Farr JA, Morgenstern R, de Vilder SJ. 2022. Measuring coastal cliff change using Remotely Piloted Aircraft System (RPAS)-mounted Light Detection And Ranging (LiDAR) technology. Lower Hutt (NZ): GNS Science. 63 p. (GNS Science report; 2022/18). doi:10.21420/VH4G-B402.
Abstract
Capture of accurate, quantifiable and repeatable data – typically ‘point clouds’ and their derivative products, such as topographic surfaces – are needed to monitor coastal cliff retreat. Currently, rates of coastal cliff change are often spatially and temporally averaged. The purpose of this report is to demonstrate how Remotely Piloted Aircraft System (RPAS)-mounted Light Detection And Ranging (LiDAR) can be used to capture these data and how the data can be processed to create topographic surface models that can be used by scientists and non-professionals alike. The aim of this report is to develop methodologies and workflows for: (1) capturing and processing RPAS-mounted LiDAR data; (2) using the processed data to create surface models; (3) creating change models by comparing the surface models from multiple RPAS-mounted LiDAR surveys captured at different times ‘epochs’; and (4) utilising the change models to calculate the locations and volumes of the changes, as well as the magnitude-frequency of such volume changes. These methods and workflows were then tested and further developed by applying them to a 1.1 km section of coastal cliff at Cape Kidnappers, Hawkes Bay. In addition to this work, we also compared the surface models developed from RPAS-mounted LiDAR with those developed from other survey techniques, including Airborne Laser Scanning (ALS), Terrestrial Laser Scanning (TLS) and RPAS-mounted photogrammetry. Cape Kidnappers in Hawkes Bay was selected as the site to test and further develop the workflows, as many cliff collapses have occurred from these cliffs and people have been hit and injured by debris falling from these cliffs. The walk along the beach below the cliffs is famous, as it allows access to a Gannet colony, which many thousands of people a year visit. Hastings District Council (HDC) and the Department of Conservation (DOC) are responsible for managing the cliff collapse hazards, and other hazards, along the beach, and the risk such hazards pose to people. This report will be presented to both HDC and DOC upon completion. Methodology of how to capture and process RPAS-mounted LiDAR data is discussed, as well as how the data can be processed to present change models, volume changes and magnitude-frequency graphs. Two lines were flown in parallel to the cliff face at 7.5 m/s; this was determined as the most effective way to gain coverage with both RPAS-mounted LiDAR and imagery. The data were ‘cleaned’ by removing data artifacts and removing vegetation to produce a ground model; this was done using Leica Cyclone 3DR. Surface models were created from these ground models, and change analyses were completed between the two data epochs. One change model shows overall change (using Leica Cyclone 3DR) and one shows individual rockfall events (using the Rockfall Activity Morphological Bigdata Optimiser [Rambo]). RPAS height and speed tests were completed on site to confirm the manufacturer’s specifications, and results were tabulated. Sensitivity analyses were tested to establish the best settings to use in Rambo for this project, and it was determined that this may be necessary to do with all future locations where Rambo is used. Advantages over other remote-sensing techniques, such as RPAS-based photogrammetry, ALS and TLS are explained, as well as what limitations come with RPAS-mounted LiDAR. It is concluded that RPAS-mounted LiDAR is the superior solution for medium-scale (between 0.1 and 5 km2) sites with complex topography, due to the coverage and point density achieved and the speed at which data can be captured. (The authors)
