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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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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. |
format | Online Article Text |
id | pubmed-10693543 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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