## 5 Conclusions  
Crop rotation affects soil pH considerably in both direct (e.g., removal of base cations by harvest) and indirect (e.g., fertilization, irrigation, tillage) ways, yet its usefulness and effectiveness for soil pH mapping remains unclear. This study assessed whether and to what extent incorporating crop rotation could improve the digital mapping of soil pH. The innovation was the incorporation of satellite crop rotation maps in predicting cropland soil pH. To unveil the effects of crop rotation on soil pH mapping, we proposed a new soil sample grouping and separate modeling strategy for paddy, vegetable, and orchard rotation systems. Our results showed the following: (1) simply incorporating crop rotation was useful for predicting soil pH and contributed the most to the spatial predictive model, followed by long-term Sentinel-1/2 composites; (2) grouping soil samples by crop rotation significantly increased the prediction accuracy of soil pH by fitting and optimizing the RF sub-models based on different crop rotation subsamples. This likely benefited from the fact that soil pH and its influencing factors varied greatly among the three main crop rotations. We also found that radar images could be considered in the digital mapping of soil pH to supplement optical perceptions through the retrieval of geophysical variables. Our study thus provides a new way of characterizing human interventions in soil pH mapping and further introduces a new soil sample grouping strategy for improving model performance over heterogeneous agricultural landscapes.  
**Author Contributions:** Conceptualization, Q.Y., Q.Z., G.S. ([PERSON]) and W.W.; methodology, Y.L. and S.C.; software, Y.L.; validation, Y.L. and Z.C.; formal analysis, X.Z.; investigation, Y.L., Z.C. and Q.Y.; resources, W.W., Q.Y. and G.S. ([PERSON]); data curation, Y.L.; writing--original draft preparation, Y.L.; writing--review and editing, Q.Y., G.S. ([PERSON]), S.C., C.C. and S.D.B.-K.; visualization, Y.L.; supervision, Q.Y. and S.C.; project administration, W.W.; funding acquisition, Y.L., G.S. ([PERSON]), and J.Z. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was funded by the National Natural Science Foundation of China (Nos. 42171271 and 42401331), the open project of State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China, the Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences (No. EUAL-2024-03), Hebei Natural Science Foundation (No. D2024403075), the National Statistical Science Research Project (2024 LY051), the National Key Research and Development Program of China (2023 YFD150130), the Guiding Funds of Centrale 1 Government for Supporting the Development of the Local Science and Technology (236Z4201G), and the Doctoral Research Start-up Fund Project of Hebei GEO University (No. BQ2024042).  
**Data Availability Statement:** The data used in this study included freely available satellite images available on GEE. Field survey data are available upon requests to the corresponding author ([EMAIL_ADDRESS]).  
**Conflicts of Interest:** The authors declare no conflicts of interest.