CLASSIFICATION AND REPRESENTATION OF COMMONLY USED ROOFING MATERIAL USING MULTISENSORIAL AERIAL DATA
As more cities are starting to experience the urban heat islands effect, knowledge about the energy emitted from building roofs is of primary importance. Since this energy depends both on roof orientations and materials, we tackled both issues by analysing sensor data from multispectral, thermal inf...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2018-09-01
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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/XLII-1/217/2018/isprs-archives-XLII-1-217-2018.pdf |
| _version_ | 1828970175492259840 |
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| author | R. Ilehag R. Ilehag D. Bulatov D. Bulatov P. Helmholz D. Belton |
| author_facet | R. Ilehag R. Ilehag D. Bulatov D. Bulatov P. Helmholz D. Belton |
| author_sort | R. Ilehag |
| collection | DOAJ |
| description | As more cities are starting to experience the urban heat islands effect, knowledge about the energy emitted from building roofs is of primary importance. Since this energy depends both on roof orientations and materials, we tackled both issues by analysing sensor data from multispectral, thermal infrared, high-resolution RGB, and airborne laser datasets (each with different spatial resolutions) of a council in Perth, Australia. To localise the roofs, we acquired building outlines that had to be updated using the normalised digital surface model, the NDVI and the planarity. Then, we computed a semantic 3D model of the study area, with roof detail analysis being a particular focus. The main objective of this study, however, was to classify three commonly used roofing materials: <i>Cement tiles</i>, <i>Colorbond</i> and <i>Zincalume</i> by combining the multispectral and thermal infrared image bands while the high-resolution RGB dataset was used to provide additional information about the roof texture. Three types of image segmentation approaches were evaluated to assess any differences while performing the material classification; pixel-wise, superpixel-wise and building-wise image segmentation. Due to the limited amount of labelled data, we extended the dataset by labelling data ourselves and merged <i>Colorbond</i> and <i>Zincalume</i> into one separate class. The supervised classifier Random Forest was applied to all reasonable configurations of segmentation kinds, numbers of classes, and finally, keeping track of the added value of principal component analysis. |
| first_indexed | 2024-12-14T12:46:11Z |
| format | Article |
| id | doaj.art-6eac6ed42c4b490aab7766a7029f6a76 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-14T12:46:11Z |
| publishDate | 2018-09-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-6eac6ed42c4b490aab7766a7029f6a762022-12-21T23:00:47ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342018-09-01XLII-121722410.5194/isprs-archives-XLII-1-217-2018CLASSIFICATION AND REPRESENTATION OF COMMONLY USED ROOFING MATERIAL USING MULTISENSORIAL AERIAL DATAR. Ilehag0R. Ilehag1D. Bulatov2D. Bulatov3P. Helmholz4D. Belton5Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology, GermanyDepartment of Spatial Sciences, Curtin University, Perth, WA, AustraliaFraunhofer IOSB, Ettlingen, GermanyDepartment of Spatial Sciences, Curtin University, Perth, WA, AustraliaDepartment of Spatial Sciences, Curtin University, Perth, WA, AustraliaDepartment of Spatial Sciences, Curtin University, Perth, WA, AustraliaAs more cities are starting to experience the urban heat islands effect, knowledge about the energy emitted from building roofs is of primary importance. Since this energy depends both on roof orientations and materials, we tackled both issues by analysing sensor data from multispectral, thermal infrared, high-resolution RGB, and airborne laser datasets (each with different spatial resolutions) of a council in Perth, Australia. To localise the roofs, we acquired building outlines that had to be updated using the normalised digital surface model, the NDVI and the planarity. Then, we computed a semantic 3D model of the study area, with roof detail analysis being a particular focus. The main objective of this study, however, was to classify three commonly used roofing materials: <i>Cement tiles</i>, <i>Colorbond</i> and <i>Zincalume</i> by combining the multispectral and thermal infrared image bands while the high-resolution RGB dataset was used to provide additional information about the roof texture. Three types of image segmentation approaches were evaluated to assess any differences while performing the material classification; pixel-wise, superpixel-wise and building-wise image segmentation. Due to the limited amount of labelled data, we extended the dataset by labelling data ourselves and merged <i>Colorbond</i> and <i>Zincalume</i> into one separate class. The supervised classifier Random Forest was applied to all reasonable configurations of segmentation kinds, numbers of classes, and finally, keeping track of the added value of principal component analysis.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-1/217/2018/isprs-archives-XLII-1-217-2018.pdf |
| spellingShingle | R. Ilehag R. Ilehag D. Bulatov D. Bulatov P. Helmholz D. Belton CLASSIFICATION AND REPRESENTATION OF COMMONLY USED ROOFING MATERIAL USING MULTISENSORIAL AERIAL DATA The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | CLASSIFICATION AND REPRESENTATION OF COMMONLY USED ROOFING MATERIAL USING MULTISENSORIAL AERIAL DATA |
| title_full | CLASSIFICATION AND REPRESENTATION OF COMMONLY USED ROOFING MATERIAL USING MULTISENSORIAL AERIAL DATA |
| title_fullStr | CLASSIFICATION AND REPRESENTATION OF COMMONLY USED ROOFING MATERIAL USING MULTISENSORIAL AERIAL DATA |
| title_full_unstemmed | CLASSIFICATION AND REPRESENTATION OF COMMONLY USED ROOFING MATERIAL USING MULTISENSORIAL AERIAL DATA |
| title_short | CLASSIFICATION AND REPRESENTATION OF COMMONLY USED ROOFING MATERIAL USING MULTISENSORIAL AERIAL DATA |
| title_sort | classification and representation of commonly used roofing material using multisensorial aerial data |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-1/217/2018/isprs-archives-XLII-1-217-2018.pdf |
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