Large-scale, high-resolution mapping of crop patterns is useful for the assessment of food security and agricultural sustainability but is still limited. This study attempted to establish remote sensing-based crop classification models for specific cropping systems using the decision trees method and monitored the distribution of the major crop species using Sentinel-2 satellites (10 m) in 2017. The results showed that the cropping areas of maize, rice, and soybean on the Northeast China Plain were approximately 12.1, 6.2, and 7.4 million ha, respectively. The cropping areas of winter wheat and summer maize on the North China Plain were 13.4 and 16.9 million ha, respectively. The cropping areas of wheat, rice, and rape on the middle-lower Yangtze River plain were 2.2, 6.4 and 1.3 million ha, respectively. Estimated images agreed well with field survey data (average overall accuracy = 94%) and the national agricultural census data (R² = 0.78). This indicated the applicability of the Sentinel-2 satellite data for large-scale, high-resolution crop mapping in China. We intend to update the crop mapping datasets annually and hope to guide the adjustment and optimization of the national agricultural structure.

Understanding the effect of climate warming and technological progress on crop production systems is crucial for developing climate adaptation strategies. This study presents a methodological framework with which to assess the suitability of the double rice cropping system in Southern China and the effects of crop management and climate warming on its distribution. The results indicate that the isolated effects of climate warming have led to the northward and westward expansions of double rice northern limits over the past six decades and an increase in suitable areas by 4.76 Mha. Under the isolated effect of crop management, the northern limits of the medium- and late-maturity double rice changed significantly due to the increased accumulated temperature required caused by varietal replacement and planting date change, which moved an average of 123 and 134 km southward, respectively. A combined scenario analysis indicated that crop management could offset the effects of climate warming and push the northern limits southward, reducing the overall suitable area by 1.31 Mha. Varietal replacement and other crop management methods should also be appropriately considered in addition to climate warming to develop locally adapted agricultural management strategies.

Confronted with the great challenges of globally growing populations and food shortages, society must achieve future food security by increasing grain output and narrowing the gap between potential yields and farmers’ actual yields. This study attempts to diagnose the climatic and agronomic dimensions of oat yield gaps and further to explore their restrictions. A conceptual framework was put forward to analyze the different dimensions of yield gaps and their limiting factors. We quantified the potential yield (Yp), attainable yield (Yt), experimental yield (Ye), and farmers’ actual yield (Ya) of oat, and evaluated three levels of yield gaps in a rain-fed cropping system in North and Northeast China (NC and NEC, respectively). The results showed that there were great differences in the spatial distributions of the four kinds of yields and three yield gaps. The average yield gap between Yt and Ye (YG-II) was greater than the yield gap between Yp and Yt (YG-I). The yield gap between Ye and Ya (YG-III) was the largest among the three yield gaps at most sites, which indicated that farmers have great potential to increase their crop yields. Due to non-controllable climatic conditions (e.g., light and temperature) for obtaining Yp, reducing YG-I is extremely difficult. Although YG-II could be narrowed through enriching soil nutrients, it is not easy to improve soil quality in the short term. In contrast, narrowing YG-III is the most feasible for farmers by means of introducing high-yield crop varieties and optimizing agronomic managements (e.g., properly adjusting sowing dates and planting density). This study figured out various dimensions of yield gaps and investigated their limiting factors, which should be helpful to increase farmers’ yields and regional crop production, as long as these restrictions are well addressed.

Quantifying reasonable crop yield gaps and determining potential regions for yield improvement can facilitate regional plant structure adjustment and promote crop production. The current study attempted to evaluate the yield gap in a region at multi-scales through model simulation and farmer investigation. Taking the winter wheat yield gap in the Huang-Huai-Hai farming region (HFR) for the case study, 241 farmers’ fields in four typical high-yield demonstration areas were surveyed to determine the yield limitation index and attainable yield. In addition, the theoretical and realizable yield gap of winter wheat in 386 counties of the HFR was assessed. Results showed that the average field yield of the demonstration plots was 8282 kg/ha, accounting for 0.72 of the potential yield, which represented the highest production in the region. The HFR consists of seven sub-regions designated 2.1–2.7: the largest attainable yield gap existed in the 2.6 sub-region, in the southwest of the HFR, while the smallest was in the 2.2 sub-region, in the northwest of the HFR. With a high irrigated area rate, the yield gap in the 2.2 sub-region could hardly be reduced by increasing irrigation, while a lack of irrigation remained an important limiting factor for narrowing the yield gap in 2.3 sub-region, in the middle of the HFR. Therefore, a multi-scale yield gap evaluation framework integrated with typical field survey and crop model analysis could provide valuable information for narrowing the yield gap.