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• Agnew MD and Palutikof JP (2000). GIS-based construction of baseline climatologies for the Mediterranean using terrain variables. Climate Research 14: 115-127.
• Alsamamra H, Ruiz-Ariaz JA, Pozo-Vazquez D and Tovar-Pescadur J (2009). A comparative study of ordinary and residual kriging techniques for mapping global solar radiation over southern Spain. Agriculture and Forest Meteorology 149:1343-1357.
• Antonic O, Krizan J, Marki A and Bukovec D (2001). Spatio-temporal variables over large region of complex terrain using neural networks. Ecological Modelling 138: 255-263.
• Ashiq MW, Zhao C, Ni J and Akhtar M (2010). GIS-based high-resolution spatial interpolation of precipitation in mountain-plain areas of Upper Pakistan for regional climate change impact studies. Theoretical and Applied Climatology 99 (3-4): 239-253.
• Benavides R, Montes F, Rubio A and Osoro K (2007). Geostatistical modelling of air temperature in a mountainous Agricultural and Forest Meteorology 146: 173- 188.
• Burrough PA and McDonnell RA (1998). Principles of Geographical Information Systems. New York: Oxford University Press.
• Collins FC and Bolstad PV (1996). A comparison of spatial interpolation techniques in temperature estimation. In: Proceedings of the Third International Integrating GIS and Environmental Modeling, Santa Fe, New Mexico, January 21-25, 1996. Santa Barbara, California: National Center for Geographic Information Analysis (NCGIA), CD-ROM.
• Daly C, Neilson RP and Phillips D (1994). A Statistical- Topographical Climatological Precipitation over Mountainous Terrain. Journal of Applied Meteorology 33 (2): 140-158. for Mapping
• Demircan M, Alan İ and Şensoy S (2011). Coğrafi bilgi sistemleri kullanarak sıcaklık haritalarının çözünürlüğünün artırılması. TMMOB Harita ve Kadastro Mühendisleri Odası 13. Türkiye Harita Bilimsel ve Teknik Kurultayı. 18-22 Nisan 2011, Ankara.
• Diodato N, Ceccarelli M (2005). Interpolation processes using multivariate geostatistics for mapping of climatological precipitation mean in the Sannio Mountains (Southern Italy). Earth Surface Processes and Landforms 30: 259-268.
• Doğan HM, Kılıç OM, and Yılmaz DS (2013). Preparing and Analyzing the Thematic Map Layers of Great Soil Groups, Erosion Classes and Land Capability Classes of Tokat Province by GIS. Journal Gaziosmanpasa University 30(2): 18-29.
• Doğru A, Okçu D, Özener H and Solum Ş (2013). Coğrafi Agricultural Faculty of bilgi sistemleri ile iklim karakteri üzerine çalışmalar, TMMOB Coğrafi Bilgi Sistemleri Kongresi, 11-13 Kasım 2013, Ankara.
• Gomez KA and Gomez AA (1984). Statistical Procedures for Agricultural Research (2nd edn). John Willey and Sons: Singapore.
• Goovaerts P (1997). Geostatistics for Natural Resources Evaluation. Oxford University Press, New York.
• Goovaerts P (1999). Using elevation to aid the geostatistical mapping of rainfall erosivity. Catena 34: 227-242.
• Guan BT, Hsu HW, Wey T and Tsao L (2009). Modelling monthly mean temperatures for the mountain regions of Taiwan by generalized additive models. Agricultural and Forest Meteorology 149: 281-290.
• Güler M, Cemek B and Günal H (2007). Assessment of Some Spatial Climatic Layers Through GIS and Statistical Analysis Techniques in Samsun Turkey. Meteorological Application 14 (2): 163- 169.
• Güler M and Kara T (2014). A comparison of different interpolation techniques used in mapping monthly precipitation in northern Turkey. Fresenius Environmental Bulletin 23(2): 341- 347.
• Hengl T (2007). A Practical Guide to Geostatistical Mapping of Environmental Variables. JRC Scientific and Technichal Reports. Office for Official Publication of the European Communities, Luxembourg.
• Isaaks EH and Srivastava RM (1989). An Introduction to applied Geostatistics. Oxford Uni. Press, Inc. New York.
• Kurtzman D and Kadmon R (1999). Mapping of temperature variables in Israel: a comparison of different Research 13: 33-43.
• Li J and Heap AD (2011). A review of comparative studies of spatial interpolation methods in environmental sciences: Performance and impact factors. Ecological Informatics 6: 228- 241.
• Luna MY, Morata A, Almarza C and Martin ML (2006). The use of GIS to evaluate and map extreme maximum and minimum temperatures in Spain. Meteorological Application 13: 385-392.
• Marquínez J, Lastra J and García P (2003). Estimation models for precipitation in mountainous regions: the use of GIS and multivariate analysis. Journal of Hydrology 270: 1-11.
• Martínez-Cob A (1996). Multivariate geostatistical analysis of evapotranspiration and precipitation in mountainous terrain. Journal of Hydrology 174: 19-35.
• MGM (2012). Meteorology Bulletin Reports, Turkey. Moral FJ (2010). Comparison of different geostatistical approaches to map climate variables: application to precipitation. International Journal of Climatology 30: 620-631.
• Ninyerola M, Pons X and Roure JM (2000). A methodological approach of climatologically modelling of air temperature and precipitation through GIS techniques. International Journal of Climatology 20: 1823-1841.
• Ninyerola M, Ponsb X and Roure JM (2007). Objective air temperature mapping for the Iberian Peninsula using spatial interpolation and GIS. International Journal of Climatology 27: 1231-1242.
• Rossi RE, Mulla DJ, Journel AG and Franz EH (1992). Geostatistical tools for modeling and interpreting ecological spatial dependence. Ecological Monographs 62: 277-314.
• Ruiz-Arias JA, Pozo-Vázquez D, Santos-Alamillos FJ, Lara-Fanego V and Tovar-Pescador J (2011). A topographic geostatistical approach for mapping monthly mean values of daily global solar radiation: A case study in southern Spain.
• Agricultural and Forest Meteorology 151:1812- 1822.
• Skirvin SM, Marsh SE, McClaranw MP and Mekoz DM (2003). Climate spatial variability and data resolution in a semi-arid watershed, southeastern Arizona. Journal of Arid Environments 54: 667-686.
• Spadavecchia L and Williams M (2009). Can spatiotemporal geostatistical mothods improve high resolution regionalisation of meteorological variables? Agricultural and Forest Meteorology 149: 1105-1117.
• Stahl K, Moore RD, Floyer JA, Asplin MG and McKendry IG (2006). Comparison of approaches for spatial interpolation of daily air temperature in a large region with complex topography and highly variable station density. Agricultural and Forest Meteorology 139: 224-236.
• Susam T, Karaman, S and Oztekin T (2006). Geographic information system of waters; Tokat province sample. Journal of Agricultural Faculty of Gaziosmanpasa University 23(1): 75-82.
• Tellez B, Cernocky T and Terradellas E (2008). Calculation of climatic reference values and its use for automatic outlier detection in meteorological datasets. Advances in Science and Research 2:1-4.
• Türkeş M, Sümer UM and Demir İ (2002). Re-evaluation of trends and changes in mean, maximum and minimum temperatures of Turkey for the period 1929-1999. International Journal of Climatology 22: 947-977.
• Voltz M and Webster R (1990). A comparison of kriging, cubic splines and classification for predicting soil properties from sample information. Journal of Soil Science 41: 473-490.
• Wackernagel H (2003). Multivariate Geostatistics: An Introduction with Applications. Springer, Berlin.
• Wang H, Liu G and Gong P (2005). Use of cokriging to improve estimates of soil salt solute spatial distribution in the Yellow River delta. Acta Geographica Sinica 60: 511-518.
• Webster R and Oliver M (2001). Geostatistics for enviromental science. John WileyandSons, Ltd, Chichester.
• Wei H, Li JL and Liang TG (2005). Study on the estimation of precipitation resources for rainwater harvesting agriculture in semi-arid land of China. Agricultural Water Management 71(1): 33-45.
• Yavuz H and Erdoğan S (2012). Spatial analysis of monthly and annual precipitation trends in Turkey. Water Resource Management 26: 609- 621.