Estimating the volume of the 1978 Rissa quick clay landslide in Central Norway using historical aerial imagery
Quick clay is found across Scandinavia and is especially prominent in south-eastern and central Norway. Quick clay is prone to failure and can cause landslides with high velocities and large run-outs. The 1978 Rissa landslide is one of the best-known quick clay landslides to have occurred in the las...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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De Gruyter
2022-03-01
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| Series: | Open Geosciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/geo-2020-0331 |
| _version_ | 1811203723510153216 |
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| author | Robson Benjamin Aubrey Hölbling Daniel Nielsen Pål Ringkjøb Koller Max |
| author_facet | Robson Benjamin Aubrey Hölbling Daniel Nielsen Pål Ringkjøb Koller Max |
| author_sort | Robson Benjamin Aubrey |
| collection | DOAJ |
| description | Quick clay is found across Scandinavia and is especially prominent in south-eastern and central Norway. Quick clay is prone to failure and can cause landslides with high velocities and large run-outs. The 1978 Rissa landslide is one of the best-known quick clay landslides to have occurred in the last century, both due to its size and the fact that it was captured on film. In this article, we utilise Structure from Motion Multi-View Stereo (SfM-MVS) photogrammetry to process historical aerial photography from 1964 to 1978 and derive the first geodetic volume of the Rissa landslide. We found that the landslide covered a total onshore area of 0.36 km2 and had a geodetic volume of 2.53 ± 0.52 × 106 m3 with up to 20 m of surface elevation changes. Our estimate differs profusely from previous estimates by 43–56% which can partly be accounted for our analysis not being able to measure the portion of the landslide that occurred underwater, nor account for the material deposited within the landslide area. Given the accuracy and precision of our analyses, we believe that the total volume of the Rissa landslide may have been less than originally reported. The use of modern image processing techniques such as SfM-MVS for processing historical aerial photography is recommended for understanding landscape changes related to landslides, volcanoes, glaciers, or river erosion over large spatial and temporal scales. |
| first_indexed | 2024-04-12T03:01:00Z |
| format | Article |
| id | doaj.art-9afacb60eef04be7825b14c9c0d91a24 |
| institution | Directory Open Access Journal |
| issn | 2391-5447 |
| language | English |
| last_indexed | 2024-04-12T03:01:00Z |
| publishDate | 2022-03-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Open Geosciences |
| spelling | doaj.art-9afacb60eef04be7825b14c9c0d91a242022-12-22T03:50:41ZengDe GruyterOpen Geosciences2391-54472022-03-0114125226310.1515/geo-2020-0331Estimating the volume of the 1978 Rissa quick clay landslide in Central Norway using historical aerial imageryRobson Benjamin Aubrey0Hölbling Daniel1Nielsen Pål Ringkjøb2Koller Max3Department of Earth Science, University of Bergen, Allégaten 41, Bergen 5007, NorwayDepartment of Geoinformatics - Z_GIS, University of Salzburg, Schillerstrasse 30, 5020 Salzburg, AustriaDepartment of Geography, University of Bergen, Fosswinckelsgate 6, Bergen 5007, NorwayDepartment of Geography, University of Bergen, Fosswinckelsgate 6, Bergen 5007, NorwayQuick clay is found across Scandinavia and is especially prominent in south-eastern and central Norway. Quick clay is prone to failure and can cause landslides with high velocities and large run-outs. The 1978 Rissa landslide is one of the best-known quick clay landslides to have occurred in the last century, both due to its size and the fact that it was captured on film. In this article, we utilise Structure from Motion Multi-View Stereo (SfM-MVS) photogrammetry to process historical aerial photography from 1964 to 1978 and derive the first geodetic volume of the Rissa landslide. We found that the landslide covered a total onshore area of 0.36 km2 and had a geodetic volume of 2.53 ± 0.52 × 106 m3 with up to 20 m of surface elevation changes. Our estimate differs profusely from previous estimates by 43–56% which can partly be accounted for our analysis not being able to measure the portion of the landslide that occurred underwater, nor account for the material deposited within the landslide area. Given the accuracy and precision of our analyses, we believe that the total volume of the Rissa landslide may have been less than originally reported. The use of modern image processing techniques such as SfM-MVS for processing historical aerial photography is recommended for understanding landscape changes related to landslides, volcanoes, glaciers, or river erosion over large spatial and temporal scales.https://doi.org/10.1515/geo-2020-0331quick clay landslidehistorical aerial imagesstructure from motiondemvolume estimationnorway |
| spellingShingle | Robson Benjamin Aubrey Hölbling Daniel Nielsen Pål Ringkjøb Koller Max Estimating the volume of the 1978 Rissa quick clay landslide in Central Norway using historical aerial imagery Open Geosciences quick clay landslide historical aerial images structure from motion dem volume estimation norway |
| title | Estimating the volume of the 1978 Rissa quick clay landslide in Central Norway using historical aerial imagery |
| title_full | Estimating the volume of the 1978 Rissa quick clay landslide in Central Norway using historical aerial imagery |
| title_fullStr | Estimating the volume of the 1978 Rissa quick clay landslide in Central Norway using historical aerial imagery |
| title_full_unstemmed | Estimating the volume of the 1978 Rissa quick clay landslide in Central Norway using historical aerial imagery |
| title_short | Estimating the volume of the 1978 Rissa quick clay landslide in Central Norway using historical aerial imagery |
| title_sort | estimating the volume of the 1978 rissa quick clay landslide in central norway using historical aerial imagery |
| topic | quick clay landslide historical aerial images structure from motion dem volume estimation norway |
| url | https://doi.org/10.1515/geo-2020-0331 |
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