___

• 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
• Intenational Olive Council, “World Olive Oil Figures”, http://www.internationaloliveoil.org/web/aa- ingles/corp/AreasActivitie/economics/AreasActivitie.html. Erişim tarihi: Eylül 2010.
• 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.