# Drone SAR Imaging for Monitoring an Active Landslide Adjacent to the M25 at Flint Hall Farm
###### Abstract  
Flint Hall Farm in Godstone, Surrey, UK, is situated adjacent to the London Orbital Motorway, or M25, and contains several landslide systems which pose a significant geohazard risk to this critical infrastructure. The site has been routinely monitored by geotechnical engineers following a landslide that encroached onto the hard shoulder in December 2000; current in situ instrumentation includes inclinometers and piezoelectric sensors. Interferometric Synthetic Aperture Radar (InSAR) is an active remote sensing technique that can quantify millimetric rates of Earth surface and structural deformation, typically utilising satellite data, and is ideal for monitoring landslide movements. We have developed the hardware and software for an Unmanned Aerial Vehicle (UAV), or drone radar system, for improved operational flexibility and spatial-temporal resolutions in the InSAR data. The hardware payload includes an industrial-grade DJI drone, a high-performance Ettus Software Defined Radar (SDR), and custom Copper Clad Laminate (CCL) radar horn antennas. The software utilises Frequency Modulated Continuous Wave (FMCW) radar at 5.4 GHz for raw data collection and a Range Migration Algorithm (RMA) for focusing the data into a Single Look Complex (SLC) Synthetic Aperture Radar (SAR) image. We present the first SAR image acquired using the drone radar system at Flint Hall Farm, which provides an improved spatial resolution compared to satellite SAR. Discrete targets on the landslide slope, such as corner reflectors and the in situ instrumentation, are visible as bright pixels, with their size and positioning as expected; the surrounding grass and vegetation appear as natural speckles. Drone SAR imaging is an emerging field of research, given the necessary and recent technological advancements in drones and SDR processing power; as such, this is a novel achievement, with few authors demonstrating similar systems. Ongoing and future work includes repeat-pass SAR data collection and developing the InSAR processing chain for drone SAR data to provide meaningful deformation outputs for the landslides and other geotechnical hazards and infrastructure. d rone; Interferometric Synthetic Aperture Radar (InSAR); landslide; M25; motorway; radar; remote sensing; Synthetic Aperture Radar (SAR); transportation; Unmanned Aerial Vehicle (UAV) 2024  
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[PERSON], M.  
(radar) satellites and their Synthetic Aperture Radar (SAR) data products. InSAR exploits the phase change between multiple SAR acquisitions of the target area to quantify earth surface and structural deformation to a millimetric scale [2]. InSAR has frequently been applied to the monitoring and prediction of slope geohazards, including landslides and landslides [3; 4; 5; 6]. Using Sentinel-l data, [PERSON] et al. [7] identified increasing trends of slope displacement at an open-pit mine, a natural rock slope, and a tailings dam embankment, which can inform early-warning prediction models. [PERSON] et al. [8] used Envisat data and the Small BASeline Subset (SBAS) InSAR technique to identify two landslides in the Three Gorges region in China, with deformation rates up to 15 mm/yr, and seasonal landslide movements attributed to changes in the water level. InSAR has also been applied to the monitoring of road and motorway infrastructure exposed to landslides. [PERSON] et al. [9] utilised Persistent Scatterer Interferometry (PSI) and visual data to identify and monitor 235 new slow-moving landslides across the complex and mountainous road network of Crete, Greece. [PERSON] et al. [10] used InSAR to identify 236 potential landslides along the Shanghai-Nyalam Road in China, including slow-sliding rockslides, debris flows and debris avalanches. These studies demonstrate the regional scale at which satellite InSAR may be applied whilst providing millimetric rates of surface deformation. The resultant landslide inventories may inform road maintenance and hazard mitigation procedures.