Assimilation of MODIS-derived LAI by radiative transfer modelling to crop growth simulation model for rice crop monitoring and yield estimation in the Mekong delta, Vietnam

Abstract:

Successful monitoring of rice crops and estimation of its yields in Mekong delta provide vital information to government agencies, rice production stakeholders and insurance companies in making their decisions and plans to establish solutions to protect rice smallholders from the risks involved. Remote sensing-based information promises a cost-effective way to observe rice crop growth in the largest rice producing region of Vietnam. For an extensive rice cultivation region as the Mekong delta, the use of divergence statistic to extract information from long-term or hypertemporal optical remote sensing NDVI profile to map rice cropping patterns has shown a high degree of success. The result map provides accurate information on where rice grew, when it was seeded and harvested, how many time it was cultivated every year. In addition, by using 8-day MODIS TERRA surface reflectance in Soil-Leaf-Canopy (SLC) radiative transfer model, 70 percent variation of seasonal rice LAI values was able to capture, making it useful to be assimilated into a rice crop growth simulation model (ORYZA 2000) to estimate the regional rice production in the season of 2008-2009. Tested results from 56 rice fields located in different rice cropping patterns showed that yields estimated using ORYZA2000 can explain 83 percent variation of field measured yields. However, simulated yields by ORYZA 2000 were used to overestimate by the model since some of model parameters could not be recalibrated due to the lack of field experiment data. This suggest that in the future, in order to gain a better results of rice crop monitoring and yield estimation, apart from improving the estimation of MODIS –derived LAIs by using SLC, calibrating crop growth simulation’s parameter have to be taken into account.