Prediction of continental-scale evapotranspiration by combining MODIS and AmeriFlux data through support vector machine
文献类型：SCI/SSCI论文
| 作者 | Yang F. H. ; White M. A. ; Michaelis A. R. ; Ichii K. ; Hashimoto H. ; Votava P. ; Zhu A. X. ; Nemani R. R. |
| 发表日期 | 2006 |
| 关键词 | AmeriFlux evapotranspiration (ET) Moderate Resolution Imaging Spectroradiometer (MODIS) support vector machines (SVMs) land-surface temperature vegetation indexes validation flux satellite parameters ecosystem pattern ndvi |
| 英文摘要 | Application of remote sensing data to extrapolate evapotranspiration (ET) measured at eddy covariance flux towers is a potentially powerful method to estimate continental-scale ET. In support of this concept, we used meteorological and flux data from the AmeriFlux network and an inductive machine learning technique called support vector machine (SVM) to develop a predictive ET model. The model was then applied to the conterminous U.S. In this process, we first trained the SVM to predict 2000-2002 ET measurements from 25 AmeriFlux sites using three remotely sensed variables [land surface temperature, enhanced vegetation index (EVI), and land cover] and one ground-measured variable (surface shortwave radiation). Second, we evaluated the model performance by predicting ET for 19 flux sites in 2003. In this independent evaluation, the SVM predicted ET with a root-mean-square error (rmse) of 0.62 mm/day (approximately 23% of the mean observed values) and an R-2 of 0.75. The rmse from SVM was significantly smaller than that from neural network and multiple-regression approaches in a cross-validation experiment. Among the explanatory variables, EVI was the most important factor. Indeed, removing this variable induced an rmse increase from 0.54 to 0.77 mm/day. Third, with forcings; from remote sensing data alone, we used the SVM model to predict the spatial and temporal distributions of ET for the conterminous U.S. for 2004. The SVM model captured the spatial and temporal variations of ET at a continental scale. |
| 出处 | Ieee Transactions on Geoscience and Remote Sensing |
| 卷 | 44 |
| 期 | 11 |
| 页 | 3452-3461 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 0196-2892 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/22608]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Yang F. H.,White M. A.,Michaelis A. R.,et al. Prediction of continental-scale evapotranspiration by combining MODIS and AmeriFlux data through support vector machine. 2006. |
入库方式： OAI收割
来源：地理科学与资源研究所
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