy of Urban Neighbourhoods: Morphological Causation</title><title>Remote sensing (Basel, Switzerland)</title><description>Surface temperature is a key variable in boundary-layer meteorology and is typically acquired by remote observation of emitted thermal radiation. However, the three-dimensional structure of cities complicates matters: uneven solar heating of urban facets produces an “effective anisotropy” of surface thermal emission at the neighbourhood scale. Remotely-sensed urban surface temperature varies with sensor view angle as a consequence. The authors combine a microscale urban surface temperature model with a thermal remote sensing model to predict the effective anisotropy of simplified neighbourhood configurations. The former model provides detailed surface temperature distributions for a range of “urban” forms, and the remote sensing model computes aggregate temperatures for multiple view angles. The combined model’s ability to reproduce observed anisotropy is evaluated against measurements from a neighbourhood in Vancouver, Canada. As in previous modeling studies, anisotropy is underestimated. Addition of moderate coverages of small (sub-facet scale) structure can account for much of the missing anisotropy. Subsequently, over 1900 sensitivity simulations are performed with the model combination, and the dependence of daytime effective thermal anisotropy on diurnal solar path (i.e., latitude and time of day) and blunt neighbourhood form is assessed. The range of effective anisotropy, as well as the maximum difference from nadir-observed brightness temperature, peak for moderate building-height-to-spacing ratios (H/W), and scale with canyon (between-building) area; dispersed high-rise urban forms generate maximum anisotropy. Maximum anisotropy increases with solar elevation and scales with shortwave irradiance. Moreover, it depends linearly on H/W for H/W &lt; 1.25, with a slope that depends on maximum off-nadir sensor angle. Decreasing minimum brightness temperature is primarily responsible for this linear growth of maximum anisotropy. These results allow first order estimation of the minimum effective anisotropy magnitude of urban neighbourhoods as a function of building-height-to-spacing ratio, building plan area density, and shortwave irradiance. Finally, four “local climate zones” are simulated at two latitudes. Removal of neighbourhood street orientation regularity for these zones decreases maximum anisotropy by 3%–31%. Furthermore, thermal and radiative material properties are a weaker predictor of anisotropy than neighbourhood morphology. This study is the first systematic evaluation of effective anisotropy magnitude and causation for urban landscapes.</description><subject>effective anisotropy</subject><subject>microscale urban climate model</subject><subject>neighbourhood geometry</subject><subject>surface structure</subject><subject>surface temperature</subject><subject>thermal remote sensing</subject><subject>urban form</subject><issn>2072-4292</issn><issn>2072-4292</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpNkMtOwzAQRS0EElXpgj_IlkVg_GpsdlV5VRTYtOvIz8ZVWld2usjfEyiqmM2MrnTPSAehWwz3lEp4SFkAAQziAo0IVKRkRJLLf_c1muS8hWEoxRLYCL0_qb4LO1esGpd2qi1m-5Bjl-KhL6Iv1kmrffHpwqbR8ZiaGG1-LD5iOjSxjZtghsZcHbPqQtzfoCuv2uwmf3uM1i_Pq_lbufx6Xcxny9JQCl2JeSW4UJprQ7iuHLNQaV1NsbTW4CkY64zVCjOiOXWEVthOpaecYCclE5iO0eLEtVFt60MKO5X6OqpQ_wYxbWqVumBaVw8PHRWec68ZAxBSMetBMe-8tZyKgXV3YpkUc07On3kY6h-p9Vkq_QZ-5mmi</recordid><startdate>2016</startdate><enddate>2016</enddate><creator>Krayenhoff, E.</creator><creator>Voogt, James</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>DOA</scope></search><sort><creationdate>2016</creationdate><title>Daytime Thermal Anisotropy of Urban Neighbourhoods: Morphological Causation</title><author>Krayenhoff, E. ; Voogt, James</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c330t-157858ab5bc25b7e4d07bb7619ddc160cdecdba142b53e2371d69f3521e994813</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>effective anisotropy</topic><topic>microscale urban climate model</topic><topic>neighbourhood geometry</topic><topic>surface structure</topic><topic>surface temperature</topic><topic>thermal remote sensing</topic><topic>urban form</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Krayenhoff, E.</creatorcontrib><creatorcontrib>Voogt, James</creatorcontrib><collection>CrossRef</collection><collection>Directory of Open Access Journals</collection><jtitle>Remote sensing (Basel, Switzerland)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Krayenhoff, E.</au><au>Voogt, James</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Daytime Thermal Anisotropy of Urban Neighbourhoods: Morphological Causation</atitle><jtitle>Remote sensing (Basel, Switzerland)</jtitle><date>2016</date><risdate>2016</risdate><volume>8</volume><issue>2</issue><spage>108</spage><pages>108-</pages><issn>2072-4292</issn><eissn>2072-4292</eissn><abstract>Surface temperature is a key variable in boundary-layer meteorology and is typically acquired by remote observation of emitted thermal radiation. However, the three-dimensional structure of cities complicates matters: uneven solar heating of urban facets produces an “effective anisotropy” of surface thermal emission at the neighbourhood scale. Remotely-sensed urban surface temperature varies with sensor view angle as a consequence. The authors combine a microscale urban surface temperature model with a thermal remote sensing model to predict the effective anisotropy of simplified neighbourhood configurations. The former model provides detailed surface temperature distributions for a range of “urban” forms, and the remote sensing model computes aggregate temperatures for multiple view angles. The combined model’s ability to reproduce observed anisotropy is evaluated against measurements from a neighbourhood in Vancouver, Canada. As in previous modeling studies, anisotropy is underestimated. Addition of moderate coverages of small (sub-facet scale) structure can account for much of the missing anisotropy. Subsequently, over 1900 sensitivity simulations are performed with the model combination, and the dependence of daytime effective thermal anisotropy on diurnal solar path (i.e., latitude and time of day) and blunt neighbourhood form is assessed. The range of effective anisotropy, as well as the maximum difference from nadir-observed brightness temperature, peak for moderate building-height-to-spacing ratios (H/W), and scale with canyon (between-building) area; dispersed high-rise urban forms generate maximum anisotropy. Maximum anisotropy increases with solar elevation and scales with shortwave irradiance. Moreover, it depends linearly on H/W for H/W &lt; 1.25, with a slope that depends on maximum off-nadir sensor angle. Decreasing minimum brightness temperature is primarily responsible for this linear growth of maximum anisotropy. These results allow first order estimation of the minimum effective anisotropy magnitude of urban neighbourhoods as a function of building-height-to-spacing ratio, building plan area density, and shortwave irradiance. Finally, four “local climate zones” are simulated at two latitudes. Removal of neighbourhood street orientation regularity for these zones decreases maximum anisotropy by 3%–31%. Furthermore, thermal and radiative material properties are a weaker predictor of anisotropy than neighbourhood morphology. This study is the first systematic evaluation of effective anisotropy magnitude and causation for urban landscapes.</abstract><pub>MDPI AG</pub><doi>10.3390/rs8020108</doi><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2072-4292
ispartof Remote sensing (Basel, Switzerland), 2016, Vol.8 (2), p.108
issn 2072-4292
2072-4292
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_330e38f55fb440089a4df0a4fefdd538
source Publicly Available Content Database; IngentaConnect Journals
subjects effective anisotropy
microscale urban climate model
neighbourhood geometry
surface structure
surface temperature
thermal remote sensing
urban form
title Daytime Thermal Anisotropy of Urban Neighbourhoods: Morphological Causation
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-11T22%3A32%3A03IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-doaj_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Daytime%20Thermal%20Anisotropy%20of%20Urban%20Neighbourhoods:%20Morphological%20Causation&rft.jtitle=Remote%20sensing%20(Basel,%20Switzerland)&rft.au=Krayenhoff,%20E.&rft.date=2016&rft.volume=8&rft.issue=2&rft.spage=108&rft.pages=108-&rft.issn=2072-4292&rft.eissn=2072-4292&rft_id=info:doi/10.3390/rs8020108&rft_dat=%3Cdoaj_cross%3Eoai_doaj_org_article_330e38f55fb440089a4df0a4fefdd538%3C/doaj_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c330t-157858ab5bc25b7e4d07bb7619ddc160cdecdba142b53e2371d69f3521e994813%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true