During the Middle-to-Late Neolithic period (7000–3800 BP), Shaanxi Province served as a critical juncture in the transmission of crops. Foxtail millet (Setaria italica), broomcorn millet (Panicum miliaceum), and rice (Oryza sativa) spread westwards into the Gansu–Qinghai region and southwards into the Sichuan basin, whilst wheat (Triticum aestivum) and barley (Hordeum vulgare) were transmitted through the Shaanxi region to the middle and lower Yellow River regions. Neolithic settlements are found in all three of the main geomorphic settings in Shaanxi: the Loess Plateau, plains, and mountainous areas. While the extent to which crop diffusion and distribution were influenced by environmental changes has previously been highlighted, the strategies of crop utilization in different geomorphic contexts have not been specified. Based on crop-remains data from 33 archaeological sites in Shaanxi, this study uses statistical modeling and ArcGIS-based spatial analysis to investigate prehistoric crop utilization in Shaanxi during the Neolithic period and its environmental determinants. Our results indicate the following: (1) The dominant crops in the Neolithic Shaanxi were foxtail millet and broomcorn millet, with the proportion of foxtail millet increasing over time. (2) The Guanzhong Plain was the earliest region in Shaanxi to adopt millet and rice (~7000–3800 BP). Subsequently, millet and rice had influenced the Qinba Mountains by ~5000 BP at the latest. By ~3800 BP, millet had affected the entire northern Shaanxi Plateau, with rice only found at the Shimao site around 4000 BP. Finally, wheat and barley influenced the Guanzhong region and the Qinba region in Shaanxi around 4000 BP. In addition, rice, wheat, and barley mainly enhanced agricultural diversity in the Guanzhong Plain and Qinba Mountains but had limited impact in the Northern Plateau, where cattle and sheep have enriched subsistence strategies since about 4500 BP. (3) Environmental factors affected the distribution of crops to different extents—elevation and river proximity had minimal effects on foxtail millet and broomcorn millet but significantly influenced the presence of rice, wheat, and barley. These factors led to a spatial pattern where millet dominated in the Northern Plateau, while the Guanzhong Plain and Qinba Mountains developed mixed farming systems incorporating all four seed types. This study provides new insights into the environmental mechanisms influencing crop diffusion and prehistoric human adaptation during the Neolithic period in Shaanxi.

Over the past decade, the rapid development of geospatial tools has significantly expanded the scope of archaeobotanical research, enabling unprecedented insights into ancient plant domestication, agricultural practices, and human-environment interactions. Within the Chinese context, where rich archaeobotanical records intersect with complex socio-ecological histories, GIS-driven approaches have revealed nuanced patterns of crop dispersal, settlement dynamics, and landscape modification. However, despite these advances, current applications remain largely exploratory, constrained by fragmented datasets and underutilized spatial-statistical methods. This paper argues that a more robust integration of large-scale archaeobotanical datasets with advanced ArcGIS functionalities—such as kernel density estimation, least-cost path analysis, and predictive modelling—is essential to address persistent gaps in the field. By synthesizing case studies from key Chinese Neolithic and Bronze Age sites, we demonstrate how spatial analytics can elucidate (1) spatiotemporal trends in plant use, (2) anthropogenic impacts on vegetation, and (3) the feedback loops between subsistence strategies and landscape evolution. Furthermore, we highlight the challenges of data standardization, scale dependency, and interdisciplinary collaboration in archaeobotanical ArcGIS. Ultimately, this study underscores the imperative for methodological harmonization and computational innovation to unravel the intricate relationships between ancient societies, agroecological systems, and long-term environmental change.