基于GLOPEM-CEVSA的烟叶产量遥感监测模型研究

Study on Remote Sensing Monitoring Model of Tobacco Yield Based on GLOPEM-CEVSA

为解决传统烟叶产量遥感监测模式依据因素单一,未考虑不同品种根、茎、叶各部位干物质比例等难题,提升监测精度,本文基于烟草碳循环过程及生理生态学特征,建立GLOPEM-CEVSA烟叶产量遥感监测模型,将生态系统过程模型CEVSA和生产效率模型GLO-PEM耦合,实现烟草碳周转、碳固定、碳分配等碳循环过程模拟,实现GPP、NPP与烟叶产量估算。结果表明,成熟期烟草NPP在99%置信级别与烟叶鲜质量显著相关(r=0.94),遥感监测模型估算的产量与样方实测结果具有较高的符合度(Ⅰ类烟误差为9.644%,Ⅱ类烟误差为4.316%,Ⅲ类烟误差为8.495%),表明该估产模型可以较好地完成烟叶产量估算,研究有助于烟叶制定种植计划,强化收购管理、宏观调控与决策。

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.