No abstract

The chalk cliffs of Normandy and Picardy are retreating rapidly and approaching the built-up areas located near the shore. Previous studies of cliff retreat in this area suffer from a large margin of error (absolute error in cliff position is ±7 m) due to the techniques and methods used. This paper presents a recent study which aims to quantify the chalk cliff retreat between 1966 and 1995 by means of photogrammetric analysis. In addition to the very high accuracy of the results (absolute error in cliff position is ±0.3 m), this technique gives geo-referenced numeric data allowing the creation of a geographical databank intended to become a tool for hazard management in coastal zones. Three scales of analysis have been used: a retreat value per hydro-sedimentary cell, per sub-cell and one every 50m. These scales show that this regressive dynamic is spatially very variable. However, three zones of distinct retreat rates are apparent. These appear to be linked with the lithological characteristics of the chalk. Furthermore, the quantification associated with the flint content of the cliff allows an assessment of the flint shingle provision from the cliff to the shore.

International audienceIntegrated in a wide research assessing destabilizing and triggering factors to model cliff dynamic along the Dieppe’s shoreline in High Normandy, this study aims at testing boat-based mobile LiDAR capabilities by scanning 3D point clouds of the unstable coastal cliffs. Two acquisition campaigns were performed in September 2012 and September 2013, scanning (1) a 30-km-long shoreline and (2) the same test cliffs in different environmental conditions and device settings. The potentials of collected data for 3D modelling, change detection and landslide monitoring were afterward assessed. By scanning during favourable meteorological and marine conditions and close to the coast, mobile LiDAR devices are able to quickly scan a long shoreline with median point spacing up to 10cm. The acquired data are then sufficiently detailed to map geomorphological features smaller than 0.5m 2. Furthermore, our capability to detect rockfalls and erosion deposits (>m 3) is confirmed, since using the classical approach of computing differences between sequential acquisitions reveals many cliff collapses between Pourville and Quiberville and only sparse changes between Dieppe and Belleville-sur-Mer. These different change rates result from different rockfall susceptibilities. Finally, we also confirmed the capability of the boat-based mobile LiDAR technique to monitor single large changes, characterizing the Dieppe landslide geometry with two main active scarps, retrogression up to 40m and about 100,000m 3 of eroded materials