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District-scale surface temperatures generated from high-resolution longitudinal thermal infrared images

This paper describes a dataset collected by infrared thermography, a non-contact, non-intrusive technique to acquire data and analyze the built environment in various aspects. While most studies focus on the city and building scales, an observatory installed on a rooftop provides high temporal and s...

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Autores principales: Lin, Subin, Ramani, Vasantha, Martin, Miguel, Arjunan, Pandarasamy, Chong, Adrian, Biljecki, Filip, Ignatius, Marcel, Poolla, Kameshwar, Miller, Clayton
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10693543/
https://www.ncbi.nlm.nih.gov/pubmed/38042845
http://dx.doi.org/10.1038/s41597-023-02749-0
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author Lin, Subin
Ramani, Vasantha
Martin, Miguel
Arjunan, Pandarasamy
Chong, Adrian
Biljecki, Filip
Ignatius, Marcel
Poolla, Kameshwar
Miller, Clayton
author_facet Lin, Subin
Ramani, Vasantha
Martin, Miguel
Arjunan, Pandarasamy
Chong, Adrian
Biljecki, Filip
Ignatius, Marcel
Poolla, Kameshwar
Miller, Clayton
author_sort Lin, Subin
collection PubMed
description This paper describes a dataset collected by infrared thermography, a non-contact, non-intrusive technique to acquire data and analyze the built environment in various aspects. While most studies focus on the city and building scales, an observatory installed on a rooftop provides high temporal and spatial resolution observations with dynamic interactions on the district scale. The rooftop infrared thermography observatory with a multi-modal platform capable of assessing a wide range of dynamic processes in urban systems was deployed in Singapore. It was placed on the top of two buildings that overlook the outdoor context of the National University of Singapore campus. The platform collects remote sensing data from tropical areas on a temporal scale, allowing users to determine the temperature trend of individual features such as buildings, roads, and vegetation. The dataset includes 1,365,921 thermal images collected on average at approximately 10-second intervals from two locations during ten months.
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spelling pubmed-106935432023-12-04 District-scale surface temperatures generated from high-resolution longitudinal thermal infrared images Lin, Subin Ramani, Vasantha Martin, Miguel Arjunan, Pandarasamy Chong, Adrian Biljecki, Filip Ignatius, Marcel Poolla, Kameshwar Miller, Clayton Sci Data Data Descriptor This paper describes a dataset collected by infrared thermography, a non-contact, non-intrusive technique to acquire data and analyze the built environment in various aspects. While most studies focus on the city and building scales, an observatory installed on a rooftop provides high temporal and spatial resolution observations with dynamic interactions on the district scale. The rooftop infrared thermography observatory with a multi-modal platform capable of assessing a wide range of dynamic processes in urban systems was deployed in Singapore. It was placed on the top of two buildings that overlook the outdoor context of the National University of Singapore campus. The platform collects remote sensing data from tropical areas on a temporal scale, allowing users to determine the temperature trend of individual features such as buildings, roads, and vegetation. The dataset includes 1,365,921 thermal images collected on average at approximately 10-second intervals from two locations during ten months. Nature Publishing Group UK 2023-12-02 /pmc/articles/PMC10693543/ /pubmed/38042845 http://dx.doi.org/10.1038/s41597-023-02749-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Data Descriptor
Lin, Subin
Ramani, Vasantha
Martin, Miguel
Arjunan, Pandarasamy
Chong, Adrian
Biljecki, Filip
Ignatius, Marcel
Poolla, Kameshwar
Miller, Clayton
District-scale surface temperatures generated from high-resolution longitudinal thermal infrared images
title District-scale surface temperatures generated from high-resolution longitudinal thermal infrared images
title_full District-scale surface temperatures generated from high-resolution longitudinal thermal infrared images
title_fullStr District-scale surface temperatures generated from high-resolution longitudinal thermal infrared images
title_full_unstemmed District-scale surface temperatures generated from high-resolution longitudinal thermal infrared images
title_short District-scale surface temperatures generated from high-resolution longitudinal thermal infrared images
title_sort district-scale surface temperatures generated from high-resolution longitudinal thermal infrared images
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10693543/
https://www.ncbi.nlm.nih.gov/pubmed/38042845
http://dx.doi.org/10.1038/s41597-023-02749-0
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