## 4 Experiment and Analysis
### 500 m Daily Soil Moisture Map Generation  
Due to the good predictive ability of the GA-BP model to retrieve soil moisture, we combined all 10 surface environmental elements in the 500 \(\times\) 500 squares in the experimental area into a map input set and input the qualified GA-BP neural network model trained above to obtain Continuous soil moisture products in 500 m of space per day. Figure 7. Comparison of the 15-day GA-BP inversion soil moisture map and the 5-day NASA-USDA soil moisture product from 15 February 2014 to1 March 2014. From Figure 7((a1)-(a4),(b1)-(b4),(c1)-(c4),(d1)-(d4),(e1)-(e4)) contrast can be seen. The soil moisture map retrieved by GA-BP is consistent with the spatial distribution of NASA-USDA soil moisture products. In the area with high NASA-USDA soil moisture value, the soil moisture value retrieved by GA-BP is also high, the soil moisture value retrieved by NASA-USDA is low, and the soil moisture value retrieved by GA-BP is also low. However, the soil moisture map of NASA-USDA represented by (a4), (b4), (c4), (d4), and (e4) has a low spatial resolution, which can not distinguish the terrain of the experimental area, let alone show the change of soil moisture in each area in detail. It can only reflect the overall, low-resolution soil moisture variation in the experimental area, and it is challenging to distinguish soil moisture variation in different areas. It can only show a whole patch of the same color, and the temporal resolution is low, which cannot reflect the daily changes of soil moisture. In contrast, the soil moisture product generated in this paper provides daily soil moisture changes over a 500-m range. Under the same climatic conditions, whether it is the Central Valley floor in the center, the Coastal Mountains in the west, the Sierra Nevada in the south, or the desert areas in the southeast, it can show the differences in soil moisture in these regions in more detail. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Accuracy Index** & \multicolumn{3}{c}{**Pearson’s Correlation Coefficient R**} \\ \hline NASA-USDA and PBO & \begin{tabular}{c} \textless{}0.6 \\ 12 \\ \end{tabular} & \begin{tabular}{c} 0.6–0.8 \\ 7 \\ \end{tabular} & \begin{tabular}{c} \textgreater{}0.8 \\ 31 \\ \end{tabular} & \begin{tabular}{c} Average \\ 0.8222 \\ \end{tabular} \\ \hline NASA-USDA and GA-BP inversion values & \begin{tabular}{c} \textless{}0.6 \\ 14 \\ \end{tabular} & \begin{tabular}{c} 0.6–0.8 \\ 6 \\ \end{tabular} & \
\begin{tabular}{c} \textgreater{}0.8 \\ 30 \\ \end{tabular} &
\begin{tabular}{c} Average \\ 0.8471 \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Comparison of soil moisture values for NASA-USDA, PBO, and GA-BP models. Figure 7: (a1-a3,b1–b3,c1–c3,d1–d3,e1–e3) are 15 February 2014–1 March 2014 GA-BP inverted soil moisture map for 15 consecutive days during the period, (a4,b4,c4,d4,e4) correspond to the NASA-USDA soil moisture during the period 15 February 2014–1 March 2014 In the picture, the time resolution of NASA products is 3 days, so there are only 5 soil moisture maps in 15 days, one every three days. Blank areas were removed as ancillary data for water body impact areas. The (a4), (b4), (c4), (d4) of the NASA-USDA products show no considerable variation in soil moisture during 15 February 2014-26 February 2014. This is basically consistent with the GA-BP inverted soil moisture map ((a1)-(a3), (b1)-(b3), (c1)-(c3), (d1)-(d3)) generated in this study. During this period, the soil moisture in each region did not change much. The northeastern region is primarily grassland and evergreen coniferous forest with denser vegetation cover. The southeastern part is a coastal area near the sea. The central part is a predominantly agricultural area with year-round irrigation and more rain, resulting in high soil moisture values in the areas mentioned above. The southwest is mostly a desert area with little rainfall all year round, so the soil moisture values are low.