Mapping dyke and dyke-related fractures is important for magma propagation and emplacement mechanisms analysis. Here, we propose a semi-automatic workflow for dyke and fracture mapping using unmanned aerial vehicle (UAV)-based photogrammetric data. Our workflow integrates mean-shift and GrabCut in one cut (GCOC) algorithms to segment dykes, and harnesses the phase symmetry algorithm and a series of follow-up actions to detect fractures. Sijiao Island of Zhejiang Province (SE China) is examined as a case study to validate the approaches. With our workflow, the generated dyke map attains more than a 97% recall rate when compared with the results of expert interpretation, and the ratio of the number of detected false fracture segments to the number of total segments is less than 18%. The dyke strike and fracture strike calculation match well with field measurements. Moreover, by combining visual interpretation and the resulting geometric information, our results manifest that dyke magma invaded along pre-existing fractures to form dykes on Sijiao Island, and the difference between dyke fractures and host rock fractures may be because of the effect of major changes of regional stress. This workflow has great potential for high-resolution terrestrial mapping.
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