46-Year (1973–2019) Permafrost Landscape Changes in the Hola Basin, Northeast China Using Machine Learning and Object-Oriented Classification
Land use and cover changes (LUCC) in permafrost regions have significant consequences on ecology, engineered systems, and the environment. Obtaining more details about LUCC is crucial for sustainable development, land conservation, and environment management. The Hola Basin (957 km<sup>2</s...
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MDPI AG
2021-05-01
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author | Raul-David Șerban Mihaela Șerban Ruixia He Huijun Jin Yan Li Xinyu Li Xinbin Wang Guoyu Li |
author_facet | Raul-David Șerban Mihaela Șerban Ruixia He Huijun Jin Yan Li Xinyu Li Xinbin Wang Guoyu Li |
author_sort | Raul-David Șerban |
collection | DOAJ |
description | Land use and cover changes (LUCC) in permafrost regions have significant consequences on ecology, engineered systems, and the environment. Obtaining more details about LUCC is crucial for sustainable development, land conservation, and environment management. The Hola Basin (957 km<sup>2</sup>) in the northernmost part of Northeast China, a boreal forest landscape underlain by discontinuous, sporadic, and isolated permafrost, was selected for the case study. The LUCC was analyzed using the Landsat archive of satellite images from 1973 to 2019. A thematic change detection analysis was performed by combining the object-based image analysis (OBIA) and the Support Vector Machine (SVM) algorithm. Four types of LUCC (forest, grass, water, and anthropic) were extracted with an overall accuracy of 80% for 1973 and >90% for 1986, 2000, and 2019. Forest, the dominant class (750 km<sup>2</sup> in 1973), declined by 88 km<sup>2</sup> (11.8%) from 1973 to 1986 but had a recovery of 78 km<sup>2</sup> (12.5%) from 2000 to 2019. Grass, the second-largest class (187 km<sup>2</sup> in 1973), increased by 86 km<sup>2</sup> (46.5%) between 1973 and 1986 and decreased by 90 km<sup>2</sup> (40%) between 2000 and 2019. The anthropic class continuously increased from 10 km<sup>2</sup> (1973) to 37 km<sup>2</sup> (2019). Major features in LUCC are attributed to rapid population growth, resource exploitation, agriculture intensification, economic development, and frequent forest fires. Under a pronounced climate warming, these drivers have been accelerating the degradation of permafrost, subsequently triggering natural hazards and deteriorating the ecological environment. This study represents a benchmark for sustainable LUCC management in the Hola Basin, Northeast China. |
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series | Remote Sensing |
spelling | doaj.art-c09a1d98565e46199b7e1def723851262023-11-21T19:35:08ZengMDPI AGRemote Sensing2072-42922021-05-011310191010.3390/rs1310191046-Year (1973–2019) Permafrost Landscape Changes in the Hola Basin, Northeast China Using Machine Learning and Object-Oriented ClassificationRaul-David Șerban0Mihaela Șerban1Ruixia He2Huijun Jin3Yan Li4Xinyu Li5Xinbin Wang6Guoyu Li7State Key Laboratory of Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, ChinaState Key Laboratory of Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, ChinaState Key Laboratory of Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, ChinaState Key Laboratory of Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, ChinaState Key Laboratory of Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, ChinaSchool of Civil Engineering, Harbin Institute of Technology, Harbin 150090, ChinaState Key Laboratory of Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, ChinaState Key Laboratory of Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, ChinaLand use and cover changes (LUCC) in permafrost regions have significant consequences on ecology, engineered systems, and the environment. Obtaining more details about LUCC is crucial for sustainable development, land conservation, and environment management. The Hola Basin (957 km<sup>2</sup>) in the northernmost part of Northeast China, a boreal forest landscape underlain by discontinuous, sporadic, and isolated permafrost, was selected for the case study. The LUCC was analyzed using the Landsat archive of satellite images from 1973 to 2019. A thematic change detection analysis was performed by combining the object-based image analysis (OBIA) and the Support Vector Machine (SVM) algorithm. Four types of LUCC (forest, grass, water, and anthropic) were extracted with an overall accuracy of 80% for 1973 and >90% for 1986, 2000, and 2019. Forest, the dominant class (750 km<sup>2</sup> in 1973), declined by 88 km<sup>2</sup> (11.8%) from 1973 to 1986 but had a recovery of 78 km<sup>2</sup> (12.5%) from 2000 to 2019. Grass, the second-largest class (187 km<sup>2</sup> in 1973), increased by 86 km<sup>2</sup> (46.5%) between 1973 and 1986 and decreased by 90 km<sup>2</sup> (40%) between 2000 and 2019. The anthropic class continuously increased from 10 km<sup>2</sup> (1973) to 37 km<sup>2</sup> (2019). Major features in LUCC are attributed to rapid population growth, resource exploitation, agriculture intensification, economic development, and frequent forest fires. Under a pronounced climate warming, these drivers have been accelerating the degradation of permafrost, subsequently triggering natural hazards and deteriorating the ecological environment. This study represents a benchmark for sustainable LUCC management in the Hola Basin, Northeast China.https://www.mdpi.com/2072-4292/13/10/1910land use and cover changes (LUCC)object-based image analysis (OBIA)Support Vector Machine (SVM)permafrostNortheast China |
spellingShingle | Raul-David Șerban Mihaela Șerban Ruixia He Huijun Jin Yan Li Xinyu Li Xinbin Wang Guoyu Li 46-Year (1973–2019) Permafrost Landscape Changes in the Hola Basin, Northeast China Using Machine Learning and Object-Oriented Classification Remote Sensing land use and cover changes (LUCC) object-based image analysis (OBIA) Support Vector Machine (SVM) permafrost Northeast China |
title | 46-Year (1973–2019) Permafrost Landscape Changes in the Hola Basin, Northeast China Using Machine Learning and Object-Oriented Classification |
title_full | 46-Year (1973–2019) Permafrost Landscape Changes in the Hola Basin, Northeast China Using Machine Learning and Object-Oriented Classification |
title_fullStr | 46-Year (1973–2019) Permafrost Landscape Changes in the Hola Basin, Northeast China Using Machine Learning and Object-Oriented Classification |
title_full_unstemmed | 46-Year (1973–2019) Permafrost Landscape Changes in the Hola Basin, Northeast China Using Machine Learning and Object-Oriented Classification |
title_short | 46-Year (1973–2019) Permafrost Landscape Changes in the Hola Basin, Northeast China Using Machine Learning and Object-Oriented Classification |
title_sort | 46 year 1973 2019 permafrost landscape changes in the hola basin northeast china using machine learning and object oriented classification |
topic | land use and cover changes (LUCC) object-based image analysis (OBIA) Support Vector Machine (SVM) permafrost Northeast China |
url | https://www.mdpi.com/2072-4292/13/10/1910 |
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