Surveying the Impact of High Building on Housing Price (Case Study: Region 9,Mashhad)

جغرافیاوتوسعه ناحیه ای

Articles in Press, Accepted Manuscript, Available Online from 10 March 2021   

Document Type: Research

DOI: 10.22067/jgrd.2021.47294.0

Authors

nazanin bagheri azghadi^* ; Mohamadrahim rahnama

ferdowsi univercity of mashhad

Abstract

Today, housing is a basic need for households and is seen as an economic good. Housing price is the most basic variable of housing sector and is subordinate of various factors and conditions. One of the factors that could affect the housing price is high building. Therefore, the aim of this research is to survey the impact of high building on housing price in an area of region 9, Mashhad where high building has more growth than other parts. To understand the impact of high building on fluctuations of apartment house price has been done to collect housing price from Khorasan newspaper and websites of real state, from 1385, namely the year before starting the high building, to 1393. In this study, to do required analyses has been used Arc GIS software to draw maps, profiles and Excel to draw diagrams. In addition to find out minimum and maximum of house price in an area, has been used Spatial Analyst in GIS.
The Regression analysis such as (OLS), also has been used to understand the effectiveness of other used factors in which apartment house price as dependent variable and seven indicators that are: Distance from Vakil Abad boulevard, crossing width, piece sizes, distance from high building collections, distance from health centers and distance from some special land use such as factory and other land uses have been considered as dependent variable.
Result showed that house price has been increased simultaneously tall building in area from 1386 and 400 meters distance is maximum distance that high building effect on house price. Also, the results of regression model indicate that independent variables respectively are: distance from Vakil Abad boulevard, crossing width, pieces sizes, distance from high building collections and distance from factory, have direct and positive relation with house price and health centers and distance from watercourse have negative and reverse relation with house price.

References