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The automatic extraction of information content from remotely sensed data is always challenging. We suggest a novel fusion approach to improve the extraction of this information from mono-satellite images. A Worldview-2 (WV-2) pan-sharpened image and a 1/5000-scaled topographic vector map (TOPO5000) were used as the sample data. Firstly, the buildings and roads were manually extracted from WV-2 to point out the maximum extractable information content. Subsequently, object-based automatic extractions were performed. After achieving two-dimensional results, a normalized digital surface model (nDSM) was generated from the underlying digital aerial photos of TOPO5000, and the automatic extraction was repeated by fusion with the nDSM to include individual object heights as an additional band for classification. The contribution was tested by precision, completeness and overall quality. Novel fusion technique increased the success of automatic extraction by 7% for the number of buildings and by 23% for the length of roads. © 2017, © 2017 Informa UK Limited, trading as Taylor & Francis Group.
| Yazar |
Sefercik U.G. Karakis S. Atalay C. Yigit I. Gokmen U. |
| Yayın Türü | Article |
| Tek Biçim Adres | https://hdl.handle.net/20.500.12628/6785 |
| Konu Başlıkları |
Automatic object extraction
fusion normalized digital surface model Wallis filtering worldview-2 |
| Koleksiyonlar |
Araştırma Çıktıları | WoS | Scopus | TR-Dizin | PubMed | SOBİAD Scopus İndeksli Yayınlar Koleksiyonu WoS İndeksli Yayınlar Koleksiyonu |
| Dergi Adı | Geocarto International |
| Dergi Cilt Bilgisi | 33 |
| Dergi Sayısı | 10 |
| Sayfalar | 1139 - 1154 |
| Yayın Yılı | 2018 |
| Eser Adı [dc.title] | Novel fusion approach on automatic object extraction from spatial data: case study Worldview-2 and TOPO5000 |
| Yazar [dc.contributor.author] | Sefercik U.G. |
| Yazar [dc.contributor.author] | Karakis S. |
| Yazar [dc.contributor.author] | Atalay C. |
| Yazar [dc.contributor.author] | Yigit I. |
| Yazar [dc.contributor.author] | Gokmen U. |
| Yayın Yılı [dc.date.issued] | 2018 |
| Yayıncı [dc.publisher] | Taylor and Francis Ltd. |
| Yayın Türü [dc.type] | article |
| Özet [dc.description.abstract] | The automatic extraction of information content from remotely sensed data is always challenging. We suggest a novel fusion approach to improve the extraction of this information from mono-satellite images. A Worldview-2 (WV-2) pan-sharpened image and a 1/5000-scaled topographic vector map (TOPO5000) were used as the sample data. Firstly, the buildings and roads were manually extracted from WV-2 to point out the maximum extractable information content. Subsequently, object-based automatic extractions were performed. After achieving two-dimensional results, a normalized digital surface model (nDSM) was generated from the underlying digital aerial photos of TOPO5000, and the automatic extraction was repeated by fusion with the nDSM to include individual object heights as an additional band for classification. The contribution was tested by precision, completeness and overall quality. Novel fusion technique increased the success of automatic extraction by 7% for the number of buildings and by 23% for the length of roads. © 2017, © 2017 Informa UK Limited, trading as Taylor & Francis Group. |
| Kayıt Giriş Tarihi [dc.date.accessioned] | 2019-12-23 |
| Açık Erişim Tarihi [dc.date.available] | 2019-12-23 |
| Yayın Dili [dc.language.iso] | eng |
| Konu Başlıkları [dc.subject] | Automatic object extraction |
| Konu Başlıkları [dc.subject] | fusion |
| Konu Başlıkları [dc.subject] | normalized digital surface model |
| Konu Başlıkları [dc.subject] | Wallis filtering |
| Konu Başlıkları [dc.subject] | worldview-2 |
| Haklar [dc.rights] | info:eu-repo/semantics/closedAccess |
| ISSN [dc.identifier.issn] | 1010-6049 |
| İlk Sayfa Sayısı [dc.identifier.startpage] | 1139 |
| Son Sayfa Sayısı [dc.identifier.endpage] | 1154 |
| Dergi Adı [dc.relation.journal] | Geocarto International |
| Dergi Sayısı [dc.identifier.issue] | 10 |
| Dergi Cilt Bilgisi [dc.identifier.volume] | 33 |
| Tek Biçim Adres [dc.identifier.uri] | https://dx.doi.org/10.1080/10106049.2017.1353646 |
| Tek Biçim Adres [dc.identifier.uri] | https://hdl.handle.net/20.500.12628/6785 |