Global land 1° mapping XCO2 dataset using satellite observations of GOSAT and OCO-2 from 2009 to 2020https://doi.org/10.7910/DVN/4WDTD8Sheng,MengyaLei,LipingZeng,Zhao-ChengWeiqiang RaoHao SongWu,ChangjiangHarvard Dataverse2021-03-262021-08-17T14:11:46ZThe global 1° land mapping XCO2 dataset (Mapping-XCO2) is derived from satellite XCO2 retrievals of GOSAT and OCO-2 spanning the period of April 2009 to December 2020. The data product is provided in GeoTIFF format and include two temporal resolutions: 3 days and month. The 3-day data files include gridded XCO2 and mapping uncertainty, which are named like “MappingXCO2_Date.nc” and “MappingUncertainty_Date.nc”. The flag “Date” is defined as date ID of 1426 time-units started from 20 April 2009. The monthly data files only include XCO2 data and named like “MappingXCO2_YYYY_MM.tif”. The number of “YYYY” and “MM” represent year and month, respectively. The domain of the dataset covers global land ranging from 56° S to 65° N and 169° W to 180° E. The spatial reference of the dataset is Geographic Lat/Lon. The unit of XCO2 data is ppm while the nodata values were assigned to NaN.Earth and Environmental SciencesZeng, Z.C.; Lei, L.; Hou, S.; Ru, F.; Guan, X.; Zhang, B. A Regional Gap-Filling Method Based on Spatiotemporal Variogram Model of Columns. IEEE Trans. Geosci. Remote Sens. 2014, 52, 3594–3603., doi, 10.1109/TGRS.2013.2273807Guo, L.J.; Lei, L.P.; Zeng, Z.C.; Zou, P.F.; Liu, D.; Zhang, B. Evaluation of Spatio-Temporal Variogram Models for Mapping XCO2 Using Satellite Observations: A Case Study in China. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2015, 8, 376–385., doi, 10.1109/JSTARS.2014.2363019Zeng, Z.C.; Lei, L.; Strong, K.; Jones, D.B.A.; Guo, L.; Liu, M.; Deng, F.; Deutscher, N.M.; Dubey, M.K.; Griffith, D.W.T.; et al. Global land mapping of satellite-observed CO2 total columns using spatio-temporal geostatistics. Int. J. Digit. Earth 2017, 10, 426–456., doi, 10.1080/17538947.2016.1156777He, Z.; Lei, L.; Welp, L.R.; Zeng, Z.C.; Bie, N.; Yang, S.; Liu, L. Detection of Spatiotemporal Extreme Changes in Atmospheric CO2 Concentration Based on Satellite Observations. Remote Sens. 2018, 10, 839., doi, 10.3390/rs10060839He, Z.; Lei, L.; Zhang, Y.; Sheng, M.; Wu, C.; Li, L.; Zeng, Z.-C.; Welp, L.R. Spatio-Temporal Mapping of Multi-Satellite Observed Column Atmospheric CO2 Using Precision-Weighted Kriging Method. Remote Sens. 2020, 12, 576., doi, 10.3390/rs12030576He, Z.; Lei, L.; Zeng, Z.C.; Sheng, M.; Welp, L.R. Evidence of Carbon Uptake Associated with Vegetation Greening Trends in Eastern China. Remote Sens. 2020, 12, 718., doi, 10.3390/rs120407182021-01-25Sheng, Mengya2021-03-262009-042020-12CC0CC0 Waiver