Constructing high-speed railways (HSRs) is critical for developing countries to stimulate economic growth and urbanization. This study focuses on the Lao section of the China–Laos Railway (CLR) and employs explicitly spatial remote sensing images to investigate the urban development surrounding HSR stations. Data-driven machine learning and causal inference approaches are integrated to quantify the spatial–temporal evolution and discover its driving factors. The results suggest that the CLR has had positive spatial spillover effects on the development of the surrounding urban space. These spillover effects have exhibited a distance attenuation pattern, reflecting obvious development in 2D rather than in 3D urban space. Meanwhile, the distance to stations and adjacent city centers as well as functional urban characteristics, such as land use patterns and industrialization level, have significantly influences the surrounding spatial development. Specifically, in industrial-dominated cities, the surrounding spatial changes have been most significant under the influence of the HSR. Change related to industrial and residential land use has shown significant land expansion patterns and increased utilization efficiency, reflecting that industrialization and urbanization have been the primary drivers of land demand surrounding the HSR. The findings offer valuable insights and references for developing nations to formulate and implement spatial management policies and initiatives related to HSR.

Economic corridors play a crucial role in promoting economic growth and facilitating coordinated regional development. However, land use changes associated with the development of emerging economic corridors have become a prominent source of conflict in regional integration in the Global South. This study takes the Laos Economic Corridor as a case study to explore the characteristics and driving mechanisms of land use changes in emerging economic corridor regions. Using global land cover data from 2000 to 2020 (GlobeLand30) and employing spatial statistical analysis, the Random Forest (RFC) algorithm, and the CA-Markov model, the study follows a Pattern–Process–Mechanism–Trend analytical framework to reveal the spatial distribution characteristics and transformation paths of land use within the corridor. The study results indicate that (1) The land use pattern in the Laos Economic Corridor has gradually shifted from a “single-core radial” structure to a “dumbbell-shaped” structure, promoting coordinated regional economic development. (2) A significant unidirectional flow of land use has been established, with forestland being converted into cultivated land and cultivated land being further converted into artificial surfaces. (3) In addition to the natural geographical constraints, the transport infrastructure and the spatial layout of industries are the main drivers for the expansion of ecological land, agricultural land, and built-up land. (4) Spatial planning interventions are essential and urgent: the establishment of land management rules based on the principles of forest conservation and intensive development can effectively control the uncontrolled expansion of artificial areas, significantly reduce the loss of forestland, and ensure the rational allocation of land resources for long-term development. The findings of this study offer valuable insights and reference points for the Global South, enhancing understanding of the spatial development dynamics of economic corridors, informing the optimization of land-use policies, and supporting efforts to promote regional integration and sustainable development.