## 3 Results
### Spatial Distribution and Regional Validation of Cultivated Land Quality  
The 2022 dataset of cultivated land quality for Shuanghe Farm categorizes the quality of cultivated land into six grades, with Grade 1 being the highest and Grade 6 the lowest. The distribution of cultivated land quality is illustrated in Figure 8(a). From Figure 8(a), it can be observed that Grade 1 and Grade 2 lands are primarily located in the northeast and southwest regions of Shuanghe Farm. Grade 3 land is mainly distributed in the central and southeastern parts of the farm, with some presence in the northwest as well. Grade 4 and Grade 5 lands are concentrated on the western-central edge, the northwest, and the southeastern margins, with sporadic distributions in the central-southern area. Grade 6 land is mainly distributed in the central-western region. In terms of proportional distribution within the dataset, Grade 1 land accounts for 6.48%, Grade 2 for 19.54%, Grade 3 for 30.89%, Grade 4 for 29.00%, Grade 5 for 12.84%, and Grade 6 for 1.25%. Based on the distribution of different grades of cultivated land, it can be seen that Shuanghe Farm's cultivated land is primarily composed of Grade 2, Grade 3, and Grade 4, with a significant proportion of Grade 5. Grade 1 and Grade 6 lands are less prevalent, with Grade 6 being the scarcest. Overall, the quality of cultivated land in Shuanghe Farm can be considered moderate, with the northeast and southwest regions having relatively higher-quality land, the central and southeastern regions possessing moderate quality, and the northwest showing poorer land quality. The cultivated land quality evaluation results from the BO-Stacking-TabNet model, which uses spectral reflectance from Landsat 9 during typical periods as input indicators, are shown in Figure 8(b). A comparison of Figure 8(a),b reveals that the spatial distribution of cultivated land quality is largely consistent between the two. Based on the proportional distribution of land quality grades in the model's evaluation results, Grade 1 accounts for 6.36%, Grade 2 for 19.31%, Grade 3 for 31.98%, Grade 4 for 28.54%, Grade 5 for 13.18%, and Grade 6 for 0.63%. When comparing these figures to the proportional distribution of cultivated land quality in the Shuanghe Farm dataset, the differences in the proportions for Grades 1, 2, 4, 5, and 6 are all less than 1%. In contrast, the difference for Grade 3 is slightly larger, but the two datasets differ by only 1.09%. Therefore, based on the proportional distribution, the BO-Stacking-TabNet model's evaluation results, which use Landsat 9 spectral reflectance as input, are essentially consistent with the cultivated land quality dataset of Shuanghe Farm. This study also calculated the absolute difference between the cultivated land quality evaluation grades from the Shuanghe Farm dataset and those obtained from the Landsat 9-based remote sensing model during typical periods. The distribution of these differences is shown in Figure 8(c). From Figure 8(c), it can be seen that the vast majority of the farm'sctivated land has consistent evaluation grades between the two methods. In areas where discrepancies exist, fields with a difference of 1 or 2 grades are mainly located in the central-southern and northwestern regions of Shuanghe Farm, with sporadic distributions in the central-northern area. Fields with differences of 3 or 4 grades are primarily found in the central-northern region, with occasional distributions in the central-southern and northwestern parts of the farm. Statistically, 83.95% of the land shows consistent evaluation grades between the two methods. Fields with a difference of 1 grade account for 13.18%, those with a difference of 2 grades account for 2.06%, fields with a difference of 3 grades represent 0.52%, and those with a difference of 4 grades represent 0.29%. Therefore, the statistical data indicate that the cultivated land quality evaluation results based on the Landsat 9 remote sensing model are generally consistent with the evaluation results of Shuanghe Farm.