1- فیضیزاده، حاجمیررحیمی؛ بختیار، سید محمود(1386)؛ آشکارسازی تغییرات فضای سبز شهر تبریز با استفاده از روشهای شیءگرا، همایش شهری GIS.
2- خلاقی، سام؛ (1385)؛ پایش تغییرات خط ساحل دریای خزر، پایان نامه کارشناسی ارشد، دانشکده ادبیات و علوم انسانی، دانشگاه تبریز.
3- احدنژاد، محسن؛ (1379)؛ ارزیابی و مدلسازی تغییرات کاربری اراضی با استفاده از تصاویر ماهوارههای چندگانه و GIS، پایان نامه کارشناسی ارشد، دانشکده علوم انسانی، دانشگاه تربیت مدرس.
4- رسولی، علی اکبر و همکاران طرح؛(1386)؛ ارزیابی تغییرات جنگلهای ارسباران با استفاده از فناوری GIS، طرح تحقیقاتی، مدیریت پژوهش و فناوری دانشگاه تبریز.
5- Alavipanah, S.K., 2003, Application Remote Sensing in Geology (Earth Sciences), Tehran University Press, 478 pages.
6 - Baatz, M. and Schape, A., 1999, Object-oriented and Multi Scale Image Analysis in Semantic Networks, Proceeding of the 2nd international symposium on remote sensing,16-22 August, Ensched, ITC.
7 - Boniad, A.E. and Hajighaderi, T., 2008, Mapping of Natural Forest Stands of Zanjan Province Using Landsat 7ETM+ sensor data, Science and Technology of Agriculture and Natural Resources, 42(11): 627-638.
8 - Borri, D., Caprioli, M. and Tarantino, E., 2005, Spayial Informattion Extraction from VHR Satellite Data to Detect land Cover Transformations, Polytechnic University of Bari, Italy.
9 - Chavez, P.S.J.R. and Mackinnon, D.J., 1994, Automatic detection of vegetation changes in the southwestern United States using remotely sensed images, Photogrammetric Engineering and Remote Sensing, 60: 571–583.
10- Chen, M., Su, W., Li, L., Chao, Z., Yue, A. and Li, H., 2009, Pixel-based and Object-oriented Knowledgebased Classification Methods Using SPOT5 Imagery, WSEAS TRANSACTIONS on INFORMATION SCIENCE and APPLICATIONS, ISSN: 1790-0832, pages 477-489.
12 - Dehvari, A. and Heck, R.J., 2009, Comparison of object-based and pixel based infrared airborne image classification methods using DEM thematic layer, Journal of Geography and Regional Planning, 2(4): 086-096.
13 - Dewan, A.M. and Yamaguchi, Y., 2009, Land Use and Land Cover Change in Greater Dhaka, Bangladesh: Using Remote Sensing to Promote Sustainable Urbanization, Applied Geography 29:390-401.
14 - Du, Y., Teillet, P.M. and Cihlar, J., 2002, Radiometric normalization of multitemporal high-resolution satellite images with quality control for land cover change detection, Remote Sensing of Environment, 82: 123–134.
15 - Fazizadeh, B. and Helali, H., 2010, Comparison of pixel-based and object-oriented and parameters affecting the on land use/cover West Azerbaijan province, Geography Studies, No. 71, 73-84.
16- Gamanya, A., Maeyer, P.D. and Dapper, M.D., 2009, Object- Oriented Change Detection for the City of Harare, Zimbabwe, Expert Systems with Applications, 36 (2009) 571-588.
17 - Gao,Y., Mas, J.F. and Navarrete, A., 2009, The improvement of an object-oriented classification using multi-temporal MODIS EVI satellite data, International Journal of Digital Earth, Volume 2, Issue 3 September 2009 , pp. 219 – 236
18- Hussaina, M., Chen, D., Cheng, A., Wei, H. and Stenley, D., 2013, Change detection from remotely sensed images: From pixel-based to object-based approaches, ISPRS Journal of Photogrammetry and Remote Sensing 80: 91–106.
19 - Karami, A., Khorani, A.A., Falahshamsi, S.R., Mosavi, V. and Khosravi, GH., 2012, Object-oriented application of remote sensing to map gully erosion, 20th Conference of Geomatics of Iran, 8 p.
20 - Khosravi, I. and Momeni, M., 2012, Identification structure of high-resolution satellite imagery using object-based image analysis, 20th Conference of Geomatics of Iran, 10 p.
21 - Mackie, R.I., 2013, Dynamic analysis of structures on multicore computers – Achieving efficiency through object oriented design, Advances in Engineering Software 66: 3–9.
22- Matinfar, H.R., Sarmadian, F., Alavipanah, S.K. and Heck, R., 2008, Characterizing Land use/land cover types by Landsat7data based upon Object oriented approach in Kashan region, Iranian journal of Range and Desert Reseach, 14 (4): 589-602.
23 - Mori, M., Hirose, Y. and Akamatsu, Y.L., 2003, Object- based classification of Ikonos data for rural land use mapping. Http://www.define.com. eCognition Applied Notes , Vol 5 , No. 1.
24- Petropoulos, G.P., Kalaitzidis, C. and Vadrevu, K.P., 2012, Support vector machines and object-based classification for obtaining land-use/cover cartography from Hyperion hyperspectral imagery, Computers & Geosciences, 41: 99–107.
25- Puissant, A., Rougier, S. and Stumpf, A., 2014, Object-oriented mapping of urban trees using Random Forest classifiers, International Journal of Applied Earth Observation and Geoinformation, 26: 235–245.
26 - Rasouli, A.A., 2008, Principles of remote sensing image processing applications, with emphasis on satellite, Tabriz University Press, 777 pages.
27 - Shattri M., Wong, T.H. and Shariff, A.R.M., 2000, Object oriented classification for land cover mapping, Htt://www.define.com. eCognition Applied Notes, Vol, No.2.
28 - Tso, B. and Mather, P.M., 2001, Classification Methods for Remotely Sensed Data, Taylor & Francis, USA.
29- Walter, Volker., 2004, Object-based classification of remote sensing data www.elsevier.com/locate/isprsjprs for change detection,
30 - Wang, L., Sousa, W.P. and Gong, P., 2004, Integration of object-based and pixel-based classification for mapping mangroves with IKONOS imagery, International jornal of Remote sensing, 25(24): 5655-5668.
31- Yaghobzadeh, M. and Akbarpour, A., 2011, The effect of satellite image classification algorithm based on curve number runoff and maximum flood discharge using GIS and RS, Geography and Development 9 (22):5-22.
32 - Yu, H.Y., Cheng, G., Ge, X.S. and Lu, X.P., 2011, Object oriented land cover classification using ALS and GeoEye imagery over mining area, Transactions Nonferrous Metals Society of China 21:733-737.
33- Zhou1, W., Austin, T. and Morgan, G.R., 2005, Measuring Urban arcel Lawn Greenness by Using an Object oriented Classification Approach, Rubenstein School of Environment and Natural Resources, University of Vermont, George D. Aiken Center, 81 Carrigan Drive