Satellite data have emerged as a widely used tool for global research. In particular, satellite data aid in overcoming long-term observational challenges caused by seasonal effects, facilitating comprehensive monitoring of large regions and simplifying infrastructure maintenance. However, in Korea, the application of satellite SAR (Synthetic Aperture Radar) data within the construction sector remains relatively limited. This study used satellite SAR data to analyze the effects of infrastructure (underground roads and subway systems) currently under construction in Korea on the surrounding ground surface, in order to identify risk zones. This study explored methods for continuously monitoring extensive areas over long distances and selecting potential risk zones. The results indicated substantial ground displacements at specific locations and seasonal changes. Furthermore, past and current satellite SAR data were overlapped to facilitate a time-series analysis. The results confirmed that satellite SAR can improve the monitoring of construction projects in Korea and provide valuable information that can contribute to enhancing maintenance efforts, including near-future ground displacement data. The results are expected to help citizens maintain a safe and sustainable life in urban areas.

Internet of Things (IoT)-based slope monitoring systems support real-time stability surveillance, but frequent false alarms cause alarm fatigue and delay responses to genuine hazards. We developed a clustering-based framework that classifies alarm causes into three categories—Malfunction, Actual Displacement, and Others—from inclinometer and extensometer data. From 55 alarm events recorded at 43 monitoring stations in 2025, 85 domain-informed features (statistical, waveform, spatial-correlation, trend, sudden-synchronization, and malfunction-pattern) were extracted and compared across five feature-extraction methods, six selection levels, and three clustering algorithms. Because the feature ranking uses expert-assigned labels, the framework is characterized as label-informed feature ranking followed by unsupervised clustering, and it was evaluated with 100 random seeds, nested leave-one-site-out validation, bootstrap confidence intervals, and permutation tests. A compact set of five features—three cross-correlation-based synchronization features and two spatial-correlation features—was stable across seeds and achieved a leave-one-site-out accuracy of 0.80 (95% CI 0.69–0.89) with the full 8 h window. Using only data recorded up to the alarm time, accuracy rose to 0.91 (0.84–0.98), 12 of the 13 Actual Displacement events were recovered (recall 0.92), and no non-displacement event was assigned to the displacement cluster. Synchronization features separated genuine displacement from the other causes, whereas spatial-correlation features distinguished external disturbance from sensor malfunction. The interpretable framework is proposed as a decision-support filter that complements conventional threshold-based alarms.

Recently, various drawbacks have been pointed out on the aspects of design, construction, and maintenance of anchor-reinforced slopes, and in some research the causes of increases and decreases of the tension force of the anchor are analyzed. However, research on the development of technology to cope with increases and decreases of the tension force in terms of maintenance is rare. In case that slipping occurs on an anchor-reinforced slope, shear and bending stress will occur in the shear section along the slip surface, and the anchor force may increase when slipping persists due to the deformation of the anchor body. Additionally, if shear deformation occurs in the anchor, cracks will occur in the grout at a relatively low deformation rate, and when deformation continues, the tension force may be further reduced due to the destruction of the grout. We tried to define investigation methodologies and safety plans through the analysis of case studies on functional loss sections, such as fractures of strands due to the excessive load placed on the anchors. From the results of the anchor lift-off test of 466 holes, the number of anchors that could not be retensioned was 177 holes, and the number of anchors with an increased tension force was 49 holes. From the results of ground exploration, it was found that soiled weathering zones or weathering zones with fractured bedrock were distributed at depths of 30m or more. It is analyzed that most anchor settlement with insufficient anchor forces were located in the slip surface and lacked anchor length. It is found that the safety of the slope can be secured if additional reinforcing anchors are installed around anchors with poor strand strength or anchors that cannot be retensioned.(Project Number: 20SCIP-C151408-02).

Slope hazard monitoring systems constitute a fundamental component of slope early warning systems, supporting timely warning issuance and risk mitigation for unstable natural and engineered slopes. However, many operational monitoring networks rely on heterogeneous sensors and data loggers from multiple manufacturers, leading to compatibility issues that undermine long-term reliability and continuity of early warning monitoring. When components require replacement due to durability limitations or product discontinuation, entire monitoring systems are often replaced, resulting in high maintenance costs and prolonged monitoring interruptions that can compromise hazard detection and warning effectiveness.This study presents an interoperable sensor system and integrated data acquisition device designed to enhance the reliability and sustainability of monitoring components within slope early warning systems. A nationwide survey of 200 slope monitoring sites managed by a Korean government agency identified 5,669 installed sensors and revealed strong dependence on a limited number of manufacturers. Based on these findings, system specifications were established to ensure broad compatibility with dominant commercial products and existing monitoring infrastructures, enabling long-term operation of early warning monitoring networks.The developed data acquisition system supports multiple sensor types commonly used for slope hazard assessment, including displacement, inclination, rainfall, and groundwater level sensors, and integrates diverse communication protocols (LAN, LTE, Wi-Fi, and LoRa) for real-time data transmission. Key features include bidirectional sensor control with self-diagnostic functions, lightning and overvoltage protection, remote configuration, and intelligent fault detection, ensuring stable monitoring performance under hazardous environmental conditions. Smart compatible sensors were also developed to ensure interoperability, remote monitoring, and enhanced durability compared to conventional slope monitoring sensors.System performance was verified through certified electromagnetic compatibility testing and field evaluations at laboratory-scale and operational slope monitoring sites. Results demonstrated stable operation, seamless compatibility with existing systems, and measurement performance comparable to commercial products.By enabling flexible sensor replacement and reducing dependency on specific manufacturers, the proposed approach improves the operational reliability and continuity of monitoring components in slope early warning systems. This contributes to more robust warning chains, proactive hazard management, and disaster risk reduction through resilient and sustainable monitoring infrastructures (Project No. RS-2025-02263904, second year).