تحلیل ارتباطات بین متغیّرهای فضایی در دشت خان‌میرزا: مقایسه‌ی کارایی الگوی رگرسیون وزنی جغرافیایی و الگوی حداقل مربعات معمولی

تقی‌پورجاوی، شهاب‌الدین؛ بهرام ملک‌محمدی؛ سجاد شمشیری ‌(1392). آثار و عوامل محیط‌زیستی تغییرات کاربری اراضی و برداشت منابع آب زیرزمینی دشت خان‌میرزا، اولین همایش ملّی حفاظت و برنامه‌ریزی محیط‌زیست.

کسرایی، اسرافیل‌‌ (1386). نظریه‌ی همگرایی، وابستگی فضائی و رشد منطقه‌ای‌ (شواهدی از کشورهای عضو سازمان کنفرانس اسلامی به منظور کاربرد)، تحقیقات اقتصادی. شماره 77. صفحات 55- 45.

Andy, M. (2005). The ESRI Guide to GIS Analysis (Vol. 2). ESRI Press.

Brown, S., Versace, V. L., Laurerson, L., Fawcett, J & Salzman, S (1996). Geographically weighted regression: A Method for Exploring Spatial Non-Stationarity. Geographical Analysis,28(4),281-298.

Chatterjee, S & Hadi, A. S. (2006). Regression Analysis By Example (Vol.4).John Wiley&Sons.

Fotheringham, S. A., Brunsdon, C & Charlton, M. (2002). Geographically Weighted Regression the analysis of spatially varying relationships. John Wiley & Sons.

Fotheringham, S. A., & Brunsdon, C. (1999). Local forms of spatial analysis. . Geographical Analysis, 31, 340-358.

Fotheringham, S. A., Charlton, M., & Brunsdon, C. (1998). Geographically weighted regression: a natural evolution of the expansion method for spatial data analysis. Environmental Planning, 30(11), 1905-1927.

Gao, J., & Li, S. (2011). Detecting spatially non-stationary and scale-dependent relationships between urban landscape fragmentation and related factors using Geographically Weighted Regression. Applied Geography, 31, 292-302.

Man, P. S. (2006). Comparison of Ordinary Least Square Regression, Spatial Autoregression, and Geographically Weighted Regression for Modeling Forest Structural Attributes Using a Geographical Information System(GIS)/Remote Sensing(RS) Approach. University of Calgary, Department of Geography. Calgary, Alberta: Msc Thesis.

Montgomery, D. C., Peck, E. A., & Vining, G. G. (2001). Introduction to Linear Regression Analysis (Vol. 3). John Wiley & Sons.

Motiee , H., Ghadri, M., Nasiri , H., & Taghipour Javi, S (2015). Spatial and temporal variability analysis of groundwater quantity to land use/land cover change in the Khanmirza agricultural plain, Iran. Arabian Journal of Geosciences, 8 (10), 8385- 8397.

Pineda Jaimes, N. B., Bosque, J., Gómez Delgado, M., & Franco Plata, R. (2010). Exploring the driving forces behind deforestation in the state of Mexico (Mexico) using geographically weighted regression. Applied Geography, 30(4), 576-591.

Pratt, B., & Chang, H. (2012). Effects of Land Cover, Topography, and Built Structure on Seasonal Water Quality at Multiple Spatial Scales. Journal of hazardous materials, 48-58.

Propastin, P. (2012). Modifying geographically weighted regression for estimating aboveground biomass in tropical rainforests by multispectral remote sensing data. International Journal of Applied Earth Observation and Geoinformation, 18, 82-90.

Robinson, D. P., Lloyd, C. D., & McKinley, J. M. (2013). Increasing the accuracy of nitrogen dioxide (NO2) pollution mapping using geographically weighted regression (GWR) and geostatistics. International Journal of Applied Earth Observation and Geoinformation, 374-383.

Su, S., Xiao, R., & Xiao, Y. (2012). Multi-scale analysis of spatially varying relationships between agricultural landscape patterns and urbanization using geographically weighted regression. Applied Geography, 32(3), 360-375.

Taghipour Javi, S., Mokhtari, H., Rashidi A, A, & Taghipour Javi,H(2015). Analysis of spatiotemporal relationships between irrigation water quality and geo-environmental variables in the Khanmirza agricultural plain, Iran. Journal of Biodiversity & Environmental Sciences,6,240-252.

Taghipour Javi, S., Fazeli, A., & Kazemi, B. (2016). A case study of desertification hazard mapping using the MEDALUS(ESAs) methodology in southwest Iran. Journal of Natural Resources and Development, 6, 1-8.

Taghipour Javi, S., Malekmohammedi, B., & Mokhtari, H (2014). Application of geographically weighted regression model to analysis of spatiotemporal varying relationships between groundwater quantity and land use changes (case study: Khanmirza plain, Iran). Environmental Monitoring and Assessment, 186(5), 3123-3138.

Tu, J (2011). Spatially varying relationships between land use and water quality across an urbanization gradient explored by geographically weighted regression. Applied Geography, 31(1), 376-392.

Tu, J., & Xia, Z (2008). Examining Spatially Varying Relationships Between Land Use And Water Quality Using Geographically Weighted Regression I: Model Design And Evaluation. Science of The Total Environment,407(1),358-378.

Zhang, L., Gove, J. H., & Heath, L. S. (2005). Spatial residual analysis of six modeling techniques. Forest Ecology and Management, 189, 317–329.