Remote sensing for cultural heritage: A systematic review

• A bibliometric analysis of remote sensing (RS) for cultural-heritage was conducted. • Multi-platform RS methods currently employed in this domain were examined. • Their performance was substantially enhanced through multi-scale integration. • Cross-disciplinary strategies were pioneered to propel the next frontier of research. Cultural heritage is an integrated system that encompasses both heritage ontology and their surrounding environments. Traditional methods, such as field measurements, are often inefficient and fragmented in assessing the condition of cultural heritage. In recent years, remote sensing has emerged as a crucial tool for the systematic safeguarding and conservation of cultural heritage, thanks to its high spatiotemporal observation capabilities. Utilizing optical, radar, and laser sensors mounted on satellites, aircraft, unmanned aerial vehicles, and terrestrial platforms, remote sensing offers a comprehensive approach to ensure the sustainability of cultural heritage. This study addresses critical gaps in the emerging, interdisciplinary field of remote sensing for cultural heritage—including limited terrestrial platform coverage, underutilized AI paradigms, and insufficient policy integration—by conducting a systematic, state-of-the-art bibliometric analysis of peer-reviewed papers from the Web of Science Core Collection (1900–2024). Based on this analysis, we summarized the applicable methods, sensor platforms, and applications of remote sensing in cultural heritage conservation and proposed a theoretical framework incorporating relevant methodologies and models. Our results indicate that the integration of multi-spatiotemporal data and diverse technologies is a key characteristic of the disciplinary development. In addition, to application-oriented methodologies, hazard-risk mapping and sustainability assessment of cultural heritage are identified as two potential future directions, which align with the progress assessment of Sustainable Development Goal Target 11.4 by harnessing economic, political and institutional drivers in concert. Leveraging artificial intelligence, data-driven knowledge mining, and multi-source coupling, remote sensing for cultural heritage is transitioning from heritage-specific sustainability through systematic monitoring and evaluation to a broader focus on regional sustainability where heritage sites are located.