Evaluating Thermal Attribute Mapping Strategies for Oblique Airborne Photogrammetric System AOS-Tx8
Thermal imagery is widely used in various fields of remote sensing. In this study, a novel processing scheme is developed to process the data acquired by the oblique airborne photogrammetric system AOS-Tx8 consisting of four thermal cameras and four RGB cameras with the goal of large-scale area ther...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-12-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/12/1/112 |
| _version_ | 1818960580050944000 |
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| author | Dong Lin Lutz Bannehr Christoph Ulrich Hans-Gerd Maas |
| author_facet | Dong Lin Lutz Bannehr Christoph Ulrich Hans-Gerd Maas |
| author_sort | Dong Lin |
| collection | DOAJ |
| description | Thermal imagery is widely used in various fields of remote sensing. In this study, a novel processing scheme is developed to process the data acquired by the oblique airborne photogrammetric system AOS-Tx8 consisting of four thermal cameras and four RGB cameras with the goal of large-scale area thermal attribute mapping. In order to merge 3D RGB data and 3D thermal data, registration is conducted in four steps: First, thermal and RGB point clouds are generated independently by applying structure from motion (SfM) photogrammetry to both the thermal and RGB imagery. Next, a coarse point cloud registration is performed by the support of georeferencing data (global positioning system, GPS). Subsequently, a fine point cloud registration is conducted by octree-based iterative closest point (ICP). Finally, three different texture mapping strategies are compared. Experimental results showed that the global image pose refinement outperforms the other two strategies at registration accuracy between thermal imagery and RGB point cloud. Potential building thermal leakages in large areas can be fast detected in the generated texture mapping results. Furthermore, a combination of the proposed workflow and the oblique airborne system allows for a detailed thermal analysis of building roofs and facades. |
| first_indexed | 2024-12-20T11:59:47Z |
| format | Article |
| id | doaj.art-ebd866e4e6754fce9b462839f2d43a91 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-20T11:59:47Z |
| publishDate | 2019-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-ebd866e4e6754fce9b462839f2d43a912022-12-21T19:41:34ZengMDPI AGRemote Sensing2072-42922019-12-0112111210.3390/rs12010112rs12010112Evaluating Thermal Attribute Mapping Strategies for Oblique Airborne Photogrammetric System AOS-Tx8Dong Lin0Lutz Bannehr1Christoph Ulrich2Hans-Gerd Maas3Institute of Photogrammetry and Remote Sensing, Technische Universität Dresden, 01069 Dresden, GermanyInstitute of Geoinformation and Surveying, Hochschule Anhalt, 06846 Dessau-Roßlau, GermanyInstitute of Geoinformation and Surveying, Hochschule Anhalt, 06846 Dessau-Roßlau, GermanyInstitute of Photogrammetry and Remote Sensing, Technische Universität Dresden, 01069 Dresden, GermanyThermal imagery is widely used in various fields of remote sensing. In this study, a novel processing scheme is developed to process the data acquired by the oblique airborne photogrammetric system AOS-Tx8 consisting of four thermal cameras and four RGB cameras with the goal of large-scale area thermal attribute mapping. In order to merge 3D RGB data and 3D thermal data, registration is conducted in four steps: First, thermal and RGB point clouds are generated independently by applying structure from motion (SfM) photogrammetry to both the thermal and RGB imagery. Next, a coarse point cloud registration is performed by the support of georeferencing data (global positioning system, GPS). Subsequently, a fine point cloud registration is conducted by octree-based iterative closest point (ICP). Finally, three different texture mapping strategies are compared. Experimental results showed that the global image pose refinement outperforms the other two strategies at registration accuracy between thermal imagery and RGB point cloud. Potential building thermal leakages in large areas can be fast detected in the generated texture mapping results. Furthermore, a combination of the proposed workflow and the oblique airborne system allows for a detailed thermal analysis of building roofs and facades.https://www.mdpi.com/2072-4292/12/1/112oblique airbornethermalrgbpoint cloudregistrationmapping |
| spellingShingle | Dong Lin Lutz Bannehr Christoph Ulrich Hans-Gerd Maas Evaluating Thermal Attribute Mapping Strategies for Oblique Airborne Photogrammetric System AOS-Tx8 Remote Sensing oblique airborne thermal rgb point cloud registration mapping |
| title | Evaluating Thermal Attribute Mapping Strategies for Oblique Airborne Photogrammetric System AOS-Tx8 |
| title_full | Evaluating Thermal Attribute Mapping Strategies for Oblique Airborne Photogrammetric System AOS-Tx8 |
| title_fullStr | Evaluating Thermal Attribute Mapping Strategies for Oblique Airborne Photogrammetric System AOS-Tx8 |
| title_full_unstemmed | Evaluating Thermal Attribute Mapping Strategies for Oblique Airborne Photogrammetric System AOS-Tx8 |
| title_short | Evaluating Thermal Attribute Mapping Strategies for Oblique Airborne Photogrammetric System AOS-Tx8 |
| title_sort | evaluating thermal attribute mapping strategies for oblique airborne photogrammetric system aos tx8 |
| topic | oblique airborne thermal rgb point cloud registration mapping |
| url | https://www.mdpi.com/2072-4292/12/1/112 |
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