## 1 Introduction
Hyperspectral imaging is a developing technology in remote sensing where an imaging spectrometer collects hundreds of images at different wavelengths for the same spatial area [26]. It is concerned with the measurement, analysis, and interpretation of spectra taken from a given scene or object at a short, medium, or long distance by an airborne (drone) or satellite sensor [27]. The NASA Jet Propulsion Laboratory's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) can record the visible and near infrared spectrum (wavelength range 400-2500 nm) of the reflected light on an area 2-12 km wide and several kilometres long using 224 spectral bands [28]. The result is a stack of images whereby each pixel has a corresponding spectral signature, or 'fingerprint', that distinguishes the underlying objects, and the final data volume comprises several gigabytes per flight [26]. This usually requires hardware accelerators to speed up computations. Hyperspectral sensors are expected to increase their spatial, spectral, and temporal resolutions [26]. The incredible amount of spectral information available from the latest hyperspectral devices has opened doors to real-time processing applications such as monitoring leakages [29]. An IR camera detects infrared energy reflected or emitted by an object and converts it into a thermal image [10]. Leaks in an underground water network may change the temperature of the surrounding soil, as leaked water is typically cooler than soil, which absorbs thermal energy faster than water [10]. In addition, IR cameras can be used at any time of the day, and they can investigate large areas in comparatively less time with lower costs than other NDTs [30]. The paper presented the use of a thermography IR camera for the detection of heat changes at pavement surfaces due to water pipe leaks underneath the surface. The results of the study showed that the IR camera successfully detected several leaks as thermal contrast at pavement surfaces occurred in the fall and spring seasons. However, it failed to detect leaks during the summer and winter due to high pavement temperatures and snow coverage. A more recent study evaluating the effectiveness of spectrometers, GPR, and IR as NDTs deduced that the IR camera was shown to be the most effective for pipeline leak detection [10]. A study [31] used medium- and high-resolution data from different satellites for the detection of water leakages in the \"Frenaros--Choirokoitia\" water pipe in Cyprus. The study applied two alternative methodologies. The first used a high-resolution QuickBird image to identify and verify'suspicious leaks' in a small area near the water pipes [31]. The second methodology involved using multi-temporal analysis using medium-resolution SPOT images. The analysis focused on regions around the joints of the pipe, using a 10-meter buffer zone [31]. This method recorded 10 possible leakage points along the 25-kilometer-long pipeline [31]. The effectiveness of this study could be enhanced if the images were taken of a larger area, displaying an entire WDN and not just a single pipeline. In addition, acquiring images at a high spatial resolution can increase the accuracy of leak detection along the pipeline. In this paper, an integrated approach of GIS and IR image processing was used to detect leakages in the WDN of Sharjah Electricity and Water Authority (SEWA). The objective of this paper is to develop a leak detection method using GIS and remote sensing. The aim of using this method is to enhance the efficiency of WDNs by increasing their accuracy in identifying leakages. This study creates a GIS-based customized system to identify potential leakage locations and deploys an IR camera to identify potential leak locations. The main contributions of this paper are as follows:  
* For potential locations of leak identification, we used GIS analysis methods, including buffer and intersection methods, using drops in water pressure, flow, and chlorine values.