## 2 Materials and Methods
### Research Methods
#### 2.2.2 Information Acquisition of the Walnut Planting Area  
Taking Sentinel-2 image as the data source, in this study, the NDVI sequential variation of different ground objects from April to September was calculated in GEE (as shown in Figure 3). Figure 3 shows that the NDVI value of walnuts in the research area is significantly higher than that of the other four types from April to the first and middle ten days of July. The months from April to July comprise the fruit development period and core-hardening period of walnuts, and the leaves of walnut trees are constantly turning green. In order to highlight the characteristics of walnuts, this study selects image data from April to the first \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Year** & **Data** & **Filter Cloud Amount** & **Number of Images** \\ \hline
2017–2018 & 1 April to 1 July & \textless{}20\% & 18 \\ \cline{2-4}  & 1 July to 15 September & \textless{}20\% & 13 \\
2018–2019 & 1 April to 1 July & \textless{}20\% & 18 \\ \cline{2-4}  & 1 July to 15 September & \textless{}20\% & 13 \\
2019–2020 & 1 April to 1 July & \textless{}10\% & 18 \\ \cline{2-4}  & 1 July to 15 September & \textless{}10\% & 13 \\
2020–2021 & 1 April to 1 July & \textless{}10\% & 18 \\ \cline{2-4}  & 1 July to 15 September & \textless{}10\% & 13 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Details of selected Sentinel-2 images. and middle ten days of September, calculates the NDVI value of each image, sorts each pixel of the image set according to the NDVI value from small to large in GEE, and extracts the synthesized image according to the maximum NDVI value (including original spectral information). The NDVI calculation formula is as follows [26]. \[NDVI=\frac{NIR-Red}{NIR+Red} \tag{1}\]  
where Red is the red waveband, and NIR is the near-infrared waveband. The water body area in the study area is mainly composed of reservoirs and rivers, etc. The edges are obvious with respect to texture, and with respect to color, the water body area is cyan and dark cyan. Other orchards in the study area are mainly located in the rural periphery of the plain zone, exhibiting clearer textures, more regular shapes (rectangular), and light green color in Google Earth. The study area is also planted with cotton, pepper, wheat, corn, and many other crops in addition to orchards. On Google Earth, it exhibits clearer textures, more regular shapes (rectangles), and bright green color. \begin{table}
\begin{tabular}{c c c} \hline
**Specimen Type** & **Interpretation Signs** & **Description** \\ \hline Impervious surface & & The impervious surfaces in the study area consist of town buildings, roads, and bare ground, which are identifiable on Google Earth by their texture information and occur in patches. \\ \hline Water & & The water body area in the study area is mainly composed of reservoirs and rivers, etc. The edges are obvious with respect to texture, and with respect to color, the water body area is cyan and dark cyan. \\ \hline Walnuts & & The walnuts in the study area are mainly distributed around the area. On Google Earth, the texture is clearer, occurs in patches, exhibits a more regular shape (rectangular), and is dark green in color. \\ \hline Other orchards & & Other orchards in the study area are mainly located in the rural periphery of the plain zone, exhibiting clearer textures, more regular shapes (rectangular), and light green color in Google Earth. \\ \hline Other crops & & The study area is also planted with cotton, pepper, wheat, corn, and many other crops in addition to orchards. On Google Earth, it exhibits clearer textures, more regular shapes (rectangles), and bright green color. \\ \hline \end{tabular}
\end{table} 
Table 3: Basis for sample selection. Ganquan Town is surrounded by the Gobi Desert, and the field is mainly comprised of sandy soil; thus, identifying the walnut planting area is difficult.