Remote Sensing Monitoring Model of Tobacco Growth and Yield Based on Ecological Process and Carbon Cycle

Abstract

Tobacco growth monitoring and yield estimation are very important for tobacco planting control and allocation. However, traditional tobacco yield estimation models have not considered the light energy utilization, carbon cycle, and ecological processes, resulting in the mechanisms poorly explained and the reduced monitoring accuracy. To address these limitations, a tobacco yield remote sensing monitoring model based on ecological process and carbon cycle was proposed. The model couples the Carbon Exchange between Vegetation, Soil, and Atmosphere (CEVSA) ecosystem process model and the global production efficiency model (GLO-PEM), to simulate effective solar radiation and tobacco light energy utilization, stress effects of surface air temperature, water vapour pressure deficit and photosynthetic effective radiation. Then the tobacco gross primary production (GPP), net primary productivity (NPP), tobacco biomass were estimated. Finally, the tobacco yield estimation model based on the correlation between tobacco yield and NPP was proposed. The results showed that there was a significant correlation (correlation= 0.94) between NPP and tobacco leaves weight at 99% confidence level, and the yield estimated by the remote sensing monitoring model was in good agreement with the measured results, with errors of Class I, II, III were 9.644%, 4.316%, and 8.495% respectively. In conclusion, the proposed model can be used to estimate tobacco yield, support decision-making of tobacco planting plan, and strengthen purchasing management.