Multitemporal monitoring of Impervious Surface Areas (ISA) changes in an Arctic setting, using ML, Remote Sensing data and GEE ...
Urban expansion in Arctic environments presents unique challenges and opportunities for sustainable development, environmental management, and adaptation to the impacts of climate change. The special characteristics of these regions, including extreme climatic conditions and limited infrastructure,...
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Online Access: | https://dx.doi.org/10.5281/zenodo.10435902 https://zenodo.org/doi/10.5281/zenodo.10435902 |
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ftdatacite:10.5281/zenodo.10435902 2024-02-04T09:57:25+01:00 Multitemporal monitoring of Impervious Surface Areas (ISA) changes in an Arctic setting, using ML, Remote Sensing data and GEE ... Dermosinoglou, Aikaterini Fratsea, Loukia Maria Papadopoulos, Apostolos Petropoulos, George Detsikas, Spyridon E. 2023 https://dx.doi.org/10.5281/zenodo.10435902 https://zenodo.org/doi/10.5281/zenodo.10435902 unknown Zenodo https://dx.doi.org/10.5281/zenodo.10435903 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 Chapter article BookChapter 2023 ftdatacite https://doi.org/10.5281/zenodo.1043590210.5281/zenodo.10435903 2024-01-05T11:14:20Z Urban expansion in Arctic environments presents unique challenges and opportunities for sustainable development, environmental management, and adaptation to the impacts of climate change. The special characteristics of these regions, including extreme climatic conditions and limited infrastructure, require customized approaches for monitoring and planning urban growth. The aim of the present study is the multi-temporal mapping of urban changes, through Impervious Surface Areas (ISA), in an Arctic setting characterized by high structural density, over the past decade. This endeavor is implemented by the application of Machine Learning classification methods in conjunction with Sentinel satellite imagery, while the execution of this methodology is carried out in Google Earth Engine (GEE) cloud platform. The results of this study map with high accuracy ISA changes in Tromso area from 1993 to 2023. These findings hold the promise of enhancing our comprehension of the dynamics behind urban expansion, the primary ... Article in Journal/Newspaper Arctic Climate change Tromso Tromso DataCite Metadata Store (German National Library of Science and Technology) Arctic Tromso ENVELOPE(16.546,16.546,68.801,68.801) |
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Open Polar |
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DataCite Metadata Store (German National Library of Science and Technology) |
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ftdatacite |
language |
unknown |
description |
Urban expansion in Arctic environments presents unique challenges and opportunities for sustainable development, environmental management, and adaptation to the impacts of climate change. The special characteristics of these regions, including extreme climatic conditions and limited infrastructure, require customized approaches for monitoring and planning urban growth. The aim of the present study is the multi-temporal mapping of urban changes, through Impervious Surface Areas (ISA), in an Arctic setting characterized by high structural density, over the past decade. This endeavor is implemented by the application of Machine Learning classification methods in conjunction with Sentinel satellite imagery, while the execution of this methodology is carried out in Google Earth Engine (GEE) cloud platform. The results of this study map with high accuracy ISA changes in Tromso area from 1993 to 2023. These findings hold the promise of enhancing our comprehension of the dynamics behind urban expansion, the primary ... |
format |
Article in Journal/Newspaper |
author |
Dermosinoglou, Aikaterini Fratsea, Loukia Maria Papadopoulos, Apostolos Petropoulos, George Detsikas, Spyridon E. |
spellingShingle |
Dermosinoglou, Aikaterini Fratsea, Loukia Maria Papadopoulos, Apostolos Petropoulos, George Detsikas, Spyridon E. Multitemporal monitoring of Impervious Surface Areas (ISA) changes in an Arctic setting, using ML, Remote Sensing data and GEE ... |
author_facet |
Dermosinoglou, Aikaterini Fratsea, Loukia Maria Papadopoulos, Apostolos Petropoulos, George Detsikas, Spyridon E. |
author_sort |
Dermosinoglou, Aikaterini |
title |
Multitemporal monitoring of Impervious Surface Areas (ISA) changes in an Arctic setting, using ML, Remote Sensing data and GEE ... |
title_short |
Multitemporal monitoring of Impervious Surface Areas (ISA) changes in an Arctic setting, using ML, Remote Sensing data and GEE ... |
title_full |
Multitemporal monitoring of Impervious Surface Areas (ISA) changes in an Arctic setting, using ML, Remote Sensing data and GEE ... |
title_fullStr |
Multitemporal monitoring of Impervious Surface Areas (ISA) changes in an Arctic setting, using ML, Remote Sensing data and GEE ... |
title_full_unstemmed |
Multitemporal monitoring of Impervious Surface Areas (ISA) changes in an Arctic setting, using ML, Remote Sensing data and GEE ... |
title_sort |
multitemporal monitoring of impervious surface areas (isa) changes in an arctic setting, using ml, remote sensing data and gee ... |
publisher |
Zenodo |
publishDate |
2023 |
url |
https://dx.doi.org/10.5281/zenodo.10435902 https://zenodo.org/doi/10.5281/zenodo.10435902 |
long_lat |
ENVELOPE(16.546,16.546,68.801,68.801) |
geographic |
Arctic Tromso |
geographic_facet |
Arctic Tromso |
genre |
Arctic Climate change Tromso Tromso |
genre_facet |
Arctic Climate change Tromso Tromso |
op_relation |
https://dx.doi.org/10.5281/zenodo.10435903 |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_doi |
https://doi.org/10.5281/zenodo.1043590210.5281/zenodo.10435903 |
_version_ |
1789961758057693184 |