Urban growth pattern modeling using logistic regression
نویسندگان
چکیده
منابع مشابه
Analysis of urban growth pattern using logistic regression modeling, spatial autocorrelation and fractal analysis Case study: Ahvaz city
Transformation of land use-land cover change occurs due to the numbers and activities of people. Urban growth modeling has attracted authentic attention because it helps to comprehend the mechanisms of land use change and thus helps relevant policies made. This study applied logistic regression to model urban growth in the Ahvaz Metropolitan Area of Khuzestan province in IDRISI Selva software a...
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This study applied logistic regression to model urban growth in the Atlanta Metropolitan Area of Georgia in a GIS environment and to discover the relationship between urban growth and the driving forces. Historical land use/cover data of Atlanta were extracted from the 1987 and 1997 Landsat TM images. Multi-resolution calibration of a series of logistic regression models was conducted from 50 m...
متن کاملanalysis of urban growth pattern using logistic regression modeling, spatial autocorrelation and fractal analysis case study: ahvaz city
transformation of land use-land cover change occurs due to the numbers and activities of people. urban growth modeling has attracted authentic attention because it helps to comprehend the mechanisms of land use change and thus helps relevant policies made. this study applied logistic regression to model urban growth in the ahvaz metropolitan area of khuzestan province in idrisi selva software a...
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the logistic regression (lr) method, as an empirical estimation method, was used to model urban growth in gorgan city between the years 1987-2001. three groups of variables including social-economic, land use and biophysical variables were used. similarity among variables is probable. to remove the correlated variables, covariance was calculated and distance to administrative, sporting centers ...
متن کاملSteganalysis using logistic regression
We advocate Logistic Regression (LR) as an alternative to the Support Vector Machine (SVM) classifiers commonly used in steganalysis. LR offers more information than traditional SVM methods – it estimates class probabilities as well as providing a simple classification – and can be adapted more easily and efficiently for multiclass problems. Like SVM, LR can be kernelised for nonlinear classifi...
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ژورنال
عنوان ژورنال: Geo-spatial Information Science
سال: 2011
ISSN: 1009-5020,1993-5153
DOI: 10.1007/s11806-011-0427-x