Eurasia Journal of Mathematics, Science and Technology Education

• Anselin, L. (1998). Exploratory spatial data analysis in a geocomputational environment. In: P. A. Longley, S. M. Brooks, R. McDonnell, B. Macmillan (eds.) Geocomputation – A Primer, pp. 77–94. Wiley, Chichester.
• Anselin, L. (1999). Interactive techniques and exploratory spatial data analysis. In: Longley,P.A., Godchild, M.F., Maguire, D.J. (Eds.), Geographical Information Systems. John Wiley & Sons, New York, pp. 253–266.
• Anselin, L., Sridharan, S., & Gholston, S. (2007). Using exploratory spatial data analysis to leverage social indicator databases: the discovery of interesting patterns. Social Indicators Research, 82(2), 287e309.
• Cervero, R., & Kang, C. D. (2011). Bus rapid transit impacts onland uses and land values in Seoul, Korea. Transport Policy, 18, 102e116.
• Geary, R. C. (1954). The contiguity ratio and statistical mapping. The Incorporated Statistician, 5, 115- 145.
• Getis, A., & Ord, J. K. (1992). An analysis of spatial association by use of distance statistic. Geographical Analysis, 24(3), 189-206.
• Gimpel, A., Stelzenmüller, V., Grote, B., Buck, B. H., Floeter, J., Núñez-Riboni, I., … Temming, A. (2015). A GIS modelling framework to evaluate marine spatial planning scenarios: Co-location of offshore wind farms and aquaculture in the German EEZ. Marine Policy, 55, 102-115.
• Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37, 17-33.
• Sánchez-García, S., Canga, E., Tolosana, E., & Majada, J. (2015). A spatial analysis of woodfuel based on WISDOM GIS methodology: Multiscale approach in Northern Spain. Applied Energy, 144, 193-203.
• Su, S. L., Xiao, R., Jiang, Z. L., & Zhang, Y. (2012). Characterizing landscape pattern and ecosystem service value changes for urbanization impacts at an eco-regional scale. Appl. Geogr, 34, 295–305.
• Tobler, W. (2014). On the first law of geography: A reply. Annals of the Association of American Geographers, 94(2), 304-310.
• Wang, C.-H., & Chen, N. (2015). A GIS-based spatial statistical approach to modeling job accessibility by transportation mode: case study of Columbus, Ohio. Journal of Transport Geography, 45, 1-11.
• Yang, Y., & Wong, K. K. (2013). Spatial distribution of tourist flows to China's cities. Tour. Geogr., 15(2), 338–363.
• Zhang, Y., Xu, J. H., & Zhuang, P. J. (2011). The spatial relationship of tourist distribution in Chinese cities. Tour. Geogr, 13(1), 75–90.

APA

Zhang, S., Lin, D., & Chang, T. (2018). Improving the Basics of GIS Students’ Specialism by Means of Application of ESDA Method. Eurasia Journal of Mathematics, Science and Technology Education, 14(6), 2121-2132. https://doi.org/10.29333/ejmste/86468

Vancouver

Zhang S, Lin D, Chang T. Improving the Basics of GIS Students’ Specialism by Means of Application of ESDA Method. EURASIA J Math Sci Tech Ed. 2018;14(6):2121-32. https://doi.org/10.29333/ejmste/86468

AMA

Zhang S, Lin D, Chang T. Improving the Basics of GIS Students’ Specialism by Means of Application of ESDA Method. EURASIA J Math Sci Tech Ed. 2018;14(6), 2121-2132. https://doi.org/10.29333/ejmste/86468

Chicago

Zhang, Shiliang, Dejing Lin, and Tingcheng Chang. "Improving the Basics of GIS Students’ Specialism by Means of Application of ESDA Method". Eurasia Journal of Mathematics, Science and Technology Education 2018 14 no. 6 (2018): 2121-2132. https://doi.org/10.29333/ejmste/86468

Harvard

Zhang, S., Lin, D., and Chang, T. (2018). Improving the Basics of GIS Students’ Specialism by Means of Application of ESDA Method. Eurasia Journal of Mathematics, Science and Technology Education, 14(6), pp. 2121-2132. https://doi.org/10.29333/ejmste/86468

MLA

Zhang, Shiliang et al. "Improving the Basics of GIS Students’ Specialism by Means of Application of ESDA Method". Eurasia Journal of Mathematics, Science and Technology Education, vol. 14, no. 6, 2018, pp. 2121-2132. https://doi.org/10.29333/ejmste/86468