# Remote Sensing and Machine Learning for Safer Railways: A Review
## 2 Research Method  
The choice of the SLR method for this study stemmed from its rigorous and structured approach [10], which is essential for synthesizing the existing literature in a field as complex and varied as railway infrastructure monitoring using RS and ML technologies. SLRs are particularly suited for areas with diverse methodologies and findings, as they provide a comprehensive overview of the state of the research and can identify gaps and suggest areas for future investigation. This method ensures a transparent, reproducible research process, enhancing the credibility and reliability of the findings by minimizing bias through predefined inclusion and exclusion criteria. Central to the SLR methodology, the authors implemented several steps to thoroughly examine the relevant literature by formulating the review questions, searching for publications, evaluating and refining the publications selected, analyzing and synthesizing the findings, and reporting the outcomes.  
Following the establishment of the main objective, the authors formulated the final research questions as outlined in the introduction section. The publication search phase used specific inclusion and exclusion criteria. Initially, the search examined general publications related to RS, transportation infrastructure, and ML, in addition to SLR publications on other topics. After reviewing the initial set of publications, the authors narrowed the search to focus solely on publications relating to both RS and ML in the context of rail infrastructure. The inclusion criteria were peer-reviewed journal publications encompassing all three aspects--RS, ML, and railway infrastructure inspection. That is, the authors excluded any publication that lacked all three elements.  
The initial search utilized Google Scholar for its strength in locating academic literature from multiple databases, including Scopus, IEEE, and Web of Science. The search encompassed entering the specific phrases shown in Table 1. The number of records initially identified was 2151, but further screening of the titles and abstracts yielded 42 publications, as summarized in Table 1. Further scrutiny of each publication yielded 10 relevant publications after excluding 32, of which, 29 did not fit the topic scope and 3 were not from journals.  
Subsequently, the authors applied the snowball technique to explore the cited works of the 10 relevant publications, which uncovered an additional 113 relevant publications.  
Careful examination of these included adding short summaries or review points gleaned from each. The authors then established a table to catalog all the methods used, including the main features of their methods, as discussed later in the results section. This scrutiny removed 68 publications from the 113, resulting in 45 that were relevant. Of the excluded publications, 28 were out of scope, 2 were duplicates, 5 lacked ML content, 12 did not focus on railway infrastructure, and 21 were not journal publications. The 10 initial publications selected plus the 45 screened from the snowball procedure resulted in a final tally of 55 relevant publications for further analysis.