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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ftzenodo:oai:zenodo.org:10435903 2024-09-09T19:19:25+00:00 Multitemporal monitoring of Impervious Surface Areas (ISA) changes in an Arctic setting, using ML, Remote Sensing data and GEE Dermosinoglou, Aikaterini Detsikas, Spyridon E. Petropoulos, George Fratsea, Loukia Maria Papadopoulos, Apostolos Detsikas, Spyridon E. Petropoulos, George Papadopoulos, Apostolos Fratsea, Loukia Maria 2023-12-27 https://doi.org/10.5281/zenodo.10435903 unknown Zenodo https://zenodo.org/communities/eo-persist https://doi.org/10.5281/zenodo.10435902 https://doi.org/10.5281/zenodo.10435903 oai:zenodo.org:10435903 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode info:eu-repo/semantics/bookPart 2023 ftzenodo https://doi.org/10.5281/zenodo.1043590310.5281/zenodo.10435902 2024-07-25T22:16:56Z 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 factors associated with urban sprawl and their interaction with the challenges posed by climate change in Arctic environments Book Part Arctic Climate change Tromso Tromso Zenodo Arctic Tromso ENVELOPE(16.546,16.546,68.801,68.801) |
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Zenodo |
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ftzenodo |
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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 factors associated with urban sprawl and their interaction with the challenges posed by climate change in Arctic environments |
author2 |
Detsikas, Spyridon E. Petropoulos, George Papadopoulos, Apostolos Fratsea, Loukia Maria |
format |
Book Part |
author |
Dermosinoglou, Aikaterini Detsikas, Spyridon E. Petropoulos, George Fratsea, Loukia Maria Papadopoulos, Apostolos |
spellingShingle |
Dermosinoglou, Aikaterini Detsikas, Spyridon E. Petropoulos, George Fratsea, Loukia Maria Papadopoulos, Apostolos Multitemporal monitoring of Impervious Surface Areas (ISA) changes in an Arctic setting, using ML, Remote Sensing data and GEE |
author_facet |
Dermosinoglou, Aikaterini Detsikas, Spyridon E. Petropoulos, George Fratsea, Loukia Maria Papadopoulos, Apostolos |
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://doi.org/10.5281/zenodo.10435903 |
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://zenodo.org/communities/eo-persist https://doi.org/10.5281/zenodo.10435902 https://doi.org/10.5281/zenodo.10435903 oai:zenodo.org:10435903 |
op_rights |
info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode |
op_doi |
https://doi.org/10.5281/zenodo.1043590310.5281/zenodo.10435902 |
_version_ |
1809759528087977984 |