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Mitsuhiro Tomosada,Koji Kanefuji,Yukio Matsumoto,Hiroe Tsubaki 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
We propose a method to generate a global distribution map of carbon dioxide (CO2) and methane (CH4)column abundance retrieved from spectra on irregular observation points by GOSAT (Greenhouse gases ObserbingSATellite). Global distribution map is gridded by 1 degree for latitude and longitude. Kriging in spatial statistics isapplied to the spatial data of CO2 and CH4 column abundance. We focus on CO2 density in this study, the distance anddifference of CO2 column abundances between observation points for sample pairs at each observation points overocean and over land on the earth’s surface are calculated. The relationship between the distance and the difference ofCO2 column abundances are represented by semi-variogram model. When semi-variogram is modeled, the difference ofsemi-variogram derived from the direction between observation points of sample pairs from North-pole direction isconsidered. And, we obtain the variogram model for each land cover. GOSAT was just launched, and CO2 columnabundance is not retrieved from spectra measured by GOSAT. Therefore, proposed method is applied to spatial data ofXCO2 instead of CO2 column abundance. We set the observation points on the earth’s surface based on the GOSATobservation plan. Global distribution map of XCO2 instead of CO2 column abundance is used, XCO2 value for eachobservation points are set. And we predict XCO2 values on the grid in global distribution map from the set observationpoints and XCO2. As a result, the standard deviation of prediction error (predicted value ? actual value) is 0.324. Thisstandard deviation, which is 0.1% of XCO2 value, is enough small comparison with target accuracy (1%).