Abstract:
In order to solve the problems of the traditional tobacco yield remote sensing monitoring model, which ignores the proportion of dry matter in different parts of roots, stems and leaves of different varieties. It is difficult to improve the monitoring accuracy. In this study we established a GLOPEM-CEVSA tobacco yield remote sensing monitoring model based on the carbon cycle process and physiological and ecological characteristics of tobacco. By coupling the ecosystem process model CEVSA and the production efficiency model GLO-PEM, carbon cycle processes such as tobacco carbon turnover, carbon fixation and carbon distribution were stimulated, and GPP, NPP and tobacco yield were estemated. The results showed that NPP of tobacco was significant correlated with fresh weight of tobacco leaves in maturation period at the 99% confidence level (correlation was 0.94), and tobacco yield estimated by the monitoring model was in good agreement with the measured data (the error is 9.644% for class I tobacco, 4.316% for class II tobacco and 8.495% for class III tobacco). The results indicated that the tobacco yield remote sensing monitoring model based on GLOPEM-CEVSA can be used for tobacco yield estimation. The results from this study can be helpful in making tobacco planting plan, strengthening purchase management, macro-control and decision-making.
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