In response to the growing threat of intensified cropland abandonment to food security in the mountainous areas of northern Hebei, this study selected Zhangjiakou City as the study area. Based on the Google Earth Engine (GEE) platform and Sentinel-2 remote sensing imagery, the continuous change detection and classification (CCDC) algorithm was employed to identify the spatiotemporal patterns, occurrence frequency, and trajectory characteristics of abandoned cropland from 2019 to 2023, and to explore the driving factors of cropland abandonment. The results were as follows. 1) During the study period, the total area of abandoned cropland in Zhangjiakou increased from 329.12 km² to 449.41 km², showing a fluctuating upward trend, with an average annual abandonment rate of 4.18%. Spatially, cropland abandonment in the Bashang Plateau region was relatively concentrated, followed by the central and southern river valley basins, while the eastern mountainous and hilly areas had the least, showing clear regional differentiation and a predominantly high–high spatial clustering pattern. 2) In terms of frequency, cropland abandoned twice was dominant, followed by cropland abandoned three times, while cropland abandoned once or more than three times accounted for a relatively small proportion. The latitudinal distribution of abandonment frequency showed a “two-peak and one-trough” pattern, whereas the longitudinal distribution displayed “more in the west and fewer in the east, with multiple peaks and valleys”. 3) In terms of trajectory, newly abandoned cropland was dominant, mostly distributed in the eastern mountainous and hilly region. Reclaimed abandoned cropland ranked second, concentrated in the Yuxian–Yangyuan basin. Fluctuating and regular abandonment ranked third and fourth, respectively, both mainly occurring in the Bashang Plateau. 4) Elevation, slope, and GDP exhibited promoting effects on cropland abandonment in most areas, while population size and distance to roads were predominantly inhibitory. The influencing intensity of each driving factor decreased sequentially in the order of GDP, population size, elevation, slope, and distance to roads.

cropland abandonment, spatiotemporal patterns, abandonment occurrence frequency, evolutionary trajectory, driving factors, Zhangjiakou City