Permafrost Probability Mapping at a 30 m Resolution in Arxan Based on Multiple Characteristic Variables and Maximum Entropy Classifier
High-resolution permafrost mapping is an important direction in permafrost research. Arxan is a typical area with permafrost degradation and is situated on the southern boundary of the permafrost region in Northeast China. With the help of Google Earth Engine (GEE), the maximum entropy classifier (M...
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MDPI AG
2023-09-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/19/10692 |
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| author | Ying Guo Shuai Liu Lisha Qiu Yan Wang Chengcheng Zhang Wei Shan |
| author_facet | Ying Guo Shuai Liu Lisha Qiu Yan Wang Chengcheng Zhang Wei Shan |
| author_sort | Ying Guo |
| collection | DOAJ |
| description | High-resolution permafrost mapping is an important direction in permafrost research. Arxan is a typical area with permafrost degradation and is situated on the southern boundary of the permafrost region in Northeast China. With the help of Google Earth Engine (GEE), the maximum entropy classifier (MaxEnt) is used for permafrost mapping using the land surface temperature (LST) of different seasons, deviation from mean elevation (DEV), solar radiation (SR), normalized difference vegetation index (NDVI), and normalized difference water index (NDWI) as the characteristic variables. The prior data of permafrost distribution were primarily based on 201 borehole data and field investigation data. A permafrost probability (PP) distribution map with a resolution of 30 m was obtained. The receiver operating characteristic (ROC) curve was used to test the distribution results, with an area under the curve (AUC) value of 0.986. The results characterize the distribution of permafrost at a high resolution. Permafrost is mainly distributed in the Greater Khingan Mountains (GKM) in the research area, which run from the northeast to the southwest, followed by low-altitude area in the northwest. According to topographic distribution, permafrost is primarily found on slope surfaces, with minor amounts present in peaks, ridges, and valleys. The employed PP distribution mapping method offers a suggestion for high-resolution permafrost mapping in permafrost degradation areas. |
| first_indexed | 2024-03-10T21:49:47Z |
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| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T21:49:47Z |
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| spelling | doaj.art-a3fa02bf669b410dae797b293f1b49722023-11-19T14:02:55ZengMDPI AGApplied Sciences2076-34172023-09-0113191069210.3390/app131910692Permafrost Probability Mapping at a 30 m Resolution in Arxan Based on Multiple Characteristic Variables and Maximum Entropy ClassifierYing Guo0Shuai Liu1Lisha Qiu2Yan Wang3Chengcheng Zhang4Wei Shan5Institute of Cold Regions Science and Engineering, Northeast Forestry University, Harbin 150040, ChinaInstitute of Cold Regions Science and Engineering, Northeast Forestry University, Harbin 150040, ChinaInstitute of Cold Regions Science and Engineering, Northeast Forestry University, Harbin 150040, ChinaInstitute of Cold Regions Science and Engineering, Northeast Forestry University, Harbin 150040, ChinaInstitute of Cold Regions Science and Engineering, Northeast Forestry University, Harbin 150040, ChinaInstitute of Cold Regions Science and Engineering, Northeast Forestry University, Harbin 150040, ChinaHigh-resolution permafrost mapping is an important direction in permafrost research. Arxan is a typical area with permafrost degradation and is situated on the southern boundary of the permafrost region in Northeast China. With the help of Google Earth Engine (GEE), the maximum entropy classifier (MaxEnt) is used for permafrost mapping using the land surface temperature (LST) of different seasons, deviation from mean elevation (DEV), solar radiation (SR), normalized difference vegetation index (NDVI), and normalized difference water index (NDWI) as the characteristic variables. The prior data of permafrost distribution were primarily based on 201 borehole data and field investigation data. A permafrost probability (PP) distribution map with a resolution of 30 m was obtained. The receiver operating characteristic (ROC) curve was used to test the distribution results, with an area under the curve (AUC) value of 0.986. The results characterize the distribution of permafrost at a high resolution. Permafrost is mainly distributed in the Greater Khingan Mountains (GKM) in the research area, which run from the northeast to the southwest, followed by low-altitude area in the northwest. According to topographic distribution, permafrost is primarily found on slope surfaces, with minor amounts present in peaks, ridges, and valleys. The employed PP distribution mapping method offers a suggestion for high-resolution permafrost mapping in permafrost degradation areas.https://www.mdpi.com/2076-3417/13/19/10692ArxanGoogle Earth Enginehigh-resolution permafrost mappingmaximum entropy classificationpermafrost probability |
| spellingShingle | Ying Guo Shuai Liu Lisha Qiu Yan Wang Chengcheng Zhang Wei Shan Permafrost Probability Mapping at a 30 m Resolution in Arxan Based on Multiple Characteristic Variables and Maximum Entropy Classifier Applied Sciences Arxan Google Earth Engine high-resolution permafrost mapping maximum entropy classification permafrost probability |
| title | Permafrost Probability Mapping at a 30 m Resolution in Arxan Based on Multiple Characteristic Variables and Maximum Entropy Classifier |
| title_full | Permafrost Probability Mapping at a 30 m Resolution in Arxan Based on Multiple Characteristic Variables and Maximum Entropy Classifier |
| title_fullStr | Permafrost Probability Mapping at a 30 m Resolution in Arxan Based on Multiple Characteristic Variables and Maximum Entropy Classifier |
| title_full_unstemmed | Permafrost Probability Mapping at a 30 m Resolution in Arxan Based on Multiple Characteristic Variables and Maximum Entropy Classifier |
| title_short | Permafrost Probability Mapping at a 30 m Resolution in Arxan Based on Multiple Characteristic Variables and Maximum Entropy Classifier |
| title_sort | permafrost probability mapping at a 30 m resolution in arxan based on multiple characteristic variables and maximum entropy classifier |
| topic | Arxan Google Earth Engine high-resolution permafrost mapping maximum entropy classification permafrost probability |
| url | https://www.mdpi.com/2076-3417/13/19/10692 |
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