| Simulation of Forest Carbon Fluxes Using Model Incorporation and Data Assimilation | |
| Yan, Min1; Tian, Xin1; Li, Zengyuan1; Chen, Erxue1; Wang, Xufeng2; Han, Zongtao1,3; Sun, Hong1 | |
| 刊名 | REMOTE SENSING
 |
| 2016-07-01 | |
| 卷号 | 8期号:7页码:16 |
| 关键词 | carbon fluxes model incorporation data assimilation |
| ISSN号 | 2072-4292 |
| DOI | 10.3390/rs8070567 |
| 通讯作者 | Tian, Xin(tianxin@ifrit.ac.cn) |
| 英文摘要 | This study improved simulation of forest carbon fluxes in the Changbai Mountains with a process-based model (Biome-BGC) using incorporation and data assimilation. Firstly, the original remote sensing-based MODIS MOD_17 GPP (MOD_17) model was optimized using refined input data and biome-specific parameters. The key ecophysiological parameters of the Biome-BGC model were determined through the Extended Fourier Amplitude Sensitivity Test (EFAST) sensitivity analysis. Then the optimized MOD_17 model was used to calibrate the Biome-BGC model by adjusting the sensitive ecophysiological parameters. Once the best match was found for the 10 selected forest plots for the 8-day GPP estimates from the optimized MOD_17 and from the Biome-BGC, the values of sensitive ecophysiological parameters were determined. The calibrated Biome-BGC model agreed better with the eddy covariance (EC) measurements (R-2 = 0.87, RMSE = 1.583 gC.m(-2).d(-1)) than the original model did (R-2 = 0.72, RMSE = 2.419 gC.m(-2).d(-1)). To provide a best estimate of the true state of the model, the Ensemble Kalman Filter (EnKF) was used to assimilate five years (of eight-day periods between 2003 and 2007) of Global LAnd Surface Satellite (GLASS) LAI products into the calibrated Biome-BGC model. The results indicated that LAI simulated through the assimilated Biome-BGC agreed well with GLASS LAI. GPP performances obtained from the assimilated Biome-BGC were further improved and verified by EC measurements at the Changbai Mountains forest flux site (R-2 = 0.92, RMSE = 1.261 gC.m(-2).d(-1)). |
| 收录类别 | SCI |
| WOS关键词 | GROSS PRIMARY PRODUCTION ; ENSEMBLE KALMAN FILTER ; PINE MIXED FOREST ; BIOME-BGC ; SENSITIVITY-ANALYSIS ; PRIMARY PRODUCTIVITY ; CHANGBAI MOUNTAINS ; ECOSYSTEM MODEL ; MODIS-GPP ; EVAPOTRANSPIRATION |
| WOS研究方向 | Remote Sensing |
| WOS类目 | Remote Sensing |
| 语种 | 英语 |
| 出版者 | MDPI AG |
| WOS记录号 | WOS:000382224800037 |
| 内容类型 | 期刊论文 |
| URI标识 | http://www.corc.org.cn/handle/1471x/2557448 |
| 专题 | 寒区旱区环境与工程研究所 |
| 通讯作者 | Tian, Xin |
| 作者单位 | 1.Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China 2.Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, Lanzhou 730000, Peoples R China 3.Fuzhou Univ, Minist Educ, Key Lab Spatial Data Min & Informat Sharing, Fuzhou 350002, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yan, Min,Tian, Xin,Li, Zengyuan,et al. Simulation of Forest Carbon Fluxes Using Model Incorporation and Data Assimilation[J]. REMOTE SENSING,2016,8(7):16. |
| APA | Yan, Min.,Tian, Xin.,Li, Zengyuan.,Chen, Erxue.,Wang, Xufeng.,...&Sun, Hong.(2016).Simulation of Forest Carbon Fluxes Using Model Incorporation and Data Assimilation.REMOTE SENSING,8(7),16. |
| MLA | Yan, Min,et al."Simulation of Forest Carbon Fluxes Using Model Incorporation and Data Assimilation".REMOTE SENSING 8.7(2016):16. |
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