With the continuous increase in the operational mileage of railways in our country, the external environment of railways is becoming increasingly complex. Hazards in the external environment of railways, mainly consisting of color steel tile houses, dust-proof nets, plastic greenhouses, ground films, and plastic waste, emerge frequently. These hazards, which frequently lead to major railway traffic accidents, have become a significant constraint on the safe operation of railways. The efficient monitoring of hazards in the external environment of railways is a crucial prerequisite for governance, and remote sensing technology is currently the optimal means to achieve large-scale, low-cost monitoring of external environmental hazards in railways. In this regard, this paper systematically reviews four categories of remote sensing monitoring technologies: optical remote sensing, synthetic aperture radar, lidar, and ground-based video surveillance. The paper discusses the advantages, limitations, and current applications of these technologies. It analyzes two types of monitoring and identification methods: those based on artificial features and those based on deep learning, highlighting their characteristics and shortcomings. Finally, the paper looks forward to the intelligent monitoring of railway external environmental hazards based on the fusion of multi-source remote sensing data at multiple levels, the construction of precise identification models for railway external environmental hazards, and knowledge-guided intelligent dynamic monitoring of railway external environmental hazards.