AUTOMATIC ROAD DETECTION FROM ORTHOPHOTO IMAGES
AUTOMATIC ROAD DETECTION FROM ORTHOPHOTO IMAGES
Aerial photos and satellite images tell us about the land surface. It provides a variety of information such as particularly human-built objects such as buildings, roads and bridges and the location and characteristics of the vegetation. With the exception of aerial photographs and satellite imagery, the collection, evaluation, and updating of the required data with other data collection methods is a time-consuming process and more costly. Data from aerial photographs and satellite images have long been detected manually by conventional methods and by operators. The automatically of these detections increases the speed of the project process and contributes to the reduction of the expenses spent. The projects carried out within the scope of the extraction and classification of objects are mostly concentrated on buildings and roads. Because roads and buildings; Due to the characteristic features such as having sharp lines and easy determination of the geometric shape, the identification of the detail lines in the objects is easier than determining the details of other objects. Various object extraction and classification techniques are used for image analysis with semi and fully automatic approach methods based on image processing techniques. In this study, aerial photographs of a certain area of Afyon Kocatepe University Ahmet Necdet Sezer Campus were obtained by using unmanned aerial vehicles (UAV). The raw data obtained were evaluated and the object-based classification approach was used to automatic detection and classify the roads of the university in the digital environment.
Keywords:
Object-based, Automatic Road Detection, Classification UAV, Road,
___
- segmentation: an optimization approach for high quality multi scale image segmentation, Proceedings of Twelfth Angewandte Geographische Informations verarbeitung, Wichmann-Verlag, Heidelberg, ss.12−23.
- Benz U.C., Hofmann P., Willhauck G., Lingenfelder I. and Heynen M. (2004). Multi-resolution object-oriented fuzzy analysis of remote sensing data for GIS- ready information, ISPRS Journal of Photogramemetry and Remote Sensing, 58 (3-4), 239-258
- Boyacı, D. (2012). Cbs-Uzaktan Algılama entegrasyonu ve örnek uygulama: uydu görüntülerinden detay ve otomatik öznitelik tespiti, Doktora Tezi, Selçuk
- Cömert R., Avdan U. and Şenkal E. (2012). İnsansız Hava Araçlarının Kullanım Alanları Ve Gelecekteki Beklentiler, IV. Uzaktan Algılama ve Coğrafi Bilgi Sistemleri Sempozyumu (UZAL-CBS 2012), 16-19.
- Definiens. (2012). Definiens Developer XD 2.0.4. Reference Book, Definiens AG, München, Germany, https://www.imperial.ac.uk/media/imperialcollege/ medicine/facilities/film/Definiens-Developer- Reference-Book-XD-2.0.4.pdf , (21.10.2019).
- Eisenbeiss, H. (2009). UAV Photogrammetry, ETH Zurich for the degree of Doctor of Science, ISNN 0252-9335 . ISBN: 978-3-906467-86-3.
- Geçen R. and Sarp G. (2007). Yüksek ve düşük çözünürlüklü uydu görüntülerinden yolların tayini, TMMOB Harita ve Kadastro Mühendisleri Odası Ulusal Coğrafi Bilgi Sistemleri Kongresi, 30 Ekim –02 Kasım 2007, KTÜ, Trabzon
- Hofmann, P. (2001a). Detecting Urban Features from IKONOS Data Using an Object-Oriented Approach, First Annual Conference of the Remote Sensing & Photogrammetry Society 12-14 September 2001, 28-33.
- Hofmann, P. (2001b). Detecting Buildings and Roads from IKONOS Data Using Additional Elevation Information. GIS GeoInformation-System, 2001:6.
- Hofmann, P. (2001c). Detecting Informal Settlements from IKONOS Image Data Using Methods of Object-Oriented Image Analysis -An Example from Cape Town”, Remote Sensing of Urban Areas. edited by Jürgens, Carsten (Regensburg) Kalkan, K. and Maktav, D. (2010). Nesne Tabanlı ve Piksel Tabanlı Sınıflandırma Yöntemlerinin Karşılaştırılması (IKONOS Örneği), III. Uzaktan Algılama ve Coğrafi Bilgi Sistemleri Sempozyumu Ocak 2010
- Marangoz A.M., Karakış S., Oruç M. and Büyüksalih G. (2005). Nesne-tabanlı görüntü analizi ve ıkonos pan-sharpened görüntüsünü kullanarak yol ve binaların çıkarımı, 10. Türkiye Harita Bilimsel ve Teknik Kurultayı 28 Mart - 1 Nisan 2005, Ankara
- Sabuncu, A. and Sunar, F. (2017). Ortofotolar ile Nesne Tabanlı Görüntü Sınıflandırma Uygulaması: Van-Erciş Depremi Örneği, Artvin Çoruh Üniversitesi Doğal Afetler Uygulama ve Araştırma Merkezi Doğal Afetler ve Çevre Dergisi Cilt:3, Sayı:1, Ocak 2017 (1-8)
- Wenxia WEI, Xiuwan Chen and Ainai Ma. (2005). Object-Oriented Information Extraction and Application in High-Resolution Remote Sensing Image, IEEE International Geoscience & Remote Sensing, Vol. 6, pp. 3803-3806, 2005.
- Yılmaz, H.M., Mutluoğlu, Ö., Ulvi, A., Yaman, A. and Bilgilioğlu, S.S. (2018). İnsansız Hava Aracı İle Ortofoto Üretimi Ve Aksaray Üniversitesi Kampüsü Örneği. Geomatik Dergisi 2018; 3(2);103-110
- Yayın Aralığı: Yılda 2 Sayı
- Başlangıç: 2019
- Yayıncı: Mersin Üniversitesi
Sayıdaki Diğer Makaleler
3D MODELLING OF KAYSERI TEKGOZ BRIDGE
Ali ULVİ, Abdurahman Yasin YİĞİT
AUTOMATIC ROAD DETECTION FROM ORTHOPHOTO IMAGES
Abdurahman Yasin YİĞİT, Murat UYSAL
LIGHT RAIL LINE DESIGN FOR EAST BLACK SEA REGION: A CASE STUDY OF TRABZON
Hatice ÇATAL REİS, Abdulkadir BİRİNCİ
INVESTIGATION OF PHENOLOGICAL STAGES OF WHEAT PLANT USING VEGETATION INDEX
THE EFFECT OF DIFFERENT FLIGHT HEIGHTS ON GENERATED DIGITAL PRODUCTS: DSM AND ORTHOPHOTO
Mehmet Özgür ÇELİK, Aydın ALPTEKİN, Fatma BÜNYAN ÜNEL, Lütfiye KUŞAK, Engin KANUN