العوامل المحددة لتباين الكثافات السكانية داخل المدن باستخدام طريقتي التربيعات الصغرى العادية ال و ال اس والوزن التراجعي الجغرافي جي دبل يو ار
DOI:
https://doi.org/10.25007/ajnu.v6n1a10الكلمات المفتاحية:
ارتفاع وانحدار الأرض، تحليل الجزئي، تحليل الكلي، Linear Regression، OLSالملخص
التوزيع الجغرافي للسكان داخل المدن والعوامل المؤثرة في ذلك تعد الركيزة الاساسية للبدء في ترتيب عناصر التركيب الداخلي للمدنو، تهدف الدراسة الى اختبار دور عوامل( البعد عن مركز المدينة، حجم السكان، المساحة، معدل ارتفاع وانحدار الارض) على مستوى المحلات السكنية في تباين توزيع الكثافات السكانية داخل مدن الاقليم الثلاث( سليمانية، أربيل، دهوك) ودرجة تاثير كل عامل واختلاف هذا التاثير مكانيا، وفق مفهوم تحليل الانحدار الخطي(Linear Regression Analysis ) وباستخدام طريقتي المربعات الصغرى العادية (Ordinary Least Squares)(OLS) والانحدار الموزون جغرافياً (Geographically Weighted Regression )(GWR) .
واظهرت الدراسة دور ثلاثة عوامل رئيسية (حجم السكان، المساحة، البعد عن مركز المدينة) في هذا المجال بثقة احصائية عالية، وبنسبة تباين تراوحت ما بين (25-76%) بالنسبة لطريقة الـ(OLS) وما بين (25-83%) بالنسبة لطريقة الـ(GWR)، وقد تباين تاثير هذه العوامل مكانيا بالتدريج من مركز المدينة نحو الاطراف كما كان متوقعاً، رغم كل ذلك بقي جزء من التباين غير مفسر تعود الى عوامل اجتماعية او اقتصادية لم تؤخذ بنظر الاعتبار في الدراسة.
التنزيلات
بيانات التنزيل غير متوفرة بعد.
المراجع
المصادر باللغة الانكليزية :
Andrew O. Finley, Comparing spatially-varying coefficients models for analysis of ecological data with non-stationary and anisotropic residual dependence, Methods in Ecology and Evolution 2011, 2, 143–154. doi: 10.1111/j.2041-210X.2010.00060.x
Bo Huanga, Bo Wub and Michael Barryc “Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices, International Journal of Geographical Information Science, Vol. 24, No. 3, March 2010, 383–401.
Chia-Hsien Lin and Tzai-Hung Wen, Using Geographically Weighted Regression (GWR) to Explore Spatial Varying Relationships of Immature Mosquitoes and Human Densities with the Incidence of Dengue, International Journal of Environmental Research and Public Health, 2011, 8, 2798-2815; doi:10.3390/ijerph8072798 www.mdpi.com/journal/ijerph
Chris Brunsdon , A.Stewart Fotheringham & Martin E.Charlton. Geographically Weighted Regression: A Method for Exploration Spatial Nonstationarity , Geographical Analysis ,Vol,28,No.4.1996.pp.281-298.
Chunrong Jia , Wesley James and Satish Kedia, Relationship of Racial Composition and Cancer Risks from Air Toxics Exposure in Memphis, Tennessee, U.S.A., International Journal of Environmental Research and Public Health, 2014, 11, 7713-7724; doi:10.3390/ijerph110807713. http://www.mdpi.com/journal/ijerph
Felix Ndidi Nkeki & Animam Beecroft Osirike,GIS-Based Local Spatial Statistical Model of Cholera Occurrence: Using Geographically Weighted Regression , Journal of Geographic Information System, 2013, 5, 531-532 http://dx.doi.org/10.4236/jgis.2013.56050
Felix Ndidi Nkeki , Animam Beecroft Osirike, GIS-Based Local Spatial Statistical Model of Cholera Occurrence: Using Geographically Weighted Regression , Journal of Geographic Information System, 2013, 5, 531-542. http://dx.doi.org/10.4236/jgis.2013.56050
Foody, G. (2004) spatial nonstationarity and scale-dependency in the relationship between species richness and environmental determinants for the sub-Saharan endemic avifauna. Global Ecology and Biogeography, 13, 315–320.
Gang Lin, Jingying Fu, Dong Jiang , Wensheng Hu , Donglin Dong , Yaohuan Huang , and Mingdong Zhao , Spatio-Temporal Variation of PM2.5 Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China, International Journal of Environmental Research and Public Health, 2014, 11, 173-186; doi:10.3390/ijerph110100173 http://www.mdpi.com/journal/ijerph
Guo, L., Ma, Z. & Zhang, L. (2008) Comparison of bandwidth selection in application of geographically weighted regression: a case study. Canadian Journal of Forest Research, 38, 2526–2534.
J. Mart´ınez-Fern´andez , E. Chuvieco , and N. Koutsias , Modelling long-term fire occurrence factors in Spain by accounting for local variations with geographically weighted regression, Natural Hazards and Earth System Sciences, 13, 311–327, 2013,doi:10.5194/nhess-13-311-2013 www.nat-hazards-earth-syst-sci.net/13/311/2013/
Jie Gao , Zhijie Zhang , Yi Hu , Jianchao Bian , Wen Jiang , Xiaoming Wang ,Liqian Sun , and Qingwu Jiang , Geographical Distribution Patterns of Iodine in Drinking-Water and Its Associations with Geological Factors in Shandong Province, China, International Journal of Environmental Research and Public Health, 2014, 11(5), 5431-5444; doi:10.3390/ijerph110505431 .http://www.mdpi.com/journal/ijerph
Khalid Al-Ahmadi , and Ali Al-Zahrani , Spatial Autocorrelation of Cancer Incidence in Saudi Arabia, International Journal of Environmental Research and Public Health, 2013, 10, 7207-7228; doi:10.3390/ijerph10127207 http://www.mdpi.com/journal/ijerph
Khalid Al-Ahmadi , and Ali Al-Zahrani , NO2 and Cancer Incidence in Saudi Arabia, International Journal of Environmental Research and Public Health, 2013, 10(11), 5844-5862; doi:10.3390/ijerph10115844 . http://www.mdpi.com/journal/ijerph
Mahdi-Salim Saib , Julien Caudeville , Florence Carre , Olivier Ganry , Alain Trugeon , and Andre Cicolella , Spatial Relationship Quantification between Environmental, Socioeconomic and Health Data at Different Geographic Levels, International Journal of Environmental Research and Public Health, 2014, 11, 3765-3786; doi:10.3390/ijerph110403765. http://www.mdpi.com/journal/ijerph
Noresah Mohd Shariff , 1Sanjay Gairola, Anita Talib . Modelling Urban Land Use Change Using Geographically Weighted Regression and the Implications for Sustainable Environmental Planning, International Environmental Modelling and Software Society (iEMSs) 2010 International Congress on Environmental Modelling and Software , Modelling for Environment’s Sake, Fifth Biennial Meeting, Ottawa, Canada , David A. Swayne, Wanhong Yang, A. A. Voinov, A. Rizzoli, T. Filatova (Eds.)
http://www.iemss.org/iemss2010/index.php?n=Main.Proceedings
Paul Holloway and Jennifer A. Miller , Exploring Spatial Scale, Autocorrelation and Nonstationarity of Bird Species Richness Patterns, International Journal of Geo-Information, 2015, 4, 783-798; doi:10.3390/ijgi4020783 http://www.mdpi.com/journal/ijgi
Pavel Propastin, Martin Kappas and Stefan Erasmi, Application of Geographically Weighted Regression to Investigate the Impact of Scale on Prediction Uncertainty by Modelling Relationship between Vegetation and Climate, International Journal of Spatial Data Infrastructures Research, 2008, Vol. 3, 73-94 . DOI: 10.2902/1725-0463.2008.03.art6
Peili Duan, Lijie Qin 1, Yeqiao Wang and Hongshi He , Spatiotemporal Correlations between Water Footprint and Agricultural Inputs: A Case Study of Maize Production in Northeast China, Water 2015, 7, 4026-4040; doi:10.3390/w708402 . http://www.mdpi.com/journal/water
S H M Arshad1, J Jaafar, M Z Z Abiden, Z A Latif and A R A Rasam , Spatial stochastic regression modelling of urban land use : 8th International Symposium of the Digital Earth (ISDE8) doi:10.1088/1755-1315/18/1/012170 http://www.healthunit.org
Shujuan Li , Hongyan Ren , Wensheng Hu 3, Liang Lu , Xinliang Xu , Dafang Zhuang andQiyong Liu , Spatiotemporal Heterogeneity Analysis of Hemorrhagic Fever with Renal Syndrome in China Using Geographically Weighted Regression Models, International Journal of Environmental Research and Public Health, 2014, 11, 12129-12147; doi:10.3390/ijerph111212129. http://www.mdpi.com/journal/ijerph
Stephen A. Matthews & Tse-Chuan Yang.Mapping the results of local statistics: Using geographically weighted regression, DEMOGRAPHIC RESEARCH ,VOLUME 26, ARTICLE 6, PAGES 151-166 ,PUBLISHED 02 MARCH 2012 http: DOI: 10.4054/DemRes.2012.26.6 www.demographic-research.org/Volumes/Vol26/6/
Tayyab Ikram Shah and Scott Bell, Exploring the Intra-Urban Variations in the Relationship among Geographic Accessibility to PHC Services and Socio-demographic Factors, Conference’HealthGIS 13, November 5–8, 2013, Orlando, Florida USA.
Ubydul Haque, Lauren M Scott, Masahiro Hashizume, Emily Fisher, Rashidul Haque, Taro Yamamoto and Gregory E Glass6 , Modeling malaria treatment practices in Bangladesh using spatial statistics, Haque et al. Malaria Journal 2012, 11:63 http://www.malariajournal.com/content/11/1/63
Wenjuan Hou, Jiangbo Gao, Shaohong Wu , and Erfu Dai .Interannual Variations in Growing-Season NDVI and Its Correlation with Climate Variables in the Southwestern Karst Region of China, remote sensing, 2015, 7, 11105-11124, doi:10.3390/rs70911105 http://www.mdpi.com/journal/remotesensing
Wenyi Sun , Jianhua Gong , Jieping Zhou , Yanlin Zhao , Junxiang Tan ,Abdoul Nasser Ibrahim and Yang Zhou , A Spatial, Social and Environmental Study of Tuberculosis in China Using Statistical and GIS Technology, International Journal of Environmental Research and Public Health, 2015, 12, 1425-1448; doi:10.3390/ijerph120201425 http://www.mdpi.com/journal/ijerph
- الكتب باللغة الانكليزية :
Christopher D.LIoyd .Local Models for spatial analysis ,CRC Press , London, 2007.
Christopher D.LIoyd .Spatial Data Analysis An Introduction for GIS users, Oxford University Press , 2010.
Coro Chasco Yrigoyen , Isabel García Rodríguez, José Vicéns Otero , MODELING SPATIAL VARIATIONS IN HOUSEHOLD DISPOSABLE INCOME WITH GEOGRAPHICALLY WEIGHTED REGRESSION1, : Instituto L.R. Klein – Centro Gauss. U.A.M. D.T. nº 15. February 2006
Fahui Wang. Quantitative Methods and Applications in GIS, CRC Press, London, 2006.
J.Keith, Spatial Autocorrelation: A Statistician's Reflections, In: Luc Anselin & Sergio J.Rey , Perspectives on Spatial Data Analysis, Springer , Heidelberg , 2010.
Lauren M. Scott & Mark V.Janikas. Spatial statistics in ArcGIS , In: Manfred M.Fischer & Arther Getis (eds). Handbook of Applied Spatial analysis, Springer, Heidelberg, 2010.
Manfred M.Fischer , Martin Reismann & Thomas Scherngerll. Spatial Interaction and Autocorrelation, In: Luc Anselin & Sergio J.Rey . Perspectives Spatial Data analysis, Springer, Heidelberg, London.2010.
Michael Jde.Smith, Michael F.Goodchild , Paul A.Longley . Geospatial analysis comprehensive guide to principles techniques and software tools ,Second Edition, Winche Sea Press, US.2007.
Mitchell, Andy.The ESRI Guide to GIS Analysis, Volume 2: Spatial Measurements & Statistics ESRI Press, Redland. California, 2005.
Peter A.Rogerson . Statistical methods for geography, SAGA, Publication, London, 2001.
Rachel Guillain and Julie Le Gallo. Employment Density in Ile-de-France : Evidence from Local Regression , In : Antonio Pa'ez, Ron N. Buliung, Julie Le Gallo, and Sandy Dall'erba . Progress in Spatial Analysis, Methods and Applications, Springer,Heidelberg, 2010 .
S. Fotheringham,A, C. Brunsdon and M. E. Charlton, “Geographically Weighted Regression, the A Spatially Varying Relationships,” John Wiley and Sons, Ltd., Hoboken, 2002.
S. Fotheringham,A, C. Brunsdon, and M. Charlton. Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. John Wiley & Sons, Chichester, 2002.
S.Fotheringham,A . Brunsdon,CH.,& Cherlton,M. Quantitative Geography Perspectives on Spatial Data Analysis. SAGE Publication. Ltd. London.2007.
Sullivan, Daivd.O, & Unwin,Daivd .Geographical Information Analysis. John Wiley & Sons. New Jersey.2003.
المصادر باللغة العربية :
جمهورية العراق ،وزارة التخطيط ،الهيئة العليا للتعداد العام للسكان والمساكن (2009) ،خلاصة تحديث وحصر المباني والأسر في محافظات دهوك وابيل والسليمانية (غير منشورة).
يمان سنكري ، (اعداد وترجمة) ، التحليل الاحصائي للبيانات المكانية في نظم المعلومات الجغرافية،
المراجعة العلمية : المهندس عبد الله كامل ، شعاع للنشر والعلوم ، حلب-سوريا، 2008 .
نعمان شحادة ، التحليل الاحصائي في الجغرافيا والعلوم الاجتماعية ، دار صفاء ، عمان -الاردن, 2011.
Andrew O. Finley, Comparing spatially-varying coefficients models for analysis of ecological data with non-stationary and anisotropic residual dependence, Methods in Ecology and Evolution 2011, 2, 143–154. doi: 10.1111/j.2041-210X.2010.00060.x
Bo Huanga, Bo Wub and Michael Barryc “Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices, International Journal of Geographical Information Science, Vol. 24, No. 3, March 2010, 383–401.
Chia-Hsien Lin and Tzai-Hung Wen, Using Geographically Weighted Regression (GWR) to Explore Spatial Varying Relationships of Immature Mosquitoes and Human Densities with the Incidence of Dengue, International Journal of Environmental Research and Public Health, 2011, 8, 2798-2815; doi:10.3390/ijerph8072798 www.mdpi.com/journal/ijerph
Chris Brunsdon , A.Stewart Fotheringham & Martin E.Charlton. Geographically Weighted Regression: A Method for Exploration Spatial Nonstationarity , Geographical Analysis ,Vol,28,No.4.1996.pp.281-298.
Chunrong Jia , Wesley James and Satish Kedia, Relationship of Racial Composition and Cancer Risks from Air Toxics Exposure in Memphis, Tennessee, U.S.A., International Journal of Environmental Research and Public Health, 2014, 11, 7713-7724; doi:10.3390/ijerph110807713. http://www.mdpi.com/journal/ijerph
Felix Ndidi Nkeki & Animam Beecroft Osirike,GIS-Based Local Spatial Statistical Model of Cholera Occurrence: Using Geographically Weighted Regression , Journal of Geographic Information System, 2013, 5, 531-532 http://dx.doi.org/10.4236/jgis.2013.56050
Felix Ndidi Nkeki , Animam Beecroft Osirike, GIS-Based Local Spatial Statistical Model of Cholera Occurrence: Using Geographically Weighted Regression , Journal of Geographic Information System, 2013, 5, 531-542. http://dx.doi.org/10.4236/jgis.2013.56050
Foody, G. (2004) spatial nonstationarity and scale-dependency in the relationship between species richness and environmental determinants for the sub-Saharan endemic avifauna. Global Ecology and Biogeography, 13, 315–320.
Gang Lin, Jingying Fu, Dong Jiang , Wensheng Hu , Donglin Dong , Yaohuan Huang , and Mingdong Zhao , Spatio-Temporal Variation of PM2.5 Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China, International Journal of Environmental Research and Public Health, 2014, 11, 173-186; doi:10.3390/ijerph110100173 http://www.mdpi.com/journal/ijerph
Guo, L., Ma, Z. & Zhang, L. (2008) Comparison of bandwidth selection in application of geographically weighted regression: a case study. Canadian Journal of Forest Research, 38, 2526–2534.
J. Mart´ınez-Fern´andez , E. Chuvieco , and N. Koutsias , Modelling long-term fire occurrence factors in Spain by accounting for local variations with geographically weighted regression, Natural Hazards and Earth System Sciences, 13, 311–327, 2013,doi:10.5194/nhess-13-311-2013 www.nat-hazards-earth-syst-sci.net/13/311/2013/
Jie Gao , Zhijie Zhang , Yi Hu , Jianchao Bian , Wen Jiang , Xiaoming Wang ,Liqian Sun , and Qingwu Jiang , Geographical Distribution Patterns of Iodine in Drinking-Water and Its Associations with Geological Factors in Shandong Province, China, International Journal of Environmental Research and Public Health, 2014, 11(5), 5431-5444; doi:10.3390/ijerph110505431 .http://www.mdpi.com/journal/ijerph
Khalid Al-Ahmadi , and Ali Al-Zahrani , Spatial Autocorrelation of Cancer Incidence in Saudi Arabia, International Journal of Environmental Research and Public Health, 2013, 10, 7207-7228; doi:10.3390/ijerph10127207 http://www.mdpi.com/journal/ijerph
Khalid Al-Ahmadi , and Ali Al-Zahrani , NO2 and Cancer Incidence in Saudi Arabia, International Journal of Environmental Research and Public Health, 2013, 10(11), 5844-5862; doi:10.3390/ijerph10115844 . http://www.mdpi.com/journal/ijerph
Mahdi-Salim Saib , Julien Caudeville , Florence Carre , Olivier Ganry , Alain Trugeon , and Andre Cicolella , Spatial Relationship Quantification between Environmental, Socioeconomic and Health Data at Different Geographic Levels, International Journal of Environmental Research and Public Health, 2014, 11, 3765-3786; doi:10.3390/ijerph110403765. http://www.mdpi.com/journal/ijerph
Noresah Mohd Shariff , 1Sanjay Gairola, Anita Talib . Modelling Urban Land Use Change Using Geographically Weighted Regression and the Implications for Sustainable Environmental Planning, International Environmental Modelling and Software Society (iEMSs) 2010 International Congress on Environmental Modelling and Software , Modelling for Environment’s Sake, Fifth Biennial Meeting, Ottawa, Canada , David A. Swayne, Wanhong Yang, A. A. Voinov, A. Rizzoli, T. Filatova (Eds.)
http://www.iemss.org/iemss2010/index.php?n=Main.Proceedings
Paul Holloway and Jennifer A. Miller , Exploring Spatial Scale, Autocorrelation and Nonstationarity of Bird Species Richness Patterns, International Journal of Geo-Information, 2015, 4, 783-798; doi:10.3390/ijgi4020783 http://www.mdpi.com/journal/ijgi
Pavel Propastin, Martin Kappas and Stefan Erasmi, Application of Geographically Weighted Regression to Investigate the Impact of Scale on Prediction Uncertainty by Modelling Relationship between Vegetation and Climate, International Journal of Spatial Data Infrastructures Research, 2008, Vol. 3, 73-94 . DOI: 10.2902/1725-0463.2008.03.art6
Peili Duan, Lijie Qin 1, Yeqiao Wang and Hongshi He , Spatiotemporal Correlations between Water Footprint and Agricultural Inputs: A Case Study of Maize Production in Northeast China, Water 2015, 7, 4026-4040; doi:10.3390/w708402 . http://www.mdpi.com/journal/water
S H M Arshad1, J Jaafar, M Z Z Abiden, Z A Latif and A R A Rasam , Spatial stochastic regression modelling of urban land use : 8th International Symposium of the Digital Earth (ISDE8) doi:10.1088/1755-1315/18/1/012170 http://www.healthunit.org
Shujuan Li , Hongyan Ren , Wensheng Hu 3, Liang Lu , Xinliang Xu , Dafang Zhuang andQiyong Liu , Spatiotemporal Heterogeneity Analysis of Hemorrhagic Fever with Renal Syndrome in China Using Geographically Weighted Regression Models, International Journal of Environmental Research and Public Health, 2014, 11, 12129-12147; doi:10.3390/ijerph111212129. http://www.mdpi.com/journal/ijerph
Stephen A. Matthews & Tse-Chuan Yang.Mapping the results of local statistics: Using geographically weighted regression, DEMOGRAPHIC RESEARCH ,VOLUME 26, ARTICLE 6, PAGES 151-166 ,PUBLISHED 02 MARCH 2012 http: DOI: 10.4054/DemRes.2012.26.6 www.demographic-research.org/Volumes/Vol26/6/
Tayyab Ikram Shah and Scott Bell, Exploring the Intra-Urban Variations in the Relationship among Geographic Accessibility to PHC Services and Socio-demographic Factors, Conference’HealthGIS 13, November 5–8, 2013, Orlando, Florida USA.
Ubydul Haque, Lauren M Scott, Masahiro Hashizume, Emily Fisher, Rashidul Haque, Taro Yamamoto and Gregory E Glass6 , Modeling malaria treatment practices in Bangladesh using spatial statistics, Haque et al. Malaria Journal 2012, 11:63 http://www.malariajournal.com/content/11/1/63
Wenjuan Hou, Jiangbo Gao, Shaohong Wu , and Erfu Dai .Interannual Variations in Growing-Season NDVI and Its Correlation with Climate Variables in the Southwestern Karst Region of China, remote sensing, 2015, 7, 11105-11124, doi:10.3390/rs70911105 http://www.mdpi.com/journal/remotesensing
Wenyi Sun , Jianhua Gong , Jieping Zhou , Yanlin Zhao , Junxiang Tan ,Abdoul Nasser Ibrahim and Yang Zhou , A Spatial, Social and Environmental Study of Tuberculosis in China Using Statistical and GIS Technology, International Journal of Environmental Research and Public Health, 2015, 12, 1425-1448; doi:10.3390/ijerph120201425 http://www.mdpi.com/journal/ijerph
- الكتب باللغة الانكليزية :
Christopher D.LIoyd .Local Models for spatial analysis ,CRC Press , London, 2007.
Christopher D.LIoyd .Spatial Data Analysis An Introduction for GIS users, Oxford University Press , 2010.
Coro Chasco Yrigoyen , Isabel García Rodríguez, José Vicéns Otero , MODELING SPATIAL VARIATIONS IN HOUSEHOLD DISPOSABLE INCOME WITH GEOGRAPHICALLY WEIGHTED REGRESSION1, : Instituto L.R. Klein – Centro Gauss. U.A.M. D.T. nº 15. February 2006
Fahui Wang. Quantitative Methods and Applications in GIS, CRC Press, London, 2006.
J.Keith, Spatial Autocorrelation: A Statistician's Reflections, In: Luc Anselin & Sergio J.Rey , Perspectives on Spatial Data Analysis, Springer , Heidelberg , 2010.
Lauren M. Scott & Mark V.Janikas. Spatial statistics in ArcGIS , In: Manfred M.Fischer & Arther Getis (eds). Handbook of Applied Spatial analysis, Springer, Heidelberg, 2010.
Manfred M.Fischer , Martin Reismann & Thomas Scherngerll. Spatial Interaction and Autocorrelation, In: Luc Anselin & Sergio J.Rey . Perspectives Spatial Data analysis, Springer, Heidelberg, London.2010.
Michael Jde.Smith, Michael F.Goodchild , Paul A.Longley . Geospatial analysis comprehensive guide to principles techniques and software tools ,Second Edition, Winche Sea Press, US.2007.
Mitchell, Andy.The ESRI Guide to GIS Analysis, Volume 2: Spatial Measurements & Statistics ESRI Press, Redland. California, 2005.
Peter A.Rogerson . Statistical methods for geography, SAGA, Publication, London, 2001.
Rachel Guillain and Julie Le Gallo. Employment Density in Ile-de-France : Evidence from Local Regression , In : Antonio Pa'ez, Ron N. Buliung, Julie Le Gallo, and Sandy Dall'erba . Progress in Spatial Analysis, Methods and Applications, Springer,Heidelberg, 2010 .
S. Fotheringham,A, C. Brunsdon and M. E. Charlton, “Geographically Weighted Regression, the A Spatially Varying Relationships,” John Wiley and Sons, Ltd., Hoboken, 2002.
S. Fotheringham,A, C. Brunsdon, and M. Charlton. Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. John Wiley & Sons, Chichester, 2002.
S.Fotheringham,A . Brunsdon,CH.,& Cherlton,M. Quantitative Geography Perspectives on Spatial Data Analysis. SAGE Publication. Ltd. London.2007.
Sullivan, Daivd.O, & Unwin,Daivd .Geographical Information Analysis. John Wiley & Sons. New Jersey.2003.
المصادر باللغة العربية :
جمهورية العراق ،وزارة التخطيط ،الهيئة العليا للتعداد العام للسكان والمساكن (2009) ،خلاصة تحديث وحصر المباني والأسر في محافظات دهوك وابيل والسليمانية (غير منشورة).
يمان سنكري ، (اعداد وترجمة) ، التحليل الاحصائي للبيانات المكانية في نظم المعلومات الجغرافية،
المراجعة العلمية : المهندس عبد الله كامل ، شعاع للنشر والعلوم ، حلب-سوريا، 2008 .
نعمان شحادة ، التحليل الاحصائي في الجغرافيا والعلوم الاجتماعية ، دار صفاء ، عمان -الاردن, 2011.
التنزيلات
منشور
2017-08-01
كيفية الاقتباس
Abdullah, N. S. (2017). العوامل المحددة لتباين الكثافات السكانية داخل المدن باستخدام طريقتي التربيعات الصغرى العادية ال و ال اس والوزن التراجعي الجغرافي جي دبل يو ار. المجلة الأكاديمية لجامعة نوروز, 6(1), 19–37. https://doi.org/10.25007/ajnu.v6n1a10
إصدار
القسم
مقالات
الرخصة
بيان الحقوق الفكرية
حقوق التأليف
يوافق المؤلفون الذين ينشرون في هذه المجلة على المصطلحات التالية:
١. يحتفظ المؤلفون بحقوق الطبع والنشر ومنح حق المجلة في النشر الأول مع العمل المرخص له في نفس الوقت بموجب ترخيص المشاع الإبداعي [سيسي بي-نك-ند 4.0] الذي يسمح للآخرين بمشاركة العمل مع الإقرار بحقوق التأليف والنشر الأولي في هذه المجلة.
٢. يمكن للمؤلفين الدخول في ترتيبات تعاقدية إضافية منفصلة للتوزيع غير الحصري للنسخة المنشورة من المجلة من العمل (على سبيل المثال، نشرها في مستودع مؤسسي أو نشرها في كتاب) مع الإقرار بنسخة أولية نشر في هذه المجلة.
٣. يسمح للمؤلفين وتشجيعهم على نشر عملهم عبر الإنترنت (على سبيل المثال، في المستودعات المؤسسية أو على موقعهم على الويب) قبل وأثناء عملية التقديم، حيث يمكن أن يؤدي إلى التبادلات الإنتاجية، فضلا عن الاستشهاد المبكر والأكبر للعمل المنشورة ( انظر تأثير النفاذ المفتوح).
نقل حقوق الطبع والنشر
بيان الخصوصية
المجلة الأكاديمية لجامعة نوروز ملتزمة بحماية خصوصية مستخدمي موقع المجلة هذا. سيتم استخدام الأسماء والتفاصيل الشخصية وعناوين البريد الإلكتروني التي تم إدخالها في هذا الموقع الإلكتروني فقط للأغراض المعلنة لهذه المجلة ولن يتم إتاحتها لأطراف ثالثة بدون إذن المستخدم أو الإجراءات القانونية الواجبة. موافقة المستخدمين مطلوبة لتلقي الاتصالات من المجلة الأكاديمية لجامعة نوروز للأغراض المعلنة للمجلة. ويمكن توجيه الاستفسارات المتعلقة بالخصوص إلى [email protected]
