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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中图分类号：Q948 文献标识码：A 文章编号：1000-3142（2025）08-1415-11

Abstract：Estimating gross primary productivity（GPP）of vegetation is essntial for exploring the flowand storageof carboninterestrial ecosystems and helps to explain the factors influencing global climatechange.Remotesensing GPP modelsare importanttolsfor simulating GPPat regionaland global scales.Inorder to clarify the applicabilityof two remotesensing GPPmodels，TGandVI，totwo typical forests inthecentral subtropicsas wellas the simulationeffects of diferent model parameter calibration methods，the present study wasconductedtocalibrate 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 annual and seasonal scales，and then the GPPs of the regenerated evergreen broad-leaved forest and eucalyptus plantation inthecentral subtropics were simulated，and thesimulationaccuraciesoftheTGandVImodels inthese two ecosystems were compared and analyzed.The results were as folows：（1）The simulation accuracy of the models was improved after parameter calibration，especially in thecase of seasonal calibration，the simulation accuracy was significantlybetterthan thatoftheyear-roundcalibration.（2）Thecorrelationbetween the inputparametersof the TG and VI models and the measured GPP of the two ecosystems was high（ （R2>0.70，P<0.001） .（3）The correlation betweenthe simulatedand measured GPPsof the TG model was higherthan thatofthe VImodel，and the simulation error of the TG model was the smallest in the regenerated evergreen broad-leaved forest ecosystem （ ∣RE∣<2%）. In conclusion，both models have thepotential tobeappliedintwo typical forests inthecentral subtropics，andthe simulation effect of the TG model is better than that of the VI model.

Key words： gross primary productivity（GPP），remote sensing，eddy covariance method，land surface temperature， enhancedvegetationindex

陆地生态系统作为净碳汇在全球碳循环中发挥着重要作用，抵消了过去几十年人类活动所排放的 10%～60% 的 CO2 （Heimann & Reichstein，2008；Friedlingsteinetal.，2020）。（剩余17928字）