Cultivated land plays a crucial role as the basis of grain production, and it is essential to effectively manage the unregulated expansion of non-grain production (NGP) on cultivated land in order to safeguard food security. The study of NGP has garnered significant attention from scholars, but the prediction of NGP trends is relatively uncommon. Therefore, we focused on Jiangsu Province, a significant grain production region in China, as the study area. We extracted data on cultivated land for non-grain production (NGPCL) in 2000, 2005, 2010, 2015, and 2019, and calculated the ratio of non-grain production (NGPR) for each county unit in the province. On this basis, Kernel Density Estimation (KDE) and spatial autocorrelation analysis tools were utilized to uncover the spatio-temporal evolution of NGP in Jiangsu Province. Finally, the Patch-Generating Land Use Simulation (PLUS) model was utilized to predict the trend of NGP in Jiangsu Province in 2038 under the three development scenarios of natural development (NDS), cultivated land protection (CPS), and food security (FSS). After analyzing the results, we came to the following conclusions:(1) During the period of 2000–2019, the NGPCL area and NGPR in Jiangsu Province exhibited a general decreasing trend. (2) The level of NGP displayed a spatial distribution pattern of being “higher in the south and central and lower in the north”. (3) The results of multi-scenario simulation show that under the NDS, the area of NGPCL and cultivated land for grain production (GPCL) decreases significantly; under the CPS, the decrease in NGPCL and GPCL is smaller than that of the NDS. Under the FSS, NGPCL decreases, while GPCL increases. These results can provide reference for the implementation of land use planning, the delineation of the cultivated land protection bottom line, and the implementation of thee cultivated land use control system in the study area.

With the intensification of the contradiction between living space and population growth, it is necessary to improve the effectiveness of urban residential land allocation. This study systematically reviews 169 papers following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol to collect and collate the contributing factors that affecting the supply of and demand for urban residential land for different countries, and a statistical analysis of long-term series data is conducted to further verify the rationality of the contributing factors. Based on systematic literature review and empirical analysis, the contributing factor set is constructed to serve the decision-making of residential land allocation. The main findings indicate that the population, house price, income, rent, mortgage loan, investment, the number of affordable houses, GDP, employment, housing stock and migration are the general contributing factors that significantly affect allocation of urban residential land. A systematic understanding of general contributing factors will help decision-makers more intuitively realize the urgent problems of urban residential land supply. Moreover, there are some specific contributing factors influencing the allocation of urban residential land in different types of countries, and the identification of specific contributing factors provides different perspectives on residential land allocation for the differentiated global development status. The contribution of this study is to assist decision-makers formulate more rational residential land allocation strategies by systematically sorting out the contributing factors influencing residential land allocation.