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Understanding the spatial distribution of soil organic matter (SOM) is important for land use management, but conventional sampling methods require significant human and financial resources. How to map SOM and monitor its changes using a limited number of sample points combined with remote sensing techniques that provide long-time series data is crucial. This study aimed to generate a regional-scale near-surface SOM map using 70 soil samples and covariate environmental factors extracted mainly from Landsat 8 OLI. Firstly, the sensitivity of each environmental factor to SOM was tested using a geographic detector model (GDM). Secondly, the tested factors were selected for modeling and mapping by ordinary least squares (OLS) and geographically weighted regression kriging (GWRK). The performance of these two models was compared. Finally, the mapping results of the better model (GWRK) were compared and analyzed with the traditional interpolation results based solely on sampling points to verify the rationality of the proposed method. The results show that three environmental factors, ratio vegetation index (RVI), differential vegetation index (DVI), and terrain roughness (TR), have a strong influence on the spatial variability of SOM. Using these three factors in combination with the GWRK method, a more accurate and refined spatial distribution map of SOM can be obtained. Comparing the SOM maps of GWRK and the traditional interpolation method, the results show that the accuracy of GWRK (R2 = 0.405; mean absolute error = 0.637, and root mean square error = 0.813) is higher than that of traditional interpolation methods (R2 = 0.291, MAE = 0.609, and RMSE = 0.863). The spatial recognition rate (fineness) of SOM patches at all levels using the GWRK method increased by more than 73 times compared to the traditional kriging. We conclude that the combination of limited SOM samples, environmental variables, GDM, and GWRK is a pragmatic approach for estimating regional-scale SOM.

Teaming a strong preschool with less-developed, rural, or newly established preschools is an effective strategy to promote quality. Since 2015, Shanghai has sought to improve preschool education quality through collaboration. Guided by the “3A2S” theoretical framework, this study evaluated the development and effectiveness of preschool federations in the city using a mixed-methods approach. First, document analysis was conducted to depict features of preschool federations in Shanghai, which identified three main features. Next, a survey study including 702 stakeholders was conducted to assess the evaluations of preschool administrators, teachers, and parents of the effectiveness of preschool federations. Finally, an interview study including 15 stakeholders was conducted to triangulate the findings of the survey study. Results revealed that the stakeholders highly approbated the preschool federations, but parents’ evaluation was significantly lower than that of other stakeholders. Finally, the sustainability and affordability of the preschool federation policy are discussed herein. Implications for policy development and preschool management are also presented.