THE CHALLENGE OF AUTOMATION FOR LARGE SCALE TOPOGRAPHIC MAPPING OF OIL AND GAS DEPOSITS BASED ON TERRESTRIAL LASER SCANNING DATA
Terrestrial laser scanning (TLS) is a modern method of spatial data acquisition. The most common application of this method is large scale topographic mapping. Point clouds obtained with laser scanning contain all necessary data for producing topographic maps and plans. One of the territories, where...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2022-05-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2022/161/2022/isprs-archives-XLIII-B2-2022-161-2022.pdf |
| _version_ | 1818208096871251968 |
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| author | M. A. Altyntsev M. A. Altyntseva |
| author_facet | M. A. Altyntsev M. A. Altyntseva |
| author_sort | M. A. Altyntsev |
| collection | DOAJ |
| description | Terrestrial laser scanning (TLS) is a modern method of spatial data acquisition. The most common application of this method is large scale topographic mapping. Point clouds obtained with laser scanning contain all necessary data for producing topographic maps and plans. One of the territories, where TLS is particularly important, is oil and gas deposits. Built-up areas of oil and gas deposits are represented with complicated industrial objects. On the one hand, introduction of TLS method for surveying of these areas significantly speeds up field surveying works. On the other hand, dense point clouds of built-up areas slow down the process of mapping due to the necessity to filter extra data. To hasten the process of mapping special algorithms of feature extraction from point cloud and techniques of compiling plan and maps are being developed. Nonetheless, majority of developed algorithms can work fine for point clouds of high uniform density where the number of objects is not large. For built-up areas developed algorithms can be not applicable. The basic steps of compiling a topographic plan are described. It is discussed which object types can be automatically extracted and vectorized in built-up areas of oil and gas deposits. The examples of manual point cloud vectorization are given. |
| first_indexed | 2024-12-12T04:39:23Z |
| format | Article |
| id | doaj.art-315a81bd04924345ad20f3a0420cb609 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-12T04:39:23Z |
| publishDate | 2022-05-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-315a81bd04924345ad20f3a0420cb6092022-12-22T00:37:51ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342022-05-01XLIII-B2-202216116710.5194/isprs-archives-XLIII-B2-2022-161-2022THE CHALLENGE OF AUTOMATION FOR LARGE SCALE TOPOGRAPHIC MAPPING OF OIL AND GAS DEPOSITS BASED ON TERRESTRIAL LASER SCANNING DATAM. A. Altyntsev0M. A. Altyntseva1Dep. of Engineering Geodesy and Mine Surveying, Siberian State University of Geosystems and Technologies, Novosibirsk, Russian FederationDept. of Cartography and Geoinformation, Siberian State University of Geosystems and Technologies, Novosibirsk, Russian FederationTerrestrial laser scanning (TLS) is a modern method of spatial data acquisition. The most common application of this method is large scale topographic mapping. Point clouds obtained with laser scanning contain all necessary data for producing topographic maps and plans. One of the territories, where TLS is particularly important, is oil and gas deposits. Built-up areas of oil and gas deposits are represented with complicated industrial objects. On the one hand, introduction of TLS method for surveying of these areas significantly speeds up field surveying works. On the other hand, dense point clouds of built-up areas slow down the process of mapping due to the necessity to filter extra data. To hasten the process of mapping special algorithms of feature extraction from point cloud and techniques of compiling plan and maps are being developed. Nonetheless, majority of developed algorithms can work fine for point clouds of high uniform density where the number of objects is not large. For built-up areas developed algorithms can be not applicable. The basic steps of compiling a topographic plan are described. It is discussed which object types can be automatically extracted and vectorized in built-up areas of oil and gas deposits. The examples of manual point cloud vectorization are given.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2022/161/2022/isprs-archives-XLIII-B2-2022-161-2022.pdf |
| spellingShingle | M. A. Altyntsev M. A. Altyntseva THE CHALLENGE OF AUTOMATION FOR LARGE SCALE TOPOGRAPHIC MAPPING OF OIL AND GAS DEPOSITS BASED ON TERRESTRIAL LASER SCANNING DATA The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | THE CHALLENGE OF AUTOMATION FOR LARGE SCALE TOPOGRAPHIC MAPPING OF OIL AND GAS DEPOSITS BASED ON TERRESTRIAL LASER SCANNING DATA |
| title_full | THE CHALLENGE OF AUTOMATION FOR LARGE SCALE TOPOGRAPHIC MAPPING OF OIL AND GAS DEPOSITS BASED ON TERRESTRIAL LASER SCANNING DATA |
| title_fullStr | THE CHALLENGE OF AUTOMATION FOR LARGE SCALE TOPOGRAPHIC MAPPING OF OIL AND GAS DEPOSITS BASED ON TERRESTRIAL LASER SCANNING DATA |
| title_full_unstemmed | THE CHALLENGE OF AUTOMATION FOR LARGE SCALE TOPOGRAPHIC MAPPING OF OIL AND GAS DEPOSITS BASED ON TERRESTRIAL LASER SCANNING DATA |
| title_short | THE CHALLENGE OF AUTOMATION FOR LARGE SCALE TOPOGRAPHIC MAPPING OF OIL AND GAS DEPOSITS BASED ON TERRESTRIAL LASER SCANNING DATA |
| title_sort | challenge of automation for large scale topographic mapping of oil and gas deposits based on terrestrial laser scanning data |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2022/161/2022/isprs-archives-XLIII-B2-2022-161-2022.pdf |
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