New approach for photogrammetric rock slope premonitory movements monitoring
An automated, fixed-location, continuous time-lapse camera system was developed to analyze the existence of rockfall precursory movements and quantify volume changes after detachments. It was implemented to monitor the basaltic formation on which Castellfollit de la Roca village is built. Due to the...
| Autores: | , , , , |
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| Formato: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/384480 |
| Acesso em linha: | https://hdl.handle.net/2117/384480 https://dx.doi.org/10.3390/rs15020293 |
| Access Level: | acceso abierto |
| Palavra-chave: | Photogrammetry Landslide hazard analysis Rock Rockfall Time-lapse photogrammetry Monitoring Automation Castellfollit de la Roca (Girona Spain) Fotogrametria Risc d'esllavissades Roca Àrees temàtiques de la UPC::Enginyeria civil::Geomàtica |
| Resumo: | An automated, fixed-location, continuous time-lapse camera system was developed to analyze the existence of rockfall precursory movements and quantify volume changes after detachments. It was implemented to monitor the basaltic formation on which Castellfollit de la Roca village is built. Due to the geometrical conditions of the area, the camera system consists of three digital cameras managed by a control unit that contains a Raspberry Pi 4 microprocessor. Images taken every day are sent to a server for processing. A workflow has been developed to work with a set of images with an irregular time interval to detect precursor movement. The first step consists of matching the images with a reference master image and filtering the vegetation to improve the process using a mask obtained by a green leaf index (GLI) index. Then, the adjusted images are used for a forward-backward correlation process carried out to detect movements. If movement is detected, a 3D model is built using structure from motion (SfM) to quantify the movements. The system has been working since September 2021. During this period, movements from 0.01 to 0.5 m and several rockfalls of a small volume have been detected |
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