The undulating topography of the Auckland urban region is susceptible to landslides of varying process-mechanisms, including: (1) earthflows of saturated Pleistocene Tauranga Group sediments, tephra and residual soils flowing off more competent underlying rock; (2) rotational slumping of man-made fill or Tauranga Group sediments; (3) block-slides of weak Miocene Waitemata Group sedimentary rock, dipping out of slope. Such landslides are often triggered by intense short periods, or prolonged periods of rainfall, such as the 'Tasman Tempest' and ex-Tropical Cyclone Debbie storms of 2017. Typically, rainfall infiltration results in a rise of the groundwater table and an increase of the pore water pressure, causing a reduction in effective normal stress and thereby soil strength, leading to landslides. Such landslide risk is likely to be accentuated in the Auckland region in future given the projected population growth and planned urban and commercial expansion driving the Auckland Unitary Plan (AUP). Indeed, the AUP encourages greater intensification by rezoning many areas to allow construction of low-rise apartments. Therefore, monitoring slope stability in the Auckland region is important, and requires assessment of the extent, rate of displacement, surface topography, and detection of tension cracks developing from slope deformation. Here, we present some investigations of slope failure mechanisms and activity in the Auckland region using Unmanned Aerial Vehicles (UAV) and structure-from-motion (SfM) photogrammetry. UAVs are emerging as an effective tool in landslide hazard management, allowing rapid collection of imagery and production of high resolution photomosaics from which safe evaluation of landslide deformation and activity can be undertaken. In addition, digital terrain models (DTMs) can be developed, and these can potentially allow time-series DTM-differencing and/or comparison with LiDAR data in order to evaluate landslide activity. UAV-derived topographic data is also useful for 2D/3D slope profile construction which is important for accurate parameterization of numerical slope stability models. Thus, the UAV-SfM technique represents an effective, rapid, financially viable alternative to traditional topographic surveying and LiDAR.