Land use and land cover changes (LULCC) are the result of the combined action of many influencing factors such as nature, society, economy and politics. Taking Chongqing as an example, the driving factors of urban land expansion in Chongqing from 1999 to 2019 are analyzed using a geographic detection (GD) method. Based on this analysis, a land use scenario of Chongqing in 2029 is simulated by an Artificial Neural Network-Cellular Automata model. The results of the analysis of factors affecting land use change show that five factors have a significance >0.05: population, distance from central city, school density, GDP and the distance from railway, showing that these factors have a high impact on LULCC in Chongqing. In addition, the results of risk detection analysis show that areas with a population >50/km²; the areas with a distance 5/km²; areas with a high GDP; and areas with a distance <25 km from the railway have a greater impact on urban land use change than other areas. The land use scenario in 2029 also is simulated based on the land use situation in 2019. The predicted results clearly reflect a land use change trend of increasing urban land and decreasing agricultural land in the region. These land use changes are especially related to the expansion of the population, economy, roads, and schools in the process of urbanization. This analysis also shows that the GD-ANN-CA model developed in this paper is well suited to urban land use simulation.

As a core element of comprehensive land consolidation, cultivated land serves as both a fundamental resource and strategic platform for driving rural revitalization and advancing ecological civilization development. Based on the five periods of remote sensing monitoring data of land use from the 1980 to 2020 in Beichuan Qiang Autonomous County, this study systematically examines cultivated land transfer dynamics and quantitatively assesses fragmentation levels through landscape metrics analysis, with the ultimate objective of informing strategic land consolidation planning at the county scale. The results indicate that (1) the cultivated land transformation in Beichuan Qiang Autonomous County exhibited distinct temporal patterns demarcated by 2010. During the initial phase, limited land transfers predominantly involved woodland transfers, characterized by cross-regional occupation–compensation dynamics and a northwest-oriented spatial shift. The subsequent phase witnessed substantial transfer intensification, incorporating grassland and construction land transfers alongside woodland. This period demonstrated balanced intra-township occupation–compensation mechanisms and a marked southeastward migration of transfer concentration; (2) cultivated land transfer dynamics demonstrated greater intensity in topographically moderate townships, whereas northwestern mountainous townships characterized by elevated altitudes and pronounced gradients maintained comparative spatial stability in transfer patterns; (3) cultivated land fragmentation exhibited topographic modulation, with reduced spatial disaggregation in low-lying plains contrasting elevated indices across northwestern highland terrains; and (4) the cultivated land area showed a predominant reduction in low-elevation and gentle-slope regions, accompanied by a decrease in landscape fragmentation. Conversely, in areas with higher elevations and steeper slopes, expansions in both cultivated land area and fragmentation were observed.