Determination of Land Use and Land Cover Using Remote Sensing in Sakarya
Tam metin:PDF (English)
Anonymous, 2010. Effects of European Union are in 100 issues on everyday life. Republic of Turkey, General Secretariat of European Union, Presidency of Civil Society, Communication and Culture, Ankara,72p.
Baker, J., Briggs, S., Gordon, V., Jones, A., Settle, J., Townsend, J., Wyatt, B. 19 Advances in Classification for Land Cover Mapping Using SPOT HRV Imagery. International Journal of Remote Sensing, 12: 1071–1085.
Barandela, R., Juarez, M. 200 Supervised Classification of Remotely Sensed Data with Ongoing Learning Capability. International Journal of Remote Sensing, 23 (22): 4965–4970.
Bennett, L.T., Judd, T.S., Adams, M.A. 2000. Closerange Vertical Photography for Measuring Cover Changes in Perennial Grasslands. Journal of Range Management. 53(6): 634-641.
Binh, T.N.K.D., Vromant, N., Hung, N.T., Hens, L., Boon, E.K. 2005. Land Cover Changes Between 1968 and 2003 in Cai Nuoc, Ca Mau Peninsula, Vietnam. Environment, Development and Sustainability, 7: 519-536.
Booth, D.T., Cox, S.E., Fifield, C., Phillips, M., Williamson, N. 2005. Image Analysis Compared with Other Methods for Measuring Ground Cover. Arid Land Research and Management, 19: 91-100.
Brodley, C., Friedl, M. 1999. Identifying Mislabeled Training Data. Journal of Artificial Intelligence Research, 11: 131–167.
Brooks, C.N., Nevada, R., Powell, R.B., French, N.H.F., Shuchman, R.A. 2006. Multi-Temporal And multiplatform Agricultural Land Cover Classification in Southeastern Michigan. ASPRS 2006 Annual Conference Reno, May 1-5, Nevada.
Chuvieco, E., Congalton, R.G. 1998. Using Cluster Analysis to Improve the Selection of Training Statistics in Classifying Remotely Sensed Data. Photogrammetric Engineering and Remote Sensing, 54: 1275–1281.
Congalton, R.G., Green, K. 1998. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, New York: Lewis Publishers.
Esetlili, M.T., Kurucu, Y. 2003. Research on Supervised Classification Methods to Determine Cotton Planted Areas by Remote Sensing Technique. Ege University, Journal of Agricultural Faculty, 40(2): 105Estes, J.E., Mooneyhan, D.W. 1994. Of Maps And Myths. Photogrammetric Engineering and Remote Sensing, 60: 517–524.
Foody, G.M. 1990. Direct Ground Survey for Improved Maximum Likelihood Classification of Remotely Sensed Data. International Journal of Remote Sensing, 11: 1935–1940.
Genc, L., Smith, S., Charles, S., McCorry, F. 2005. A Comparison of Landsat Thematic Mapper and Indian Remote Sensing Data for Land Use and Land Cover Change Assessment. Trakya University Journal of Science. 6(2): 17-28.
Goward, S.N., Dye, D.G. 1987. Evaluating North American Net Primary Productivity with Satellite Observations. Advances in Space Research, 7: 1651
GTHB, 2006. Hazelnut Report. Ministry of Food Agriculture and Livestock, Sakarya Provincial Directorate, 5 p.
GTHB, 2007. Project and Statistics Branch 2007 Annual Activity Summary. Sakarya, Turkey: Ministry of Food Agriculture and Livestock, Sakarya Provincial Directorate, 39 p.
GTHB, 2011. The Regulation of Procedures And Principles on Planning Hazelnut Production and Determining the Planting Areas with Supporting the Producers Who Prefer Planting Alternative Products Instead of Hazelnut and Supplying Technical Help for These Producers. Ministry of Food Agriculture and Livestock Sakarya Provincial Directorate.12p. www.tarim.gov.tr/files/
Mevzuat/yonetmelik_son/ findik~1.pdf Hatfield, J.L., Asrar, G., Kanemasu, E.T. 1984. Intercepted Photosynthetically Active Radiation Estimated by Spectral Reflectance. Remote Sensing of Environment, 14: 65-75.
Ince, F. 1986. Maximum Likelihood Classification, Optimal or Problematic? A Comparison with the KNN Classification Izmit, Turkey: TUBITAK, Marmara Scientific and Industrial Research Institute, Electronic Research Unit, Technical Report No. TR-86/09.
Isik, S. 2007. Sakarya’s Agriculture Geography. Sakarya, Turkey: Sakarya University, Institute of Social Sciences, MSc thesis, 123 p. Sakarya, Turkey.
Janssen, L., Van Der Wel, F. 19 Accuracy Assessment of Satellite Derived Land Cover Data: a review. Photogrammetric Engineering and Remote Sensing, 60: 419-426. Jones, G.J., Vaughan, R.A. 2010. Remote Sensing of Vegetation. New York: Oxford University Press, 400p.
Kershaw, C.D., Fuller, R.M. 1992. Statistical Problems in the Discrimination of Land Cover from Satellite Images: A Case Study in Lowland Britain. International Journal of Remote Sensing, 13: 3085– 3
Ozyavuz, M. 2010. Analysis of Changes in Vegetation Using Multi Temporal Satellite Imagery, the Case of Tekirdag Coastal Town.
Journal of Coastal Research, 26 (6): 1038-1046.
Price K. P, Pike D. A, Mendes L. 1992. Shrub Dieback in a Semiarid Ecosystem the Integration of Remote Sensing and Geographic Information Systems for Detecting Vegetation Change. Photogrammetric Engineering and Remote Sensing, 58(4): 455-463.
Reis, S., Yomralioglu, T. 2002. Using Landsat ETM to Obtain Land Use Map of the Province of Trabzon, 7 th
ESRI and ERDAS Users Meeting, Ankara, Turkey. Tucker, C.J., Sellers, P. 1986. Satellite Remote Sensing of Primary Production. International Journal of Remote Sensing, 7: 1395-1416. TUIK. 200 Turkish Statistical Institute. http://www.tuik.gov.tr/bitkiselapp/bitkisel.zul accessed on 16 December, 2009.
Woodcock C. E., Macomber S. A. 2001. Monitoring Large Areas for Forest Change Using Landsat: Generalization across Space, Time and Landsat Sensors. Remote Sensing of Environment, 78 (1): 194-20