Knowledge Management System of Northwest Institute of Plateau Biology, CAS
| A MODIS-based Photosynthetic Capacity Model to estimate gross primary production in Northern China and the Tibetan Plateau | |
| Gao, Yanni1,2; Yu, Guirui1; Yan, Huimin1; Zhu, Xianjin1,2; Li, Shenggong1; Wang, Qiufeng1; Zhang, Junhui3; Wang, Yanfen2; Li, Yingnian4; Zhao, Liang4; Shi, Peili1 | |
| 2014-05-25 | |
| 发表期刊 | REMOTE SENSING OF ENVIRONMENT
 |
| ISSN | 0034-4257 |
| 卷号 | 148页码:108-118 |
| 文章类型 | Article |
| 摘要 | Accurate quantification of the spatio-temporal variation of gross primary production (GPP) for terrestrial ecosystems is significant for ecosystem management and the study of the global carbon cycle. In this study, we propose a MODIS-based Photosynthetic Capacity Model (PCM) to estimate GPP in Northern China and the Tibetan Plateau. The PCM follows the logic of the light use efficiency model and is only driven by the Enhanced Vegetation Index (EVI) and the Land Surface Water Index (LSWI). Multi-year eddy CO2 flux data from five vegetation types in North China (temperate mixed forest, temperate steppe) and the Tibetan Plateau (alpine shrubland, alpine marsh and alpine meadow-steppe) were used for model parameterization and validation. In most cases, the seasonal and interannual variation in the simulated GPP agreed well with the observed GPP. Model comparisons showed that the predictive accuracy of the PCM was higher than that of the MODIS GPP products and was comparable with that of the Vegetation Photosynthesis Model (VPM) and the potential PAR-based GPP models. The model parameter (PCmax) of the PCM represents the maximum photosynthetic capacity, which showed a good linear relationship with the mean annual nighttime Land Surface Temperature (LSTan). With this linear function, the PCM-simulated GPP can explain approximately 93% of the variation in the flux-observed GPP across all five vegetation types. These analyses demonstrated the potential of the PCM as an alternative tool for regional GPP estimation. (C) 2014 Elsevier Inc. All rights reserved.; Accurate quantification of the spatio-temporal variation of gross primary production (GPP) for terrestrial ecosystems is significant for ecosystem management and the study of the global carbon cycle. In this study, we propose a MODIS-based Photosynthetic Capacity Model (PCM) to estimate GPP in Northern China and the Tibetan Plateau. The PCM follows the logic of the light use efficiency model and is only driven by the Enhanced Vegetation Index (EVI) and the Land Surface Water Index (LSWI). Multi-year eddy CO2 flux data from five vegetation types in North China (temperate mixed forest, temperate steppe) and the Tibetan Plateau (alpine shrubland, alpine marsh and alpine meadow-steppe) were used for model parameterization and validation. In most cases, the seasonal and interannual variation in the simulated GPP agreed well with the observed GPP. Model comparisons showed that the predictive accuracy of the PCM was higher than that of the MODIS GPP products and was comparable with that of the Vegetation Photosynthesis Model (VPM) and the potential PAR-based GPP models. The model parameter (PCmax) of the PCM represents the maximum photosynthetic capacity, which showed a good linear relationship with the mean annual nighttime Land Surface Temperature (LSTan). With this linear function, the PCM-simulated GPP can explain approximately 93% of the variation in the flux-observed GPP across all five vegetation types. These analyses demonstrated the potential of the PCM as an alternative tool for regional GPP estimation. (C) 2014 Elsevier Inc. All rights reserved. |
| 关键词 | Gross Primary Production (Gpp) Eddy Covariance Vegetation Index Moisture Index Photosynthetic Capacity Photosynthetic Capacity Model (Pcm) |
| WOS标题词 | Science & Technology ; Life Sciences & Biomedicine ; Technology |
| 关键词[WOS] | LIGHT-USE EFFICIENCY ; SPECTRAL VEGETATION INDEXES ; DECIDUOUS BROADLEAF FOREST ; NET ECOSYSTEM EXCHANGE ; EDDY COVARIANCE ; CLIMATE DATA ; TERRESTRIAL ECOSYSTEMS ; REMOTE ESTIMATION ; SURFACE-TEMPERATURE ; CHLOROPHYLL CONTENT |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS研究方向 | Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS类目 | Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS记录号 | WOS:000336773600009 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://210.75.249.4/handle/363003/4229 |
| 专题 | 中国科学院西北高原生物研究所 |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Synth Res Ctr Chinese Ecosyst Res Network, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Appl Ecol, Shenyang 110016, Peoples R China 4.Chinese Acad Sci, Northwest Inst Plateau Biol, Xining 810001, Peoples R China |
| 推荐引用方式 GB/T 7714 | Gao, Yanni,Yu, Guirui,Yan, Huimin,et al. A MODIS-based Photosynthetic Capacity Model to estimate gross primary production in Northern China and the Tibetan Plateau[J]. REMOTE SENSING OF ENVIRONMENT,2014,148:108-118. |
| APA | Gao, Yanni.,Yu, Guirui.,Yan, Huimin.,Zhu, Xianjin.,Li, Shenggong.,...&Shi, Peili.(2014).A MODIS-based Photosynthetic Capacity Model to estimate gross primary production in Northern China and the Tibetan Plateau.REMOTE SENSING OF ENVIRONMENT,148,108-118. |
| MLA | Gao, Yanni,et al."A MODIS-based Photosynthetic Capacity Model to estimate gross primary production in Northern China and the Tibetan Plateau".REMOTE SENSING OF ENVIRONMENT 148(2014):108-118. |
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| A MODIS-based Photos（1827KB） | 开放获取 | CC BY-NC-SA | 浏览 下载 | |||
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