[Objective] Real-time monitoring and scientific early warning of landslide risk at waste disposal areas along mountainous highway from three perspectives-space, air, and ground were conducted to provide key data and technical support for accurately monitoring the safety status of slag abandonment sites. The results provide a theoretical reference for the formulation of landslide risk assessment and control strategies for waste disposal areas. [Methods] Xuanwe-Qujing Expressway waste disposal areas (38^#, 41^#, and 45^#) were selected as the research objects, and a real-time dynamic waste disposal area landslide safety early warning and monitoring platform was constructed using modern monitoring and network communication technologies. By integrating satellite remote sensing technology and unmanned aerial photogrammetry with ground sensors, the pattern of slope feature variation and surface deformation in the waste disposal areas from 2015 to 2024 at multi-spatial and multi-temporal scales was analyzed. In addition, the early warning of landslide risk was determined by utilizing evidence of cumulative deformation and deformation rate. [Results] ① Vegetation was gradually reestablished within the disturbed areas, and the overall vegetation coverage of the waste disposal areas in 38^#, 41^#, and 45^# increased by an average of 50% from 2018 to 2024. ② The actual disturbed areas of 38^# and 41^# were only 0.04 beyond the designed disturbed area, whereas the disturbed range of 45^# remained unchanged. Furthermore, the amount of slag and disturbed area, maximum pile height, slope, and slope ratio were in line with the stability requirements for landslides, indicating that the overall slopes of the waste disposal areas maintained a stable state, and the possibility of landslide risk was low. ③ The total average deformation rate of each monitoring point showed that cumulative deformation in the direction of 41^#JCD3-elevation reached a maximum value of 1 815.4 mm, which is within the critical interval of cumulative deformation with respect to warning level, and the landslide deformation exhibited a decreasing trend. Thus, the likelihood of landslide risk is reduced. [Conclusion] Based on the early warning judgment method, the landslide warning level of different waste disposal areas was level Ⅰ (the lowest risk level), and when the cumulative amount of displacement reached the preset threshold that triggered the early warning system, the intelligent space-air-ground monitoring performance was effectively verified.