Prediction of abovegroundgrassland biomass on the LoessPlateau, China, using a randomforest algorithm
文献类型：期刊论文
| 作者 | Shuangguan,Zhouping; Shuangguan,ZP(Shuangguan,Zhouping)3,4; Sun,WY(Sun,Wenyi)4; Tang,ZS(Tang,Zhuangsheng)2; Deng,L(Deng,Lin)4; Wu,GL(Wu,Gaolin)4; Wang,YY(Wang,Yinyin)3,4 |
| 刊名 | Scientific Reports
 |
| 出版日期 | 2017-07-31 |
| 卷号 | 7期号:1页码:6940 |
| DOI | 10.1038/s41598-017-07197-6 |
| 文献子类 | 期刊论文 |
| 英文摘要 | Grasslands are an important component of terrestrial ecosystems that play a crucial role in the carbon cycle and climate change. In this study, we collected aboveground biomass (AGB) data from 223 grassland quadrats distributed across the Loess Plateau from 2011 to 2013 and predicted the spatial distribution of the grassland AGB at a 100-m resolution from both meteorological station and remote sensing data (TM and MODIS) using a Random Forest (RF) algorithm. The results showed that the predicted grassland AGB on the Loess Plateau decreased from east to west. Vegetation indexes were positively correlated with grassland AGB, and the normalized difference vegetation index (NDVI) acquired from TM data was the most important predictive factor. Tussock and shrub tussock had the highest AGB, and desert steppe had the lowest. Rainfall higher than 400 m might have benefitted the grassland AGB. Compared with those obtained for the bagging, mboost and the support vector machine (SVM) models, higher values for the mean Pearson coefficient (R) and the symmetric index of agreement (λ) were obtained for the RF model, indicating that this RF model could reasonably estimate the grassland AGB (65.01%) on the Loess Plateau. |
| 项目编号 | 2016YFC0501605 ; 41390463 ; 2014FY210100 |
| 语种 | 英语 |
| 资助机构 | National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; National Sci-TechBasic Program of China ; National Sci-TechBasic Program of China |
| 源URL | [http://ir.ieecas.cn/handle/361006/5611]  |
| 专题 | 地球环境研究所_生态环境研究室 |
| 通讯作者 | Shuangguan,Zhouping |
| 作者单位 | 1.Institute of Earth Environment 2.State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, 712100, Yangling, Shaanxi, P.R. China 3.University of Chinese Academy of Sciences 4.Institute of Soil and Water Conservation |
| 推荐引用方式 GB/T 7714 | Shuangguan,Zhouping,Shuangguan,ZP,Sun,WY,et al. Prediction of abovegroundgrassland biomass on the LoessPlateau, China, using a randomforest algorithm[J]. Scientific Reports,2017,7(1):6940. |
| APA | Shuangguan,Zhouping.,Shuangguan,ZP.,Sun,WY.,Tang,ZS.,Deng,L.,...&Wang,YY.(2017).Prediction of abovegroundgrassland biomass on the LoessPlateau, China, using a randomforest algorithm.Scientific Reports,7(1),6940. |
| MLA | Shuangguan,Zhouping,et al."Prediction of abovegroundgrassland biomass on the LoessPlateau, China, using a randomforest algorithm".Scientific Reports 7.1(2017):6940. |
入库方式： OAI收割
来源：地球环境研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。