# Exploring the Spatiotemporal Alterations in China's GPP Based on the DTEC Model
## 2 Materials and Methods
### Data Sources  
The flux observation data used in this paper were obtained from the China Terrestrial Ecosystem Flux Observation Research Network ([[http://chinaflux.org](http://chinaflux.org)]([http://chinaflux.org](http://chinaflux.org)), accessed on 11 April 2022) and the FLUXENT2015 dataset ([[https://fluxnet.org](https://fluxnet.org)]([https://fluxnet.org](https://fluxnet.org)), accessed on 20 April 2022). This study selected 10 flux towers in China, and detailed information about each site is shown in Table 1. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Flux Sites** & **Latitude/\({}^{\circ}\)N** & **Longitude/\({}^{\circ}\)E** & **Vegetation Type** & **Period/Year** \\ \hline Changbaishan & 42.40 & 128.10 & Deciduous Broadleaf Forests & 2004–2010 \\ (CBS) & 23.17 & 112.53 & Evergreen Broadleaf Forests & 2004–2010 \\ Dinghushan & 30.50 & 91.07 & Grassland & 2004–2010 \\ (DX) & 37.62 & 101.32 & Shrubland & 2004–2010 \\ Inner Mongolia & 43.55 & 116.67 & Grassland & 2004–2010 \\ Qianyanzhou (QYZ) & 26.74 & 115.06 & Evergreen Broadleaf Forests & 2004–2010 \\ Yucheng (YC) & 36.83 & 116.57 & Cropland & 2004–2010 \\ Changling & 44.59 & 123.51 & Grassland & 2007–2010 \\ Ailaoshan (ALS) & 24.54 & 101.29 & Mixed Forest & 2009–2012 \\ Yuanjiang (YJ) & 23.47 & 102.18 & Savannas & 2014–2015 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Flux site details for 10 flux towers in China. Figure 1: Elevation, flux tower location distribution and ecological regions in the study area. The two types of GPP product data used in this paper were MODIS17A2H.006 (MOD17) and the global dataset of sun-induced chlorophyll fluorescence (GO-SIF). The GO-SIF data were obtained from the high spatial and temporal resolution (0.05\({}^{\circ}\), 8 days) dataset provided by the Global Ecology Team ([[https://globalecology.unh.edu](https://globalecology.unh.edu)]([https://globalecology.unh.edu](https://globalecology.unh.edu)), accessed on 15 April 2022). The MOD17 data were obtained from the MOD17A2H.006 product on the Google Earth Engine (GEE) platform, which provides spatial and temporal resolution (500 m, 8 days). The performance of the DTEC model was evaluated in this paper with these two products and flux data. The C4 vegetation distribution percentage data were obtained from the International-Satellite-Land-Surface-Climatology-Project-II ([[https://doi.org/10.3334/ORNLDAAC/932](https://doi.org/10.3334/ORNLDAAC/932)]([https://doi.org/10.3334/ORNLDAAC/932](https://doi.org/10.3334/ORNLDAAC/932)), accessed on 15 April 2022), which provides a 1\({}^{\circ}\) spatial resolution static map of the globe. The aerosol optical depth (AOD) data were obtained from [[https://doi.org/10.5281/zenodo.5652257](https://doi.org/10.5281/zenodo.5652257)]([https://doi.org/10.5281/zenodo.5652257](https://doi.org/10.5281/zenodo.5652257)) (accessed on 15 April 2022), which was produced by the [PERSON] team and had a spatial and temporal resolution of 1000 m/day. The following data were obtained from the GEE platform. Meteorological driving data such as temperature, precipitation, and solar radiation were obtained from the ERA5-Land Monthly Averaged-ECMWF Climate Reanalysis data, with a spatiotemporal resolution of 11,132 m/1 month. The digital elevation model (DEM) data were taken from the NASANASADEM_HGT.001 data product with a spatial resolution of 30 m. Evaporation and potential evapotranspiration data were obtained from the MOD16A2.006 product, solar zenith angle data were obtained from the MOD09A1.061 product, the leaf area index (LAI) was obtained from the MOD15A2H.061 product, and the temporal and spatial resolutions were both 500 m, 8 days.