区域冬小麦单产统计数据降尺度制图方法OA

Spatial distribution of winter wheat yield is fundamental for precision crop management.However,fine-scale mapping remains challenging due to the scarcity of field-observed yield samples.Agricultural statistical data are continuous,stable and authoritative,but their application in pixel-scale yield downscaling is still limited.A key challenge is how to characterize spatial heterogeneity while maintaining statistical consistency.The main winter wheat producing area in northern China was taken as the research object,and a downscaling mapping method for regional winter wheat yield statistics was proposed.Firstly,based on the data of vegetation index,meteorology,soil and terrain,a county-scale yield model was constructed by using multiple linear regression(MLR),random forest(RF),and light gradient boosting machine(LightGBM).Secondly,on the premise of maintaining statistical consistency,the relative yield weight was introduced to push the average yield at the county level to the pixel scale,and the refined spatial distribution data of winter wheat yield per unit area were generated.Finally,the accuracy of the downscaling results was verified by field measured samples,and the driving factors of spatial variation of yield per unit area were analyzed based on SHapley additive exPlanations(SHAP)framework.The results showed that the LightGBM model performed best at the county scale(R2=0.79,RMSE=581.51 kg/hm2,MAE=401.48 kg/hm2,MRE=8.20％,NRMSE=9.72％),and the downscaled pixel yield was in good agreement with the measured data(R2=0.65,RMSE=623.32 kg/hm2,MAE=540.65 kg/hm2,MRE=8.45％,NRMSE=9.76％).The yield of winter wheat ranged from 943.96 kg/hm2 to 9 453.06 kg/hm2,which was dominated by medium-high yield level and showed a bimodal distribution,showing a spatial distribution of high in the east and low in the west,high in the plain and low in the mountain.SHAP-based interpretability analysis further indicated that elevation,soil silt content,total phosphorus content,slope and water stress were the main driving factors affecting winter wheat yield variation.Low-yield areas were significantly constrained by topography and soil structure,while high-yield areas were mainly limited by nutrient factors.The proposed downscaling method can provide a useful reference for statistical yield downscaling and can support precision crop management and winter wheat cultivation decision-making.