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DOI | 10.3390/su12052099 |
Estimating Ecosystem Respiration in the Grasslands of Northern China Using Machine Learning: Model Evaluation and Comparison | |
Zhu, Xiaobo; He, Honglin; Ma, Mingguo; Ren, Xiaoli; Zhang, Li; Zhang, Fawei; Li, Yingnian; Shi, Peili; Chen, Shiping; Wang, Yanfen; Xin, Xiaoping; Ma, Yaoming; Zhang, Yu; Du, Mingyuan; Ge, Rong; Zeng, Na; Li, Pan; Niu, Zhongen; Zhang, Liyun; Lv, Yan; Song, Zengjing; Gu, Qing | |
通讯作者 | Ma, MG (通讯作者) |
发表日期 | 2020 |
EISSN | 2071-1050 |
卷号 | 12期号:5 |
英文摘要 | While a number of machine learning (ML) models have been used to estimate RE, systematic evaluation and comparison of these models are still limited. In this study, we developed three traditional ML models and a deep learning (DL) model, stacked autoencoders (SAE), to estimate RE in northern China's grasslands. The four models were trained with two strategies: training for all of northern China's grasslands and separate training for the alpine and temperate grasslands. Our results showed that all four ML models estimated RE in northern China's grasslands fairly well, while the SAE model performed best (R-2 = 0.858, RMSE = 0.472 gC m(-2) d(-1), MAE = 0.304 gC m(-2) d(-1)). Models trained with the two strategies had almost identical performances. The enhanced vegetation index and soil organic carbon density (SOCD) were the two most important environmental variables for estimating RE in the grasslands of northern China. Air temperature (Ta) was more important than the growing season land surface water index (LSWI) in the alpine grasslands, while the LSWI was more important than Ta in the temperate grasslands. These findings may promote the application of DL models and the inclusion of SOCD for RE estimates with increased accuracy. |
英文关键词 | ecosystem respiration; machine learning; deep learning; grasslands; northern China |
语种 | 英语 |
WOS研究方向 | Science & Technology - Other Topics ; Environmental Sciences & Ecology |
WOS类目 | Green & Sustainable Science & Technology ; Environmental Sciences ; Environmental Studies |
WOS记录号 | WOS:000522470900400 |
来源期刊 | SUSTAINABILITY |
来源机构 | 中国科学院青藏高原研究所 |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/260072 |
推荐引用方式 GB/T 7714 | Zhu, Xiaobo,He, Honglin,Ma, Mingguo,et al. Estimating Ecosystem Respiration in the Grasslands of Northern China Using Machine Learning: Model Evaluation and Comparison[J]. 中国科学院青藏高原研究所,2020,12(5). |
APA | Zhu, Xiaobo.,He, Honglin.,Ma, Mingguo.,Ren, Xiaoli.,Zhang, Li.,...&Gu, Qing.(2020).Estimating Ecosystem Respiration in the Grasslands of Northern China Using Machine Learning: Model Evaluation and Comparison.SUSTAINABILITY,12(5). |
MLA | Zhu, Xiaobo,et al."Estimating Ecosystem Respiration in the Grasslands of Northern China Using Machine Learning: Model Evaluation and Comparison".SUSTAINABILITY 12.5(2020). |
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