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| TG和VI生产力模型在中亚热带典型森林多时间尺度的 适用性评价 |
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贾玉伟1,2,3, 顾大形2,3*, 秦佳双2,3, 倪隆康2,3, 任世奇4,5
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(1. 广西师范大学 生命科学学院,广西 桂林 541006；2. 广西喀斯特植物保育与恢复生态学重点实验室,广西壮族自治区中国科学院广西植物研究所,广西 桂林 541006；3. 广西桂林城市生态系统国家定位观测研究站,广西 桂林541006；4. 广西壮族自治区林业科学研究院,南宁530002；5. 南宁桉树森林生态系统广西野外科学观测研究站,南宁530002）
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| 摘要: |
| 估算植被总初级生产力（GPP）对探索陆地生态系统中碳的流动和存储至关重要，并有助于解释全球气候变化的影响因素。遥感GPP模型是区域和全球尺度上模拟GPP的重要工具。为摸清TG和VI这两种遥感GPP模型在中亚热带地区两种典型森林的适用性以及不同模型参数标定方法的模拟效果，该研究基于地面气象数据和MODIS数据，从全年和季节两种尺度利用通量塔实测GPP对TG和VI模型的敏感参数进行标定，分别对中亚热带次生常绿阔叶林和桉树人工林的GPP进行模拟，并对比分析TG和VI模型在这两种生态系统的模拟精度。结果表明：（1）经过参数标定后，模型的模拟精度得到了提升，特别是在分季节标定的情况下，模拟精度明显优于全年标定的结果。（2）TG和VI模型的输入参数与两种生态系统实测GPP的相关性较高（R2 >0.70，P<0.001）。（3）TG模型的GPP模拟值与实测GPP的相关性高于VI模型，并且TG模型在次生常绿阔叶林生态系统的模拟误差最小（RE<2%）。综上认为，两种模型皆具备在中亚热带地区两种典型森林应用的潜力，且TG模型的模拟效果优于VI模型。 |
| 关键词: 总初级生产力，遥感，涡度相关法，地表温度，增强型植被指数 |
| DOI：10.11931/guihaia.gxzw202403013 |
| 分类号:S718.5 |
| Fund project:中科院西部之光项目（广西典型森林生态系统碳汇的速率、效率与遥感估算模型研究）；广西野外台站开放课题（NES-2023KF01）；广西科技计划项目（桂科AD20159086）；国家自然科学基金（41830648，32060243，32160362）。 |
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| Evaluation of the applicability of TG and VI productivity models at multiple time scales in typical forests in the central subtropics |
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JIA Yuwei1,2,3, Gu Daxing2,3*, Qin Jiashuang2,3, Ni Longkang2,3, Ren Shiqi4,5
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(1. College of Life Sciences, Guangxi Normal University, Guilin 541006, Guangxi, China; 2. Guangxi Institute of Botany, Guangxi Zhuang Autonomous Region and Chinese Academy of Sciences, Guangxi Key Laboratory of Plant Conservation and Restoration Ecology in Karst Terrain, Guilin 541006, Guangxi, China; 3. Guangxi Guilin Urban Ecosystem National Observation and Research Station, National Forestry and Grassland Administration, Guilin 541006, Guangxi, China; 4. Guangxi Zhuang Autonomous Region Forestry Research Institute, Nanning, 530002, China; 5. Nanning Eucalypt Plantation Ecosystem Observation and Research Station of Guangxi, Nanning 530002, China)
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| Abstract: |
| Estimating gross primary productivity (GPP) of vegetation is essential for exploring the flow and storage of carbon in terrestrial ecosystems and helps to explain the factors influencing global climate change. Remote sensing GPP models are important tools for simulating GPP at regional and global scales. In order to clarify the applicability of two remote sensing GPP models, TG and VI, to two typical forests in the meso-subtropical region as well as the simulation effects of different model parameter calibration methods, the present study was conducted to calibrate the sensitive parameters of the TG and VI models based on the ground-based meteorological data and MODIS data using flux-tower measured GPP at both year-round and seasonal scales, and then the GPPs of the meso-subtropical regenerated broad-leaved evergreen forest and the eucalyptus The GPP of meso-subtropical secondary evergreen broadleaf forest and eucalyptus plantation forest were simulated, and the simulation accuracies of the TG and VI models in these two ecosystems were compared and analyzed. The results were as follows: (1) The simulation accuracy of the models was improved after parameter calibration, especially in the case of seasonal calibration, the simulation accuracy was significantly better than that of the year-round calibration. (2) The correlation between the input parameters of the TG and VI models and the measured GPP of the two ecosystems was high (R2 >0.70，P<0.001). (3) The correlation between the simulated and measured GPPs of the TG model was higher than that of the VI model, and the simulation error of the TG model was the smallest in the secondary broadleaf evergreen forest ecosystem (RE< 2%). In conclusion, both models have the potential to be applied in two typical forests in the central subtropical region, and the simulation effect of the TG model is better than that of the VI model. |
| Key words: gross primary productivity, remote sensing, eddy covariance, land surface temperature, enhanced vegetation index |
