English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

. Current research questions in the field of geomorphology focus on the impactof climate change on several processes subsequently causing natural hazards.Geodetic deformation measurements are a suitable tool to document suchgeomorphic mechanisms, e.g. by capturing a region of interest withterrestrial laser scanners which results in a so-called 3-D point cloud. Themain problem in deformation monitoring is the transformation of 3-D pointclouds captured at different points in time (epochs) into a stable referencecoordinate system. In this contribution, a surface-based registrationmethodology is applied, termed the iterative closest proximity algorithm(ICProx), that solely uses point cloud data as input, similar to theiterative closest point algorithm (ICP). The aim of this study is toautomatically classify deformations that occurred at a rock glacier and anice glacier, as well as in a rockfall area. For every case study, two epochswere processed, while the datasets notably differ in terms of geometriccharacteristics, distribution and magnitude of deformation. In summary, theICProx algorithm's classification accuracy is 70 % on average incomparison to reference data.

Identification of stable areas in unreferenced laser scans for automated geomorphometric monitoring