Landsat-observed changes in forest cover and attribution analysis over Northern China from 1996‒2020
ABSTRACTForest dynamics provide important information on the ecological environment. The Three-North Shelter Forest Program (TNSFP) is one of the world’s largest reforestation/afforestation programs, however the actual changes in forest cover in the Three-North Regions (TNR) of China resulting from...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | GIScience & Remote Sensing |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/15481603.2023.2300214 |
| _version_ | 1797354392618270720 |
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| author | Xiaobang Liu Shunlin Liang Han Ma Bing Li Yufang Zhang Yingying Li Tao He Guodong Zhang Jianglei Xu Changhao Xiong Rui Ma Wenfu Wu Jiahua Teng |
| author_facet | Xiaobang Liu Shunlin Liang Han Ma Bing Li Yufang Zhang Yingying Li Tao He Guodong Zhang Jianglei Xu Changhao Xiong Rui Ma Wenfu Wu Jiahua Teng |
| author_sort | Xiaobang Liu |
| collection | DOAJ |
| description | ABSTRACTForest dynamics provide important information on the ecological environment. The Three-North Shelter Forest Program (TNSFP) is one of the world’s largest reforestation/afforestation programs, however the actual changes in forest cover in the Three-North Regions (TNR) of China resulting from this program are highly uncertain. This study quantified changes in fractional forest cover (FFC) at 30 m using Landsat data from 1996 to 2020. Using the Google Earth Engine platform, more than 40,000 images from Landsat-5, Landsat 7 and Landsat-8 were integrated, and the annual surface reflectance was normalized based on the multi-band least squares regression and maximum normalized difference vegetation index composite method. An ensemble learning model trained using high-resolution Gao-Fen 2 satellite imagery was used to generate the FFC long time-series product. FFC showed an increasing trend with average rates of 0.022/10a in the last 25 years, and 0.03/10a after 2010 largely corresponding to the fourth and fifth phases of the TNSFP. There are significant regional differences in the relationship between FFC and air temperature ([Formula: see text] = 0.37) and precipitation ([Formula: see text] = 0.49). The increased air temperature in arid and less rainy areas inhibit the FFC increase, whereas the increase in precipitation had a promoting effect. FFC appeared more sensitive to changes in solar radiation and heat conditions in humid and rainy areas. The attribution analysis revealed that 34% of FFC changes were caused by climatic variables and 66% were caused by non-climatic factors. Among them, afforestation associated with the TNSFP significantly increased FFC, and forest fire is a key factor of forest change in the Greater Khingan Ranges and Lesser Khingan Ranges regions. Planting single tree species caused biological disasters in forests of Xinjiang and Inner Mongolia. Further analysis of the increased FFC using high-level satellite products demonstrated an improvement in environmental conditions with cooler land surface temperature and higher vegetation gross primary production over the TNR. |
| first_indexed | 2024-03-08T13:49:46Z |
| format | Article |
| id | doaj.art-ecce374f56194733ba517f1e679f3fa8 |
| institution | Directory Open Access Journal |
| issn | 1548-1603 1943-7226 |
| language | English |
| last_indexed | 2024-03-08T13:49:46Z |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | GIScience & Remote Sensing |
| spelling | doaj.art-ecce374f56194733ba517f1e679f3fa82024-01-16T06:46:57ZengTaylor & Francis GroupGIScience & Remote Sensing1548-16031943-72262024-12-0161110.1080/15481603.2023.2300214Landsat-observed changes in forest cover and attribution analysis over Northern China from 1996‒2020Xiaobang Liu0Shunlin Liang1Han Ma2Bing Li3Yufang Zhang4Yingying Li5Tao He6Guodong Zhang7Jianglei Xu8Changhao Xiong9Rui Ma10Wenfu Wu11Jiahua Teng12Hubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaJockey Club Laboratory of Quantitative Remote Sensing, Department of Geography, University of Hong Kong, Hong Kong, ChinaJockey Club Laboratory of Quantitative Remote Sensing, Department of Geography, University of Hong Kong, Hong Kong, ChinaKey Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization of Henan Province, Henan University, Kaifeng, ChinaHubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaHubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaHubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaHubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaHubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaHubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaHubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaSatellite Environment Protetion Key Laboratory of Satellite Remote Sensing, Satellite Application Center for Ecology and Environment, Ministry of Ecology and Environment, Beijing, ChinaABSTRACTForest dynamics provide important information on the ecological environment. The Three-North Shelter Forest Program (TNSFP) is one of the world’s largest reforestation/afforestation programs, however the actual changes in forest cover in the Three-North Regions (TNR) of China resulting from this program are highly uncertain. This study quantified changes in fractional forest cover (FFC) at 30 m using Landsat data from 1996 to 2020. Using the Google Earth Engine platform, more than 40,000 images from Landsat-5, Landsat 7 and Landsat-8 were integrated, and the annual surface reflectance was normalized based on the multi-band least squares regression and maximum normalized difference vegetation index composite method. An ensemble learning model trained using high-resolution Gao-Fen 2 satellite imagery was used to generate the FFC long time-series product. FFC showed an increasing trend with average rates of 0.022/10a in the last 25 years, and 0.03/10a after 2010 largely corresponding to the fourth and fifth phases of the TNSFP. There are significant regional differences in the relationship between FFC and air temperature ([Formula: see text] = 0.37) and precipitation ([Formula: see text] = 0.49). The increased air temperature in arid and less rainy areas inhibit the FFC increase, whereas the increase in precipitation had a promoting effect. FFC appeared more sensitive to changes in solar radiation and heat conditions in humid and rainy areas. The attribution analysis revealed that 34% of FFC changes were caused by climatic variables and 66% were caused by non-climatic factors. Among them, afforestation associated with the TNSFP significantly increased FFC, and forest fire is a key factor of forest change in the Greater Khingan Ranges and Lesser Khingan Ranges regions. Planting single tree species caused biological disasters in forests of Xinjiang and Inner Mongolia. Further analysis of the increased FFC using high-level satellite products demonstrated an improvement in environmental conditions with cooler land surface temperature and higher vegetation gross primary production over the TNR.https://www.tandfonline.com/doi/10.1080/15481603.2023.2300214ForestsNorthern Chinacover change analysisclimate variablesdriver contribution ratesfeedback effects |
| spellingShingle | Xiaobang Liu Shunlin Liang Han Ma Bing Li Yufang Zhang Yingying Li Tao He Guodong Zhang Jianglei Xu Changhao Xiong Rui Ma Wenfu Wu Jiahua Teng Landsat-observed changes in forest cover and attribution analysis over Northern China from 1996‒2020 GIScience & Remote Sensing Forests Northern China cover change analysis climate variables driver contribution rates feedback effects |
| title | Landsat-observed changes in forest cover and attribution analysis over Northern China from 1996‒2020 |
| title_full | Landsat-observed changes in forest cover and attribution analysis over Northern China from 1996‒2020 |
| title_fullStr | Landsat-observed changes in forest cover and attribution analysis over Northern China from 1996‒2020 |
| title_full_unstemmed | Landsat-observed changes in forest cover and attribution analysis over Northern China from 1996‒2020 |
| title_short | Landsat-observed changes in forest cover and attribution analysis over Northern China from 1996‒2020 |
| title_sort | landsat observed changes in forest cover and attribution analysis over northern china from 1996 2020 |
| topic | Forests Northern China cover change analysis climate variables driver contribution rates feedback effects |
| url | https://www.tandfonline.com/doi/10.1080/15481603.2023.2300214 |
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