This dataset contains georeferenced orthophotos collected daily along a 450 metre coastal stretch at Happisburgh, UK, over a time span of 9 months (April 6, 2019 to December 23, 2019). The dataset contains 190 colour images and 190 intensity images in GEOTIFF format. The orthophotos are produced by projection of LiDAR (Light Detection And Ranging) scans of the coastal stretch. There are 190 images out of a possible 262 days, since only days when scans were performed from two locations are included, which did not happen every day due to weather conditions. The orthophotos are point-cloud renders of the scan data created using ScanLAB's proprietary point-cloud rendering engine. The colour orthophotos are rendered using the colour information projected onto the scan during post-process colourisation. The intensity orthophotos are rendered using the intensity data for each scan. The orthophotos are rendered using an orthographic virtual camera which frames the useful extents of the scan data and is orientated such that the rendered orthophoto is "north-up". The orthophotos are georeferenced using pythons GDAL library and ground-truth GPS measurements taken at the two TLS positions onsite. The procedure for this follows; 1) the ground-truth GPS positions were converted from OSGB 1936 / British National Grid to Latitude and Longitude., 2) The pixel resolution of the orthophotos was calculated from the pixel position of the two TLS in the orthophotos and the two ground truth GPS positions., 3) The GPS position of the top left pixel of the orthophoto was calculated using pixel position of a TLS and the pixel resolution., 4) A python script using the GDAL library applied the GPS metadata to the orthophoto and saved it in GEOTIFF format. These data were collected to better understand the dynamic of beach-cliff and shore platform interaction along soft cliffed coasts. This research was funded by the UK Natural Environment Research Council (NE/M004996/1; BLUE-coast project). The on-location LiDAR Scanning and Technical R&D operated by ScanLAB Projects Ltd was funded by Innovate UK's Audience of the Future Program (Multiscale 3D Scanning with Framerate for TV and Immersive Applications project). The first 6 months of LiDAR scans (April to September 2019) were funded by Innovate UK, and this project was continued by the NERC BLUE-coast funding for the last 3 months (October to December 2019). The files were re-submitted and this DOI represents the second version of the data.