Keywords: global warming, data assimilation, remote sensing, crop yield, photosynthesis, grain production monitoring, meteorological data, Asia, satellite data, CO2 emissions, carbon dioxide, grain yields, solar radiation, air temperature, photosynthetic sterility, modelling, climate change, crisis management, emergency management, food security, decision tree
Data assimilation for crop yield and CO2 fixation monitoring in Asia by a photosynthetic sterility model using satellites and meteorological data
This study assimilates satellite and meteorological data to monitor grain yields and CO2 fixation by developing a photosynthetic-sterility model that integrates the Asian scale of meteorological data such as solar radiation, air temperature effects on photosynthesis and the Normalised Difference Vegetation Index (NDVI) with a Satellite Pour l'Observation de la Terre (SPOT) VEGETATION sensor. Monitoring crop production using remotely sensed and daily meteorological data can provide an important early warning regarding poor crop production to Asian countries with their still-growing populations. Grain production monitoring would support orderly crisis management to maintain food security in Asia, which is facing climate fluctuations through this century of global warming. A decision-tree method classifies the distribution of crop fields in Asia using Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and SPOT VEGETATION data, which include the NDVI and Land Surface Water Index (LSWI). The air temperature data are available from the National Centres for Environmental Prediction (NCEP) and European Centre for Medium-Range Weather Forecasts (ECMWF). The solar radiation data are supplied by the Geostationary Meteorological Satellite (GMS) Centre and re-analysis data, by the NCEP and ECMWF. This study provides daily distributions of the photosynthesis rate, which is the CO2 fixation in Asian areas combined with the distribution of grain fields.