The effect of different areas and image band in the road extraction from high-resolution uav images using the Obia method
- Görüntülenme 13
- İndirme 0
-
Google Akademik
-
DOI

| Yazarlar | Yiğit, Abdurahman Yasin |
| Kurum Dışı Yazarlar | Uysal, Murat |
| Tek Biçim Adres (URI) | https://hdl.handle.net/20.500.14114/9069 |
| Yayın Türü | Makale |
| Yayın Yılı | 2026 |
| DOI Adresi | https://doi.org/10.1007/s12518-025-00678-8 |
| Yayıncı | Springer Nature |
| Dergi Adı | Applied Geomatics |
| Konu Başlıkları | Cartography Computer Vision Object Recognition Object vision Remote Sensing/Photogrammetry Shape Analysis |
| İndekslenen Platformlar | Web of Science |
This study semi-automatically detects road lines using object-based classification methods from orthophoto produced from UAV images. Three studies were carried out on images with visible and infrared wavelengths. The study's major aim is to examine the effect of spectral bands and different areas on classification accuracy. First, orthophotos were produced from UAV images of different areas and an object-based classification algorithm was used to detect roads. Then, statistical comparisons were made and, user accuracy in the three study regions ranged from 85 to 91%. Overall accuracies were calculated between 0.819 and 0.889, and the results were within the confidence interval.
Koleksiyonlar
- Fakülteler
- Mühendislik Fakültesi
- Harita Mühendisliği Bölümü
- Harita Mühendisliği Anabilim Dalı
|
Eser Adı dc.title |
The effect of different areas and image band in the road extraction from high-resolution uav images using the Obia method |
|---|---|
|
Yazarlar dc.contributor.author |
Yiğit, Abdurahman Yasin |
|
Kurum Dışı Yazarlar dc.contributor.other |
Uysal, Murat |
|
Yayıncı dc.publisher |
Springer Nature |
|
Yayın Türü dc.type |
Makale |
|
Özet dc.description.abstract |
This study semi-automatically detects road lines using object-based classification methods from orthophoto produced from UAV images. Three studies were carried out on images with visible and infrared wavelengths. The study's major aim is to examine the effect of spectral bands and different areas on classification accuracy. First, orthophotos were produced from UAV images of different areas and an object-based classification algorithm was used to detect roads. Then, statistical comparisons were made and, user accuracy in the three study regions ranged from 85 to 91%. Overall accuracies were calculated between 0.819 and 0.889, and the results were within the confidence interval. |
|
Kayıt Giriş Tarihi dc.date.accessioned |
2026-01-12 |
|
Yayın Yılı dc.date.issued |
2026 |
|
Açık Erișim Tarihi dc.date.available |
2026-01-12 |
|
Dil dc.language.iso |
eng |
|
Konu Başlıkları dc.subject |
Cartography |
|
Konu Başlıkları dc.subject |
Computer Vision |
|
Konu Başlıkları dc.subject |
Object Recognition |
|
Konu Başlıkları dc.subject |
Object vision |
|
Konu Başlıkları dc.subject |
Remote Sensing/Photogrammetry |
|
Konu Başlıkları dc.subject |
Shape Analysis |
|
Atıf İçin Künye dc.identifier.citation |
Yiğit, A. Y., & Uysal, M. (2026). The effect of different areas and image band in the road extraction from high-resolution uav images using the Obia method. Applied Geomatics, 18(1), 33. |
|
Haklar dc.rights |
Applied Geomatics |
|
ISSN dc.identifier.issn |
1866-928X |
|
İlk Sayfa dc.identifier.startpage |
18 |
|
Son Sayfa dc.identifier.endpage |
33 |
|
Makale Numarası dc.identifier.articlenumber |
33 |
|
Dergi Adı dc.relation.journal |
Applied Geomatics |
|
Dergi Sayısı dc.identifier.issue |
1 |
|
Dergi Cilt dc.identifier.volume |
18 |
|
Tek Biçim Adres (URI) dc.identifier.uri |
https://link.springer.com/article/10.1007/s12518-025-00678-8 |
|
Tek Biçim Adres (URI) dc.identifier.uri |
https://hdl.handle.net/20.500.14114/9069 |
|
DOI Numarası dc.identifier.doi |
https://doi.org/10.1007/s12518-025-00678-8 |
|
İndekslenen Platformlar dc.source.database |
Web of Science |
Bulunamadı