Detection of Water Pipeline Leakages Using High-Resolution Satellite Imagery and Auxiliary Ground Data in Cyprus. Case study of Community Councils of Doros and Monagri
Date Issued
October 28, 2025
DOI
10.1117/12.3069672
Abstract
Water losses due to pipeline leakages remain a persistent challenge in water-scarce regions, particularly within rural and mountainous communities where detection and maintenance are more complex. On average, 20–30% of distributed freshwater is lost before reaching consumers, and in areas with ageing infrastructure, this proportion can rise to nearly 50%, exacerbating the stress on limited water resources. This study presents a multi-source geospatial approach to detect and verify pipeline leakages in the distribution networks of the Doros and Monagri community councils in Cyprus. The methodology combines analysis of very high- (PlanetScope | 3m) and high- (Sentinel-2 | 10m) spatial resolution satellite data, strategically acquired during prolonged dry periods to maximise the detectability of leakage-induced anomalies in soil moisture and vegetation. Satellite analysis was complemented with drone-based surveys for centimetre-level validation, acoustic noise loggers for in-pipe monitoring, and Ground Penetrating Radar (GPR) profiling to characterise subsurface conditions. The results demonstrate that while some vegetation indices (NDVI, SAVI) were less sensitive to localised leakage signals, moisture-sensitive indices (NMDI, NDWI) consistently highlighted leakage zones. UAV imagery successfully confirmed satellite-detected hotspots, revealing surface manifestations such as cracking and localised greening. Acoustic sensors detected distinct leak-related signals but also produced inconclusive anomalies, with one strong signal most likely originating from pressure-regulating equipment rather than an actual leak. GPR surveys provided critical subsurface validation, with multi-directional profiling reducing false positives and strengthening confidence in anomaly detection. Overall, the integration of satellite, UAV, acoustic, and GPR data proved significantly more effective than any single method, offering a robust and replicable framework for leak detection in semi-arid, rural water networks. The study highlights both the advantages and the limitations of each method and underlines the value of cross-validation for prioritising excavations and maintenance. The findings are directly transferable to other Mediterranean and semi-arid regions facing similar challenges, supporting more efficient, timely, and cost-effective water resource management.
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