Modelling soil moisture using climate data and normalized difference vegetation index based on nine algorithms in alpine grasslands
文献类型：期刊论文
| 作者 | Wang, Shaohua; Fu, Gang2 |
| 刊名 | FRONTIERS IN ENVIRONMENTAL SCIENCE
 |
| 出版日期 | 2023-02-10 |
| 卷号 | 11 |
| 关键词 | soil quality global change random forest alpine ecosystem alpine region 'third pole' Tibetan plateau NDVI |
| ISSN号 | 2296-665X |
| DOI | 10.3389/fenvs.2023.1130448 |
| 文献子类 | Article |
| 英文摘要 | Soil moisture (SM) is closely correlated with ecosystem structure and function. Examining whether climate data (temperature, precipitation and radiation) and the normalized difference vegetation index (NDVI) can be used to estimate SM variation could benefit research related to SM under climate change and human activities. In this study, we evaluated the ability of nine algorithms to explain potential SM (SMp) variation using climate data and actual SM (SMa) variation using climate data and NDVI. Overall, climate data and the NDVI based on the constructed random forest models led to the best estimated SM (R (2) >= 94%, RMSE <= 2.98, absolute value of relative bias: <= 3.45%). Randomness, and the setting values of the two key parameters (mtry and ntree), may explain why the random forest models obtained the highest accuracy in predicating SM. Therefore, the constructed random forest models of SMp and SMa in this study can be thus be applied to estimate spatiotemporal variations in SM and for other related scientific research (e.g., differentiating the relative effects of climate change and human activities on SM), at least for Tibetan grassland region. |
| WOS关键词 | TIBETAN PLATEAU ; GROWING-SEASON ; INCREASED PRECIPITATION ; PLANT-PRODUCTION ; MEADOW ; RESPIRATION ; VALIDATION ; RETRIEVAL ; PRODUCTS ; SIMULATIONS |
| WOS研究方向 | Environmental Sciences & Ecology |
| WOS记录号 | WOS:000938051100001 |
| 出版者 | FRONTIERS MEDIA SA |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/190305]  |
| 专题 | 拉萨站高原生态系统研究中心_外文论文 |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Lhasa Plateau Ecosyst Res Stn, Beijing, Peoples R China 2.Int Res Ctr Big Data Sustainable Dev Goals, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Shaohua,Fu, Gang. Modelling soil moisture using climate data and normalized difference vegetation index based on nine algorithms in alpine grasslands[J]. FRONTIERS IN ENVIRONMENTAL SCIENCE,2023,11. |
| APA | Wang, Shaohua,&Fu, Gang.(2023).Modelling soil moisture using climate data and normalized difference vegetation index based on nine algorithms in alpine grasslands.FRONTIERS IN ENVIRONMENTAL SCIENCE,11. |
| MLA | Wang, Shaohua,et al."Modelling soil moisture using climate data and normalized difference vegetation index based on nine algorithms in alpine grasslands".FRONTIERS IN ENVIRONMENTAL SCIENCE 11(2023). |
入库方式： OAI收割
来源：地理科学与资源研究所
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