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Abstract
Since the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) instrument on the Environmental Satellite (ENVISAT) was launched in 2002, CH4 measurements from the satellite at regional or global scales became available. However, many gaps of missing data exist on the maps of the retrieved atmospheric CH4 column concentrations from SCIAMACHY/ENVISAT. Moreover, the gridded CH4 map with 50 × 50 km is a bit coarse for local interpretation. In this study, two geostatistical methods of ordinary kriging (OK) and ordinary cokriging (OCK) associated with 5 km normalized difference vegetation index (NDVI) images were examined to fill in missing data and to downscale the spatial resolution of CH4 images. The 50 km CH4 images interpolated by the two methods presented similar spatial patterns to the original 50 km CH4 image and provided good results for the missing data. Taking into account the statistical results, the OCK method achieved better performance than OK in filling gaps of missing data. In further downscaling the CH4 image from 50 to 5 km, the OCK method achieved a significant amount of spatial detail, and the statistical results also showed that OCK performed better than OK.
Acknowledgements
Funding support was partially from the Specialized Research Fund for the Doctoral Programme of Higher Education of China (20100091120017), the State Key Fundamental Science Funds of China (2010CB950702 and 2010CB428503), Fundamental Research Funds for the Central Universities, the Priority Academic Programme Development of Jiangsu Higher Education Institutions, the Public Benefit Research Foundation from the National Land and Resource Administration Bureau (No. 200811033) and the Open Fund of the State Key Laboratory of Remote Sensing (OFSLRSS201013). The authors also acknowledge the website (http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS) for providing the atmospheric methane column VMR data.