Assessing Changes in Boreal Vegetation of Kola Peninsula via Large-Scale Land Cover Classification between 1985 and 2021
The effective monitoring of boreal and tundra vegetation at different scales and environmental management at latitudes above 50 degrees North relies heavily on remote sensing. The vastness, remoteness and, in the case of Russia, the difficulty of access to boreal–tundra vegetation make it an ideal t...
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Online Access: | https://doi.org/10.3390/rs14215616 https://doaj.org/article/06e79a8a681d4929b5247c8d28b07061 |
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ftdoajarticles:oai:doaj.org/article:06e79a8a681d4929b5247c8d28b07061 2023-05-15T15:16:49+02:00 Assessing Changes in Boreal Vegetation of Kola Peninsula via Large-Scale Land Cover Classification between 1985 and 2021 Ekaterina Sklyar Gareth Rees 2022-11-01T00:00:00Z https://doi.org/10.3390/rs14215616 https://doaj.org/article/06e79a8a681d4929b5247c8d28b07061 EN eng MDPI AG https://www.mdpi.com/2072-4292/14/21/5616 https://doaj.org/toc/2072-4292 doi:10.3390/rs14215616 2072-4292 https://doaj.org/article/06e79a8a681d4929b5247c8d28b07061 Remote Sensing, Vol 14, Iss 5616, p 5616 (2022) boreal forest northern vegetation human impact climate change land cover monitoring Science Q article 2022 ftdoajarticles https://doi.org/10.3390/rs14215616 2022-12-30T20:23:06Z The effective monitoring of boreal and tundra vegetation at different scales and environmental management at latitudes above 50 degrees North relies heavily on remote sensing. The vastness, remoteness and, in the case of Russia, the difficulty of access to boreal–tundra vegetation make it an ideal technique for vegetation monitoring in the Kola peninsula, located predominantly beyond the Arctic circle in the European part of Russia. Since the 1930s, this area has been highly urbanised and exposed to strong influence by a number of different types of human impact, such as toxic pollutions, fires, mineral excavation, grazing, logging, etc. Extensive open archives of remote sensing imagery as well as recent advances in machine learning further enable the efficient use of remote sensing methods for assessing land cover changes. Here, we present the results of mapping northern vegetation land cover and changes in it over a large territory, in time and under human impact based on remote imagery from Landsat TM, ETM+ and OLI. We study the area of about 37,000 km <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mrow></mrow><mn>2</mn></msup></semantics></math> located in the central part of the Kola peninsula in the boreal, pre-tundra and tundra between 1985 and 2021 with a time interval of approximately 5 years and confirm the correlations between the human pressure and the level of vegetation changes. We put those into the perspective of year-on-year changes in the temperature and precipitation regimes and describe the recovery of the damaged original boreal vegetation (dominated by spruce) through pine and deciduous vegetation. As a by-product of this study, we develop and test an approach for the semi-automated processing and classification of Landsat images using the novel TensorFlow machine learning technique (widely spread across other disciplines) that enables high-throughput classification, even on conventional ... Article in Journal/Newspaper Arctic Climate change kola peninsula Tundra Directory of Open Access Journals: DOAJ Articles Arctic Kola Peninsula Remote Sensing 14 21 5616 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
boreal forest northern vegetation human impact climate change land cover monitoring Science Q |
spellingShingle |
boreal forest northern vegetation human impact climate change land cover monitoring Science Q Ekaterina Sklyar Gareth Rees Assessing Changes in Boreal Vegetation of Kola Peninsula via Large-Scale Land Cover Classification between 1985 and 2021 |
topic_facet |
boreal forest northern vegetation human impact climate change land cover monitoring Science Q |
description |
The effective monitoring of boreal and tundra vegetation at different scales and environmental management at latitudes above 50 degrees North relies heavily on remote sensing. The vastness, remoteness and, in the case of Russia, the difficulty of access to boreal–tundra vegetation make it an ideal technique for vegetation monitoring in the Kola peninsula, located predominantly beyond the Arctic circle in the European part of Russia. Since the 1930s, this area has been highly urbanised and exposed to strong influence by a number of different types of human impact, such as toxic pollutions, fires, mineral excavation, grazing, logging, etc. Extensive open archives of remote sensing imagery as well as recent advances in machine learning further enable the efficient use of remote sensing methods for assessing land cover changes. Here, we present the results of mapping northern vegetation land cover and changes in it over a large territory, in time and under human impact based on remote imagery from Landsat TM, ETM+ and OLI. We study the area of about 37,000 km <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mrow></mrow><mn>2</mn></msup></semantics></math> located in the central part of the Kola peninsula in the boreal, pre-tundra and tundra between 1985 and 2021 with a time interval of approximately 5 years and confirm the correlations between the human pressure and the level of vegetation changes. We put those into the perspective of year-on-year changes in the temperature and precipitation regimes and describe the recovery of the damaged original boreal vegetation (dominated by spruce) through pine and deciduous vegetation. As a by-product of this study, we develop and test an approach for the semi-automated processing and classification of Landsat images using the novel TensorFlow machine learning technique (widely spread across other disciplines) that enables high-throughput classification, even on conventional ... |
format |
Article in Journal/Newspaper |
author |
Ekaterina Sklyar Gareth Rees |
author_facet |
Ekaterina Sklyar Gareth Rees |
author_sort |
Ekaterina Sklyar |
title |
Assessing Changes in Boreal Vegetation of Kola Peninsula via Large-Scale Land Cover Classification between 1985 and 2021 |
title_short |
Assessing Changes in Boreal Vegetation of Kola Peninsula via Large-Scale Land Cover Classification between 1985 and 2021 |
title_full |
Assessing Changes in Boreal Vegetation of Kola Peninsula via Large-Scale Land Cover Classification between 1985 and 2021 |
title_fullStr |
Assessing Changes in Boreal Vegetation of Kola Peninsula via Large-Scale Land Cover Classification between 1985 and 2021 |
title_full_unstemmed |
Assessing Changes in Boreal Vegetation of Kola Peninsula via Large-Scale Land Cover Classification between 1985 and 2021 |
title_sort |
assessing changes in boreal vegetation of kola peninsula via large-scale land cover classification between 1985 and 2021 |
publisher |
MDPI AG |
publishDate |
2022 |
url |
https://doi.org/10.3390/rs14215616 https://doaj.org/article/06e79a8a681d4929b5247c8d28b07061 |
geographic |
Arctic Kola Peninsula |
geographic_facet |
Arctic Kola Peninsula |
genre |
Arctic Climate change kola peninsula Tundra |
genre_facet |
Arctic Climate change kola peninsula Tundra |
op_source |
Remote Sensing, Vol 14, Iss 5616, p 5616 (2022) |
op_relation |
https://www.mdpi.com/2072-4292/14/21/5616 https://doaj.org/toc/2072-4292 doi:10.3390/rs14215616 2072-4292 https://doaj.org/article/06e79a8a681d4929b5247c8d28b07061 |
op_doi |
https://doi.org/10.3390/rs14215616 |
container_title |
Remote Sensing |
container_volume |
14 |
container_issue |
21 |
container_start_page |
5616 |
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1766347108958339072 |