Quantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scale
The climate of a city influences the ways in which its outdoor spaces are used. Especially, public spaces intended for use by pedestrians and cyclists, such as parks, squares, residential and commercial streets, and foot and cycle paths will be used and enjoyed more frequently if they have a comfort...
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Online Access: | http://dx.doi.org/10.1080/22797254.2019.1646104 |
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doaj-6cf8a38307be475d8c7e3eba0257c2fb2020-12-17T17:28:34ZengTaylor & Francis GroupEuropean Journal of Remote Sensing2279-72542019-12-01520748310.1080/22797254.2019.16461041646104Quantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scaleElena Barbierato0Iacopo Bernetti1Irene Capecchi2Claudio Saragosa3University of FlorenceUniversity of FlorenceUniversity of FlorenceUniversity of FlorenceThe climate of a city influences the ways in which its outdoor spaces are used. Especially, public spaces intended for use by pedestrians and cyclists, such as parks, squares, residential and commercial streets, and foot and cycle paths will be used and enjoyed more frequently if they have a comfortable and healthy climate. Due to the predicted global temperature increase, urban climate is likely to become more uncomfortable, especially in summer when an increase in heat stress is expected. Urban forestry has been proposed as one approach for mitigating the human health consequences of increased temperature resulting from climate change. The aims of the current research were to (a) provide a transferable methodology useful for analyzing the effect of urban trees on surface temperature reduction, particularly in public spaces, and (b) provide high-resolution urban mapping for adaptation strategies to climate change based on green space projects. To achieve the established aims, we developed a methodology that uses multisource data: LiDAR data, high-resolution Landsat imagery, global climate model data from CMIP5 (IPPC Fifth Assessment), and data from meteorological stations. The proposed model can be a useful tool for validating the efficiency of design simulations of new green spaces for temperature mitigation.http://dx.doi.org/10.1080/22797254.2019.1646104land surface temperature (lst)climate changelight detection and ranging (lidar)urban foresturban heat wavesclimate changeland surface temperaturelidarsolar radiationurban foresturban heat island |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Elena Barbierato Iacopo Bernetti Irene Capecchi Claudio Saragosa |
spellingShingle |
Elena Barbierato Iacopo Bernetti Irene Capecchi Claudio Saragosa Quantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scale European Journal of Remote Sensing land surface temperature (lst) climate change light detection and ranging (lidar) urban forest urban heat waves climate change land surface temperature lidar solar radiation urban forest urban heat island |
author_facet |
Elena Barbierato Iacopo Bernetti Irene Capecchi Claudio Saragosa |
author_sort |
Elena Barbierato |
title |
Quantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scale |
title_short |
Quantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scale |
title_full |
Quantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scale |
title_fullStr |
Quantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scale |
title_full_unstemmed |
Quantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scale |
title_sort |
quantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scale |
publisher |
Taylor & Francis Group |
series |
European Journal of Remote Sensing |
issn |
2279-7254 |
publishDate |
2019-12-01 |
description |
The climate of a city influences the ways in which its outdoor spaces are used. Especially, public spaces intended for use by pedestrians and cyclists, such as parks, squares, residential and commercial streets, and foot and cycle paths will be used and enjoyed more frequently if they have a comfortable and healthy climate. Due to the predicted global temperature increase, urban climate is likely to become more uncomfortable, especially in summer when an increase in heat stress is expected. Urban forestry has been proposed as one approach for mitigating the human health consequences of increased temperature resulting from climate change. The aims of the current research were to (a) provide a transferable methodology useful for analyzing the effect of urban trees on surface temperature reduction, particularly in public spaces, and (b) provide high-resolution urban mapping for adaptation strategies to climate change based on green space projects. To achieve the established aims, we developed a methodology that uses multisource data: LiDAR data, high-resolution Landsat imagery, global climate model data from CMIP5 (IPPC Fifth Assessment), and data from meteorological stations. The proposed model can be a useful tool for validating the efficiency of design simulations of new green spaces for temperature mitigation. |
topic |
land surface temperature (lst) climate change light detection and ranging (lidar) urban forest urban heat waves climate change land surface temperature lidar solar radiation urban forest urban heat island |
url |
http://dx.doi.org/10.1080/22797254.2019.1646104 |
work_keys_str_mv |
AT elenabarbierato quantifyingtheimpactoftreesonlandsurfacetemperatureadownscalingalgorithmatcityscale AT iacopobernetti quantifyingtheimpactoftreesonlandsurfacetemperatureadownscalingalgorithmatcityscale AT irenecapecchi quantifyingtheimpactoftreesonlandsurfacetemperatureadownscalingalgorithmatcityscale AT claudiosaragosa quantifyingtheimpactoftreesonlandsurfacetemperatureadownscalingalgorithmatcityscale |
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