## 2 Materials and Methods
### Data Resources
#### 2.2.2 Remote Sensing Data
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Data Sources** & **Factors** &
\begin{tabular}{c} **Temporal** \\ **Resolution** \\ \end{tabular} & **Spatial Resolution** & **Unit** & **Classification** \\ \hline \multirow{8}{*}{AgERA5} & T & Daily & 0.1\({}^{\circ}\) & K \\  & RH & Real-time & 0.1\({}^{\circ}\) & / \\  & W & Daily & 0.1\({}^{\circ}\) & m s\({}^{-1}\) \\  & RS & Daily & 0.1\({}^{\circ}\) & J m\({}^{-2}\) d\({}^{-1}\) \\  & VP & Daily & 0.1\({}^{\circ}\) & hPa \\  & CC & Daily & 0.1\({}^{\circ}\) & / \\  & DEWT & Daily & 0.1\({}^{\circ}\) & K \\ \hline \multirow{8}{*}{MODIS} & MYD16A2 & ET & Eight-day & 500 m & kg m\({}^{-2}\) d\({}^{-1}\) \\ \cline{2-6}  & MCD15A2H & FPAR & Eight-day & 500 m & / \\ \cline{1-1} \cline{2-6}  & MCD15A2H & LAI & Eight-day & 500 m & / \\ \cline{1-1} \cline{2-6}  & MYD17A2H & GPP & Eight-day & 500 m & kg C m\({}^{-2}\) \\ \hline \multirow{2}{*}{GOSIF} & GOSIF & SIF & Eight-day & 0.05\({}^{\circ}\) & W m\({}^{-2}\) um\({}^{-1}\) sr\({}^{-1}\) \\ \hline \multirow{4}{*}{SRTM} & DEM & / & 90 m & m \\  & Slope & / & 90 m & \({}^{\circ}\) \\  & Aspect & / & 90 m & \({}^{\circ}\) \\ \hline \multirow{2}{*}{NPP/VIIRS} & Lit & Monthly & 1000 m & / & Intensity of human activity \\ \hline \multirow{8}{*}{China Environmental Monitoring Station} & AQI & Hourly & / & / \\  & PM\({}_{2.5}\) & Hourly & / & \(\mu\)g m\({}^{-3}\) \\ \cline{1-1}  & PM\({}_{10}\) & Hourly & / & \(\mu\)g m\({}^{-3}\) \\ \cline{1-1} \cline{2-6}  & SO\({}_{2}\) & Hourly & / & \(\mu\)g m\({}^{-3}\) \\ \cline{1-1} \cline{2-6}  & NO\({}_{2}\) & Hourly & / & \(\mu\)g m\({}^{-3}\) \\ \cline{1-1} \cline{2-6}  & CO & Hourly & / & mg m\({}^{-3}\) \\ \cline{1-1} \cline{2-6}  & O\({}_{3}\) & Hourly & / & \(\mu\)g m\({}^{-3}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Data overview of the driving factors on NAI dynamics. Topographic parameters include the digital elevation model (DEM), slope, and aspect. These data were collected from the SRTM datasets, which were produced by the cooperation between NASA, the Department of Defense's National Mapping Agency (NIMA), and space agencies in Germany and Italy. The DEM datasets were downloaded from the Geospatial Data Cloud Platform of the Computer Network Information Center of the Chinese Academy of Sciences ([[http://www.gscloud.cn](http://www.gscloud.cn)]([http://www.gscloud.cn](http://www.gscloud.cn)), accessed on 4 January 2021). Human activity intensity is represented by nighttime light radiation intensity (Lit). The Lit data were collected from the NPP/VIIRS datasets. NPP/VIIRS is the nighttime light data obtained by the visible light infrared imaging radiometer carried by the US National Polar Orbiting Cooperation Satellite. Since nighttime lights do not change much in a short period of time, this study uses monthly nighttime light data from 2020 with a spatial resolution of 1000 m, which are downloaded from the official website of the Earth Observation Group (EOG) ([[https://payneinstitute.mines.edu/eog/](https://payneinstitute.mines.edu/eog/)]([https://payneinstitute.mines.edu/eog/](https://payneinstitute.mines.edu/eog/)), accessed on 4 January 2021). Negative values were removed to improve the data quantity. In this paper, the mask-denoising method was used to preprocess the raw data. Firstly, negative values in the original data were replaced with 0 values. Secondly, the stable light data of DMSP in 2013, which was the closest to the date of the NPP/VIIRS data, was selected to form a mask (pixels with DN values greater than 0 in the DMSP image were assigned a value of 1). Finally, the mask data were multiplied by NPP /VIIRS data to achieve the purpose of denoising. Air quality includes air quality index (AQI) and pollutant (PM\({}_{2.5}\), PM\({}_{10}\), SO\({}_{2}\), NO\({}_{2}\), CO, O\({}_{3}\)) concentrations. These data were collected from China Environmental Monitoring Station.