## 5 Conclusions
Considering the strong terrestrial respiration, and its relationship with temperature over low-latitude zones, LST, an important remote sensing parameter, was used for correlation with the seasonal change of XCO\({}_{2}\). Fortunately, high positive coefficients are shown in low-latitude area for LST and seasonal change of XCO\({}_{2}\), which provide us a potential method of utilizing remote sensing parameters related to the photosynthesis and terrestrial respiration for better understanding the biosphere-atmosphere interaction for lack of surface measurements in the low-latitude areas. Future studies, including improving the mapping XCO\({}_{2}\) data over the tropical areas, comparing the mapping XCO\({}_{2}\) with results from other models, and a detailed investigation of the discrepancies between observations and modeling, should be further explored. It is expected that the data-driven assessment developed in this study will be improved as more CO\({}_{2}\) observations are becoming availablefrom newly-launched satellite, such as OCO-2, and upcoming satellites, such a as TanSat [80], as well as more remote sensing data on vegetation activities. The following are available online at www.mdpi.com/2072-4292/9/3/251/s1. Figure S1. The global map of the coefficient of determination (R\({}^{2}\)) between fitting-XCO\({}_{2}\) and GM-XCO\({}_{2}\) using Equation (1). R\({}^{2}\) in each grid represents the goodness-of-fit of the grid, such as one fitting shown in Figure 2. Figure S2: Temporal variation comparison for the 12 TCCON sites. As shown in these panels, the original ACOS-GOSAT XCO\({}_{2}\) retrievals within 500 km of the TCCON site are in gray dots. The TCCON data, smoothed by applying the ACOS-GOSAT averaging kernel, are indicated by blue dots. The data are chosen using coincidence criteria of within \(\pm 1\) h of the GOSAT overpass time, and a three-day (one time-unit) mean is calculated for the comparison. The predicted TCCON site XCO\({}_{2}\) time series using the mapping approach are indicated by the red dots. Figure S3: SCA difference between averaged GM-XCO\({}_{2}\) and CT-XCO\({}_{2}\) in the mapping area from June 2009 to May 2014, which is calculated using GM-XCO\({}_{2}\) shown in Figure 3 minus corresponding values of CT-XCO\({}_{2}\) shown in Figure 9. Negative values indicate GM-XCO\({}_{2}\) SCA is lower than that of CT-XCO\({}_{2}\), and positive values indicate that GM-XCO\({}_{2}\) is higher. Figure S4: Monthly mean of detrended XCO\({}_{2}\) (dXCO\({}_{2}\)) and bottom-up estimation of fossil fuel emissions (FFCO\({}_{2}\)) from ODIAC (Open-source Data Inventory for Anthropogenic CO\({}_{2}\)) and CDIAC (Carbon Dioxide information Analysis Center) over (a) cropland in Northern India (CnI) and (b) cropland in Northern China (CnC), two regions of interest as shown in Figure 1, from June 2009 to May 2014. This research was supported by the National Research Program on Global Changes and Adaptation: \"Big data on global changes: data sharing platform and recognition\" (Grant No. 2016 YFA0600303, Grant No. 2016 YFA0600304). We acknowledge The ACOS-GOSAT v3.5 data were produced by the ACOS/OCO-2 project at the Jet Propulsion Laboratory, California Institute of Technology, and obtained from the ACOS/OCO-2 data archive maintained at the NASA Goddard Earth Science Data and Information Services Center. We also acknowledge the GOSAT Project for acquiring the spectra. CarbonTracker CT2015 results are provided by NOAA ESRL, Boulder, Colorado, USA from the website at [[http://carbontracker.noaa.gov](http://carbontracker.noaa.gov)]([http://carbontracker.noaa.gov](http://carbontracker.noaa.gov)). Terra MODIS GPP/NPP Product MODI7A2 was downloaded from the University of Montana and Aqua or Terra MODIS NDVI/EVI, LAI products (MYD13C2, MOD11C3) were download from USGS websites ([http://e4 ff101.cr.usgs.gov](http://e4 ff101.cr.usgs.gov)). Land cover products were downloaded from ESA ([[http://www.esa-ghg-cgi.org](http://www.esa-ghg-cgi.org)]([http://www.esa-ghg-cgi.org](http://www.esa-ghg-cgi.org))).