| Summary: | The development of techniques for the detection of water leaks from underground pipelines is seen as a high profile activity by water companies and regulators. This is due to increasing water demands and problems with current leak detection methods. In this thesis optical reflectance and microwave backscatter were used to identify optimal indices for detecting water leaks amongst a variety of different land cover types at different growth stages. Ground-based surveys and modelling techniques were used to establish optimal wavelengths for detection. Results from these studies suggested that in the optical domain visible/middle infrared ratios show potential for leak detection for a wide range of leak types, under a variety of vegetation canopies at different growth stages. Given the sensitivity of L-band radar to moisture, and the ability to separate contributions from canopy and ground surface, it is possible to detect surface water beneath a range of vegetation canopies. The optimal leak detection indices were then used to idenitfy leaks on airborne image data. The available image data was L - band fully polarimetric E-SAR data, and 126 channel HYMAP hyperspectral airborne data which were acquired over an 8km section of the Vrynwy aqueduct (UK), which included a high concentration of leaks. Four of the five leaks were identifiable on the optical image data and none of the leaks were detectable on the microwave data. However the E-SAR data was obtained under unfavourable conditions. The results of both approaches are used to infer limits of detection in terms of season and meteorological conditions for a range of land covers. Preliminary findings suggest that leaks may be optimally detected when canopy height is low, surrounding soil is dry after a period of no rain, and the leak has been present for at least 2 days. The results from this work suggest that remote sensing is both an effective and feasible tool for leak identification.
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