## 2 Data and Methodology
### Methodology
#### 2.3.6 Garlic Fragmentation Analysis  
To comprehensively analyze the factors contributing to variations in accuracy across different regions, this study leverages previous research findings [44; 45] and integrates the characteristics of the study area to evaluate garlic fragmentation using the GFI. The GFI quantifies the fragmentation of garlic cultivation areas, with higher values indicating greater fragmentation [46]. The formula is provided below:  
\[\text{GFI}=\text{n}/\text{A} \tag{6}\]  
where GFI represents the garlic fragmentation index, n denotes the number of plots planted with garlic, and A is the total area planted with garlic in the sample area.  
Ten square samples, each with a side length of one kilometer, were randomly selected from each county in the study area to assess the degree of garlic fragmentation. The fragmentation of the garlic crop in each county was evaluated based on the GFI of the  
\begin{table}
\begin{tabular}{l l l l l l l l l} \hline \hline
**Feature Sets** & **MSAVI** & **SAVI** & **EVI** & **GNDVI** & **NDVI** & **SAR** & **Multi-Bands** \\ \hline \hline
1 & me-sm & \(\surd\) & \(\times\) & \(\surd\) & \(\times\) & \(\times\) & \(\surd\) & \(\surd\) \\
2 & mg-sm & \(\surd\) & \(\times\) & \(\times\) & \(\surd\) & \(\times\) & \(\surd\) & \(\surd\) \\
3 & mn-sm & \(\surd\) & \(\times\) & \(\times\) & \(\times\) & \(\surd\) & \(\surd\) & \(\surd\) \\
4 & sn-sm & \(\times\) & \(\surd\) & \(\times\) & \(\times\) & \(\surd\) & \(\surd\) \\
5 & e-sm & \(\times\) & \(\times\) & \(\surd\) & \(\times\) & \(\times\) & \(\surd\) & \(\surd\) \\
6 & n-sm & \(\times\) & \(\times\) & \(\times\) & \(\times\) & \(\surd\) & \(\surd\) & \(\surd\) \\
7 & n-s & \(\times\) & \(\times\) & \(\times\) & \(\times\) & \(\surd\) & \(\times\) & \(\times\) \\
8 & n-sswir & \(\times\) & \(\times\) & \(\times\) & \(\times\) & \(\surd\) & \(\times\) & SWIR (only) \\ \hline \hline \end{tabular} In the table, MSAVI, SAVI, EVI, GNDVI, and NDVI refer to the modified soil-adjusted vegetation index, soil-adjusted vegetation index, enhanced vegetation index, green normalized difference vegetation index, and normalized difference vegetation index, respectively. SAR represents time series data from vertical–vertical (VV) and vertical–horizontal (VH) polarizations, along with their ratio. Multi-bands refer to the time series data of the red, green, blue, and shortwave infrared bands. ‘SWIR (only)’ indicates that the feature combination n-sswir includes only the SWIR band from the four bands represented by multi-bands in the time series data. A ‘\(\surd\)’ indicates the presence of the corresponding categorical feature in the feature combination, while a ‘\(\times\)’ denotes its absence.  
\end{table}
Table 1: Combination of classification characteristics.  
\begin{table}
\begin{tabular}{c l l l l l l l} \hline \hline
**Region** & **Class Results** & **Jinxiang** & **Laiwu** & **Lanling** & **Pizhou** & **Qixian** & **Zhongmou** \\ \hline \multirow{3}{*}{Ground Truth (Pixels)} & Garlic & 321 & 149 & 210 & 343 & 236 & 196 \\  & Other & 255 & 355 & 305 & 349 & 280 & 285 \\  & All & 576 & 504 & 515 & 692 & 516 & 481 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Garlic distribution map verification points by county.  
samples. To more accurately reflect garlic fragmentation, the random area range of Laiwu and Pizhou was artificially constrained.