Urban growth analysis using spatial and temporal data
نویسندگان
چکیده
منابع مشابه
Urban Growth Analyses Using Spatial and Temporal Data
Urban growth identification, quantification, and the knowledge of rate and trends of growth would help in regional planning with better infrastructure in environmentally sound way. This requires analyses of spatial and temporal data, which can be done with the help of spatial and temporal technologies such as Remote Sensing, Geographic Information System (GIS) and Global Positioning System (GPS...
متن کاملMeasuring spatial - temporal of Yazd urban form using spatial metrics
Abstract Urban form can be affected by diverse factors in different times. Socio- economic, political and physical factors are among the main contributors. So, one of the most important challenges of urban planners is measuring and identifying urban development pattern in order to direct and strengthen it to sustainable pattern and right direction. The case study of the present paper is the ...
متن کاملSpatial zoning and spatial analysis of urban poverty using spatial analysis (Case study: Mashhad city)
Spatial Zoning and Analysis of Urban Poverty via Spatial Analysis (Case Study: Mashhad City) Abstract Examining the degree of poverty in every community is the first step taken towards planning for fighting against poverty and deprivation. With understanding the poverty change process over time, planners can make the necessary decisions. The present study aims to investigate the spatial z...
متن کاملSpatial zoning and spatial analysis of urban poverty using spatial analysis (Case study: Mashhad city)
Spatial Zoning and Analysis of Urban Poverty via Spatial Analysis (Case Study: Mashhad City) Abstract Examining the degree of poverty in every community is the first step taken towards planning for fighting against poverty and deprivation. With understanding the poverty change process over time, planners can make the necessary decisions. The present study aims to investigate the spatial z...
متن کاملImproving the Performance of ICA Algorithm for fMRI Simulated Data Analysis Using Temporal and Spatial Filters in the Preprocessing Phase
Introduction: The accuracy of analyzing Functional MRI (fMRI) data is usually decreases in the presence of noise and artifact sources. A common solution in for analyzing fMRI data having high noise is to use suitable preprocessing methods with the aim of data denoising. Some effects of preprocessing methods on the parametric methods such as general linear model (GLM) have previously been evalua...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of the Indian Society of Remote Sensing
سال: 2003
ISSN: 0255-660X,0974-3006
DOI: 10.1007/bf03007350