Apan, A., Young, F., Phinn, S., Held, A. and Favier, J, 2004. Mapping Olive Varieties and Within-Field Spatial Variability Using High Resolution Quickbird Imagery. In Proceedings of 12th Australasian Remote Sensing and Photogrammetry Conference, Spatial Science Institute. 18-22 October 2004, Fremantle, Australia.
Barata T. and Pina P., 2002. Morphological Segmentation of Remotely Sensed Forest Covers in High Spatial Resolution Images. CVRM/Centro de Geo-Sistemas, Instituto Superior Tecnico Av. Rovisco Pais, 1049-001 Lisboa, PORTUGAL. ISBN 0 643 06804 X
Dogan, H., N. Ceylan, E. Unal, M. Aydoğdu, G. Nestı, J. Mason, P. Spruyt, 2004. Determining Olive Growing Areas and Establishing Olive Database of Balıkesir-Burhaniye in Turkey. 10th Annual Conference on Control with Remote Sensing of Area-Based Subsidies, EC-JRC, 25-26 November 2004, Budapest-Hungary- ORA/POST 65783
Falcón, J. D., J. González y G. Ambrosio, 2004. Detección De Olivos En Imágenes De Satélite De Alta Resolución. Revista de Teledetección. 2004. 21: 5-9.
FAO, 2010. “Food and Agrıculture Organızatıon of the Unıted Natıons, FAOSTAT, Crops”, http://faostat.fao.org/DesktopDefault.aspx?PageID=567#ancor. Erişim Tarihi: Ağustos 2010.
Gonzalez J., C. Galindo, V. Arevalo, and G. Ambrosio, 2007. Applying Image Analysis and Probabilistic Techniques for Counting Olive Trees in High-Resolution Satellite Images. 0302- 9743 (Print) 1611-3349 (Online). Volume 4678/2007. Springer Berlin / Heidelberg
Islam Z. and Metternicht G., 2003. Fuzzy Approach to Mapping Tree Crowns and Species from a Forested Area using High Resolution Multispectral Data. Asian Journal of Geoinformatics, Vol. 41, No. 1 September 2003 .Published by ARSRIN, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand
Joint Research Center (JRC), “Computer-Assisted Recognition of Olive Trees in Digital Imagery”, http://mars.jrc.it/Documents/Olivine/COMPUTER- ASSISTED%20RECOGNITION%20OT%20OT.htm. Erişim tarihi: Ağustos 2004.
Karantzalos, G. K., and Argialas, P. D., 2004. Towards Automatic Olive Tree Extraction from Satellite Imagery, Commission III, WG 4, Greece.
Kay, S., Leo, O., Peedell, S., and Giardino, G., 2000. Computer Assited Recognition of Olive Tree in Digital Imagery, Space Applications Institute, JRC of the European Commission, Ispra, Italy.
Kurucu, Y., Ü. Altınbaş, M.Bolca, T.Esetlili, N.Özden, F.Özen, 2008. Uzaktan Algılama Tekniği Kullanılarak Zeytin Dikili Alanların Belirlenebilirliği Üzerine Bir Araştırma. Ege Üniversitesi Bilimsel Araştırma Projesi, - Proje No: 2004-ZRF- 027, Bornova İzmir.
Larsen, M. and M. Rudemo, 1997. Estimation of Tree Positions from Aerial Photos. – In: LINDEBERG,T. (Ed.): Proceedings of the 1997 Swedish Symposium on Image Analysis, pp. 130-134.
Masson, J. and Soille, P., 2004, Tests With VHR Images for The Identification of Olive Trees and Other Fruit Trees in The European Union, Proc. SPIE, Vol. 5568, 23p
Peña-Barragán J.M., M. Jurado-Expósito, F. López-Granados, S. Atenciano, M. Sánchez-de la Orden, A. Garcia-Ferrer, L. Garcia- Torres, 2004. Assessing Land-Use İn Olive Groves From Aerial Photographs. Elsevier Agriculture, Ecosystems and Environment 103 (2004) pp:117–122. USA.
Pouliot, D.A., D.J. King, and D.G. Pitt, 2005. Development and Evaluation of An Automated Tree Detection–Delineation Algorithm for Monitoring Regenerating Coniferous Forests. Can. J. For. Res. 35: 2332–2345 (2005)
Quackenbush, L. J., P. F.Hopkıns, And G. J. Kınn. 2000. Using Template Correlation to Identify Individual Trees in High Resolution Imagery. American Society for Photogrammetry & Remote Sensing (ASPRS) 2000 Annual Conference Proceedings, Washington DC.
Yüksek Çözünürlüklü Uydu Görüntüleri İle Zeytin Dikili Alanların Haritalanmasında Kullanabilecek En Uygun Yöntemin Belirlenmesi Üzerine Araştırmalar
eytin ağaç varlığının belirlenmesi amaçlanan bu çalışmada manuel (elle sayım) olarak uygulanan şablon yöntemi ve yarı otomatik olarak sayım yapabilen OLICOUNT yazılımı karşılaştırılmıştır. Yapılan araştırmalar ve
Apan, A., Young, F., Phinn, S., Held, A. and Favier, J, 2004. Mapping Olive Varieties and Within-Field Spatial Variability Using High Resolution Quickbird Imagery. In Proceedings of 12th Australasian Remote Sensing and Photogrammetry Conference, Spatial Science Institute. 18-22 October 2004, Fremantle, Australia.
Barata T. and Pina P., 2002. Morphological Segmentation of Remotely Sensed Forest Covers in High Spatial Resolution Images. CVRM/Centro de Geo-Sistemas, Instituto Superior Tecnico Av. Rovisco Pais, 1049-001 Lisboa, PORTUGAL. ISBN 0 643 06804 X
Dogan, H., N. Ceylan, E. Unal, M. Aydoğdu, G. Nestı, J. Mason, P. Spruyt, 2004. Determining Olive Growing Areas and Establishing Olive Database of Balıkesir-Burhaniye in Turkey. 10th Annual Conference on Control with Remote Sensing of Area-Based Subsidies, EC-JRC, 25-26 November 2004, Budapest-Hungary- ORA/POST 65783
Falcón, J. D., J. González y G. Ambrosio, 2004. Detección De Olivos En Imágenes De Satélite De Alta Resolución. Revista de Teledetección. 2004. 21: 5-9.
FAO, 2010. “Food and Agrıculture Organızatıon of the Unıted Natıons, FAOSTAT, Crops”, http://faostat.fao.org/DesktopDefault.aspx?PageID=567#ancor. Erişim Tarihi: Ağustos 2010.
Gonzalez J., C. Galindo, V. Arevalo, and G. Ambrosio, 2007. Applying Image Analysis and Probabilistic Techniques for Counting Olive Trees in High-Resolution Satellite Images. 0302- 9743 (Print) 1611-3349 (Online). Volume 4678/2007. Springer Berlin / Heidelberg
Islam Z. and Metternicht G., 2003. Fuzzy Approach to Mapping Tree Crowns and Species from a Forested Area using High Resolution Multispectral Data. Asian Journal of Geoinformatics, Vol. 41, No. 1 September 2003 .Published by ARSRIN, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand
Joint Research Center (JRC), “Computer-Assisted Recognition of Olive Trees in Digital Imagery”, http://mars.jrc.it/Documents/Olivine/COMPUTER- ASSISTED%20RECOGNITION%20OT%20OT.htm. Erişim tarihi: Ağustos 2004.
Karantzalos, G. K., and Argialas, P. D., 2004. Towards Automatic Olive Tree Extraction from Satellite Imagery, Commission III, WG 4, Greece.
Kay, S., Leo, O., Peedell, S., and Giardino, G., 2000. Computer Assited Recognition of Olive Tree in Digital Imagery, Space Applications Institute, JRC of the European Commission, Ispra, Italy.
Kurucu, Y., Ü. Altınbaş, M.Bolca, T.Esetlili, N.Özden, F.Özen, 2008. Uzaktan Algılama Tekniği Kullanılarak Zeytin Dikili Alanların Belirlenebilirliği Üzerine Bir Araştırma. Ege Üniversitesi Bilimsel Araştırma Projesi, - Proje No: 2004-ZRF- 027, Bornova İzmir.
Larsen, M. and M. Rudemo, 1997. Estimation of Tree Positions from Aerial Photos. – In: LINDEBERG,T. (Ed.): Proceedings of the 1997 Swedish Symposium on Image Analysis, pp. 130-134.
Masson, J. and Soille, P., 2004, Tests With VHR Images for The Identification of Olive Trees and Other Fruit Trees in The European Union, Proc. SPIE, Vol. 5568, 23p
Peña-Barragán J.M., M. Jurado-Expósito, F. López-Granados, S. Atenciano, M. Sánchez-de la Orden, A. Garcia-Ferrer, L. Garcia- Torres, 2004. Assessing Land-Use İn Olive Groves From Aerial Photographs. Elsevier Agriculture, Ecosystems and Environment 103 (2004) pp:117–122. USA.
Pouliot, D.A., D.J. King, and D.G. Pitt, 2005. Development and Evaluation of An Automated Tree Detection–Delineation Algorithm for Monitoring Regenerating Coniferous Forests. Can. J. For. Res. 35: 2332–2345 (2005)
Quackenbush, L. J., P. F.Hopkıns, And G. J. Kınn. 2000. Using Template Correlation to Identify Individual Trees in High Resolution Imagery. American Society for Photogrammetry & Remote Sensing (ASPRS) 2000 Annual Conference Proceedings, Washington DC.
Bolca, M., & Özen, F. (2012). Yüksek Çözünürlüklü Uydu Görüntüleri İle Zeytin Dikili Alanların Haritalanmasında Kullanabilecek En Uygun Yöntemin Belirlenmesi Üzerine Araştırmalar. Journal of Agriculture Faculty of Ege University, 49(1), 63-70.