## 2 Study Area and Data Sources
### Data Sources
#### 2.2.2 Field Crop Samples  
A field survey was conducted in Zhangjiakou from mid-July to late August 2023 to create a ground database. Mobile GIS devices (Ovital v9.1.3) were used to record location and crop types at each sample point for accuracy assessment. To ensure consistency between reference and image data, a 10 m buffer was applied to each training sample [41]. The database included 363 sample points, covering maize, potato, oats, sesame, and other crops. Vegetables, sunflowers, rapeseed, wheat and sugar beets were also surveyed and classified as \"other crops\". To account for interannual variability, additional field observations from 2021 and 2022 were used exclusively for validating historical classifications and were not included in model training (Figure 1). Samples were strategically distributed across diverse topographic zones and cropping systems, encompassing both irrigated lowlands and rainfed uplands. To ensure adequate representation of all crop types, samples were randomly divided into a training set (60%) and a validation set (40%). This ratio improves  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Data** & **Time** & **Resolution** & **Data Access** & **Last Access** \\ \hline Sentinel-2 MSI & 2019, 2020, 2021, 2022, 2023 & 10 m & [[https://developers.google.com/earth-engine/datasets/catalog/catalog/COPERNICUS](https://developers.google.com/earth-engine/datasets/catalog/catalog/COPERNICUS)]([https://developers.google.com/earth-engine/datasets/catalog/catalog/COPERNICUS](https://developers.google.com/earth-engine/datasets/catalog/catalog/COPERNICUS))\_S2 & 08 January 2025 \\  & & & [[https://developers.google.com/earth-engine/datasets/catalog/catalog/Landsat8/9](https://developers.google.com/earth-engine/datasets/catalog/catalog/Landsat8/9)]([https://developers.google.com/earth-engine/datasets/catalog/catalog/Landsat8/9](https://developers.google.com/earth-engine/datasets/catalog/catalog/Landsat8/9)) & 2019, 2020, 2021, 2022, 2023 & 30 m & LANDSAT\_LC08\_C02\_T1\_L2; \\  & 2019, 2020, 2021, 2022, 2023 & 30 m & [[https://developers.google.com/earth-engine/datasets/catalog/catalog/Landsat](https://developers.google.com/earth-engine/datasets/catalog/catalog/Landsat)]([https://developers.google.com/earth-engine/datasets/catalog/catalog/Landsat](https://developers.google.com/earth-engine/datasets/catalog/catalog/Landsat))\_LC09\_C02\_T1\_L2 & 08 January 2025 \\  & & & [[https://developers.google.com/neut-engine/datasets/catalog/Landsat](https://developers.google.com/neut-engine/datasets/catalog/Landsat)]([https://developers.google.com/neut-engine/datasets/catalog/Landsat](https://developers.google.com/neut-engine/datasets/catalog/Landsat))\_LC09\_C02\_T1\_L2 & 08 January 2025 \\ Sentinel-1 SAR & 2019, 2020, 2021, 2022, 2023 & 10 m & [[https://developers.google.com/earth-engine/datasets/catalog/Landsat](https://developers.google.com/earth-engine/datasets/catalog/Landsat)]([https://developers.google.com/earth-engine/datasets/catalog/Landsat](https://developers.google.com/earth-engine/datasets/catalog/Landsat))\_LC09\_C02\_T1\_L2 & 08 January 2025 \\ The Shuttle Radar & 2023 & 30 m & earth-engine/datasets/catalog/Landsat\_LC09\_C02\_T1\_L2 & 08 January 2025 \\ Topography & 2023 & 30 m & earth-engine/datasets/catalog/USSG\_SRTMGL1\_003 & 08 January 2025 \\ Dynamic World & 2019, 2020, 2021, 2022, 2023 & 10 m & earth-engine/datasets/catalog/GOOGLE\_DYNAMICWORLD\_V1 & 16 October 2024 \\ Agricultural & 2019–2022 & County & [[https://www.zjk.gov.cn](https://www.zjk.gov.cn)]([https://www.zjk.gov.cn](https://www.zjk.gov.cn)) & 05 December 2024 \\ statistics data & July 2023–August & & & \\ Field survey sites & 2023 & In-situ & Field survey & July–August 2023 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Summary of data used in this study.  
model generalization in fragmented and phenologically complex agricultural systems and aligns with practices in similar studies [42].