Rapid Vegetation Growth due to Shifts in Climate from Slow to Sustained Warming over Terrestrial Ecosystems in China from 1980 to 2018
文献类型：期刊论文
| 作者 | Zhang, Yuxin; Wang, Junbang; Watson, Alan E. E. |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2023-08-01 |
| 卷号 | 15期号:15页码:3707 |
| 关键词 | FPAR artificial neural network interannual trend climate change terrestrial ecosystems |
| ISSN号 | 2072-4292 |
| DOI | 10.3390/rs15153707 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | The fraction of absorbed photosynthetically active radiation (FPAR) is a key biophysiological parameter of terrestrial ecosystems. However, due to a lack of data with adequate spatial resolution and in long enough time series, there have been limitations in exploring the spatiotemporal changes of vegetation and response to climate change. In this study, a 1 km spatial resolution and 8-day period length dataset (FPAR(ANN)) was developed covering the years 1980 to 2018 and evaluated on spatiotemporal change consistency by validating with Gross Primary Production (GPP) observations from the Chinese Flux Observation and Research Network (ChinaFLUX), and comparison with other FPAR products. FPAR(ANN) provided a comparable performance in capturing seasonal change observed through GPP, according to the coefficient of determination (R-2): 0.50, 0.51, 0.70 and 0.74 averaged for all sites, forest sites, grassland sites and cropland flux sites, respectively. The new data had more spatial similarity to the MODIS FPAR product (FPAR(MCD15A2)) with a greater R-2 (0.77) and a lower RMSE (0.12) than other products. With a newly developed dataset, combined with FPAR(ANN) (1980-2003) and FPAR(MCD15A2) (2004-2018), an overall increasing trend in FPAR was found for over 81% of the vegetated area of China from 1980 to 2018. FPAR increased more rapidly for over 83.7% of the area in the 2010s, and at a slower pace for over 62.1% of the area in the early 2000s, which was attributed to a decadal shifting of climate change. This study implies the new dataset is useful in quantifying vegetation changes and would be an important data source for future study of the carbon cycle, soil erosion, or evapotranspiration, with great application potential. |
| WOS关键词 | ARTIFICIAL NEURAL-NETWORKS ; NET PRIMARY PRODUCTION ; LEAF-AREA INDEX ; SOLAR-RADIATION ; SATELLITE DATA ; MODEL-DRIVEN ; TIME-SERIES ; LANDSAT ; CARBON ; FAPAR |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001046307700001 |
| 出版者 | MDPI |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/194526]  |
| 专题 | 生态系统网络观测与模拟院重点实验室_外文论文 |
| 作者单位 | 1.Chinese Academy of Forestry 2.Chinese Academy of Sciences 3.United States Forest Service 4.United States Department of Agriculture (USDA) 5.Institute of Desertification Studies, CAF 6.Institute of Geographic Sciences & Natural Resources Research, CAS |
| 推荐引用方式 GB/T 7714 | Zhang, Yuxin,Wang, Junbang,Watson, Alan E. E.. Rapid Vegetation Growth due to Shifts in Climate from Slow to Sustained Warming over Terrestrial Ecosystems in China from 1980 to 2018[J]. REMOTE SENSING,2023,15(15):3707. |
| APA | Zhang, Yuxin,Wang, Junbang,&Watson, Alan E. E..(2023).Rapid Vegetation Growth due to Shifts in Climate from Slow to Sustained Warming over Terrestrial Ecosystems in China from 1980 to 2018.REMOTE SENSING,15(15),3707. |
| MLA | Zhang, Yuxin,et al."Rapid Vegetation Growth due to Shifts in Climate from Slow to Sustained Warming over Terrestrial Ecosystems in China from 1980 to 2018".REMOTE SENSING 15.15(2023):3707. |
入库方式： OAI收割
来源：地理科学与资源研究所
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