## 2 Materials and Methods
### Research Methods
#### 2.3.7. Correlation Analysis between the Ecological Environment Quality and POI  
In order to analyze the correlation between human activities and ecological environment quality in the study area, the POI points in Meizhou City in 2018 were used as data sources (collected and provided by the Meizhou branch of Guangzhou Jiantong Surveying and Mapping Geographic Information Technology Co., Ltd., Guangzhou, China). This  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**RSEI Grade**} & \multicolumn{2}{c}{**2008**} & \multicolumn{2}{c}{**2013**} & \multicolumn{2}{c}{**2018**} \\ \cline{2-7}  & **Area** & \(\text{/km}^{2}\) & **Percentage/\%** & \(\text{Area}\) & \(\text{/km}^{2}\) & **Percentage/\%** & \(\text{Area}\) & **Percentage/\%** \\ \hline Excellent (0.8–1) & 2457 & 15.7 & 4371 & 27.9 & 2814 & 18.0 \\ Good (0.6–0.8) & 7201 & 46.0 & 5740 & 36.7 & 7545 & 48.2 \\ Medium (0.4–0.6) & 5459 & 34.9 & 4788 & 30.6 & 4650 & 29.7 \\ Inferior (0.2–0.4) & 125 & 0.8 & 250 & 1.6 & 147 & 0.9 \\ Poor (0–0.2) & 418 & 2.7 & 511 & 3.3 & 504 & 3.2 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Leveled RSEI statistics of Meizhou City.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Category**} & \multirow{2}{*}{**Grade**} & \multicolumn{2}{c}{**2008–2013**} & \multicolumn{2}{c}{**2013–2018**} & \multicolumn{2}{c}{**2008–2018**} \\ \cline{3-8}  & & **Area/km\({}^{2}\)** & **Percentage/\%** & **Area/km\({}^{2}\)** & **Percentage/\%** & **Area/km\({}^{2}\)** & **Percentage/\%** \\ \hline \multirow{4}{*}{Worse} & Significantly & 1 & 0.01 & 293 & 1.87 & 238 & 1.52 \\  & Obviously & 28 & 0.18 & 866 & 5.54 & 168 & 1.07 \\ \cline{1-1}  & Moderately & 424 & 2.71 & 2703 & 17.28 & 682 & 4.36 \\ \cline{1-1}  & Slightly & 3454 & 22.08 & 6442 & 41.19 & 2018 & 12.90 \\ \cline{1-1} Unchanged & Nominally & 7798 & 49.86 & 3838 & 24.54 & 8416 & 53.81 \\ \cline{1-1}  & Slightly & 3486 & 22.29 & 890 & 5.69 & 2965 & 18.96 \\ \cline{1-1}  & Moderately & 437 & 2.79 & 197 & 1.26 & 630 & 4.03 \\ \cline{1-1}  & Obviously & 12 & 0.08 & 222 & 1.42 & 343 & 2.19 \\ \cline{1-1}  & Significantly & 0 & 0.00 & 293 & 1.87 & 180 & 1.15 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Changes in the ecological environment quality level of Meizhou City.  
type of data divides the geographical entities into 17 categories, including natural villages, catering, high-speed service areas, gas stations, traffic trips, tourist attractions, commercial service land, etc., totaling about 116,000 POI points. The data processing and analysis work is carried out in three steps.  
First, the authors use ArcGIS software to perform point density analysis, generate a POI point density raster map, and use resampling tools to set the resolution to 1000 m. Next, we normalize the POI point density raster map and GPP, LST, WET, NDSI, and RSEI raster data of 2018. Then, using the fishnet tool of ArcGIS software to extract multi-value to points, we generate the relevant attribute point files containing the above 6 raster maps; by exporting the attribute table method in txt format, the data for subsequent correlation analysis is obtained. Finally, using IBM SPSS Statistics 25 software, the correlation (Spearman) analysis was performed on the data obtained in the previous step.