Object-Based High-Rise Building Detection Using Morphological Building Index and Digital Map
High-rise buildings (HRBs) as modern and visually unique land use continue to increase due to urbanization. Therefore, large-scale monitoring of HRB is very important for urban planning and environmental protection. This paper performed object-based HRB detection using high-resolution satellite imag...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/14/2/330 |
| _version_ | 1797490690600468480 |
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| author | Sejung Jung Kirim Lee Won Hee Lee |
| author_facet | Sejung Jung Kirim Lee Won Hee Lee |
| author_sort | Sejung Jung |
| collection | DOAJ |
| description | High-rise buildings (HRBs) as modern and visually unique land use continue to increase due to urbanization. Therefore, large-scale monitoring of HRB is very important for urban planning and environmental protection. This paper performed object-based HRB detection using high-resolution satellite image and digital map. Three study areas were acquired from KOMPSAT-3A, KOMPSAT-3, and WorldView-3, and object-based HRB detection was performed using the direction according to relief displacement by satellite image. Object-based multiresolution segmentation images were generated, focusing on HRB in each satellite image, and then combined with pixel-based building detection results obtained from MBI through majority voting to derive object-based building detection results. After that, to remove objects misdetected by HRB, the direction between HRB in the polygon layer of the digital map HRB and the HRB in the object-based building detection result was calculated. It was confirmed that the direction between the two calculated using the centroid coordinates of each building object converged with the azimuth angle of the satellite image, and results outside the error range were removed from the object-based HRB results. The HRBs in satellite images were defined as reference data, and the performance of the results obtained through the proposed method was analyzed. In addition, to evaluate the efficiency of the proposed technique, it was confirmed that the proposed method provides relatively good performance compared to the results of object-based HRB detection using shadows. |
| first_indexed | 2024-03-10T00:36:39Z |
| format | Article |
| id | doaj.art-aaaa1dd6a47a4ad0b305e6c1048069ea |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T00:36:39Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-aaaa1dd6a47a4ad0b305e6c1048069ea2023-11-23T15:15:57ZengMDPI AGRemote Sensing2072-42922022-01-0114233010.3390/rs14020330Object-Based High-Rise Building Detection Using Morphological Building Index and Digital MapSejung Jung0Kirim Lee1Won Hee Lee2Department of Convergence and Fusion System Engineering, Kyungpook National University, Sangju 37224, KoreaDepartment of Spatial Information, Kyungpook National University, Daegu 41566, KoreaDepartment of Convergence and Fusion System Engineering, Kyungpook National University, Sangju 37224, KoreaHigh-rise buildings (HRBs) as modern and visually unique land use continue to increase due to urbanization. Therefore, large-scale monitoring of HRB is very important for urban planning and environmental protection. This paper performed object-based HRB detection using high-resolution satellite image and digital map. Three study areas were acquired from KOMPSAT-3A, KOMPSAT-3, and WorldView-3, and object-based HRB detection was performed using the direction according to relief displacement by satellite image. Object-based multiresolution segmentation images were generated, focusing on HRB in each satellite image, and then combined with pixel-based building detection results obtained from MBI through majority voting to derive object-based building detection results. After that, to remove objects misdetected by HRB, the direction between HRB in the polygon layer of the digital map HRB and the HRB in the object-based building detection result was calculated. It was confirmed that the direction between the two calculated using the centroid coordinates of each building object converged with the azimuth angle of the satellite image, and results outside the error range were removed from the object-based HRB results. The HRBs in satellite images were defined as reference data, and the performance of the results obtained through the proposed method was analyzed. In addition, to evaluate the efficiency of the proposed technique, it was confirmed that the proposed method provides relatively good performance compared to the results of object-based HRB detection using shadows.https://www.mdpi.com/2072-4292/14/2/330object-based high-rise building detectionmorphological building indexdigital mapazimuth angle |
| spellingShingle | Sejung Jung Kirim Lee Won Hee Lee Object-Based High-Rise Building Detection Using Morphological Building Index and Digital Map Remote Sensing object-based high-rise building detection morphological building index digital map azimuth angle |
| title | Object-Based High-Rise Building Detection Using Morphological Building Index and Digital Map |
| title_full | Object-Based High-Rise Building Detection Using Morphological Building Index and Digital Map |
| title_fullStr | Object-Based High-Rise Building Detection Using Morphological Building Index and Digital Map |
| title_full_unstemmed | Object-Based High-Rise Building Detection Using Morphological Building Index and Digital Map |
| title_short | Object-Based High-Rise Building Detection Using Morphological Building Index and Digital Map |
| title_sort | object based high rise building detection using morphological building index and digital map |
| topic | object-based high-rise building detection morphological building index digital map azimuth angle |
| url | https://www.mdpi.com/2072-4292/14/2/330 |
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