Multi-Source Remote Sensing for Airport Runway Monitoring: A Review of Techniques and Applications

Abstract

Against the background of new urbanisation and regional integration, construction land planning in smart city clusters is becoming increasingly fine-grained, dynamic, and collaborative. However, traditional planning approaches still face limitations in update frequency, information integration, and cross-regional coordination, making it difficult to support continuous monitoring and timely decision-making. This paper examines the role of high-resolution satellite remote sensing in empowering dynamic construction land planning from the perspectives of theory, technology, and application. A four-level technical framework is proposed, including data collaboration, intelligent perception, quantitative evaluation and analysis, and digital-twin-based decision support. On this basis, the paper discusses key enabling mechanisms, including multi-source data fusion, AI-based interpretation and change detection, index threshold warnings, rule digitisation, and digital twin simulation. It also summarises the adaptation logic of different technologies in typical planning scenarios. The study shows that high-resolution remote sensing can provide important support for monitoring, evaluation, early warning, and coordinated governance in smart city clusters. Nevertheless, challenges remain in data timeliness, cross-regional standardisation, model generalisation, interpretability, and the credible calibration of digital twins, and these deserve further attention in future research.