Land Price Forecasting Research by Macro and Micro Factors and Real Estate Market Utilization Plan Research by Landscape Factors: Big Data Analysis Approach

In real estate, there are various variables for the forecasting of future land prices, in addition to the macro and micro perspectives used in the current research. Examples of such variables are the economic growth rate, unemployment rate, regional development and important locations, and transport...

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Main Authors: Sang-Hyang Lee, Jae-Hwan Kim, Jun-Ho Huh
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Symmetry
Subjects:
Online Access:https://www.mdpi.com/2073-8994/13/4/616
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author Sang-Hyang Lee
Jae-Hwan Kim
Jun-Ho Huh
author_facet Sang-Hyang Lee
Jae-Hwan Kim
Jun-Ho Huh
author_sort Sang-Hyang Lee
collection DOAJ
description In real estate, there are various variables for the forecasting of future land prices, in addition to the macro and micro perspectives used in the current research. Examples of such variables are the economic growth rate, unemployment rate, regional development and important locations, and transportation. Therefore, in this paper, data on real estate and national price fluctuation rates were used to predict the ways in which future land prices will fluctuate, and macro and micro perspective variables were actively utilized in order to conduct land analysis based on Big Data analysis. We sought to understand what kinds of variables directly affect the fluctuation of the land, and to use this for future land price analysis. In addition to the two variables mentioned above, the factor of the landscape was also confirmed to be closely related to the real estate market. Therefore, in order to check the correlation between the landscape and the real estate market, we will examine the factors which change the land price in the landscape district, and then discuss how the landscape and real estate can interact. As a result, re-explaining the previous contents, the future land price is predicted by actively utilizing macro and micro variables in real estate land price prediction. Through this method, we want to increase the accuracy of the real estate market, which is difficult to predict, and we hope that it will be useful in the real estate market in the future.
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spelling doaj.art-c886dada90314c2e91dd08d7cedf827a2023-11-21T14:31:19ZengMDPI AGSymmetry2073-89942021-04-0113461610.3390/sym13040616Land Price Forecasting Research by Macro and Micro Factors and Real Estate Market Utilization Plan Research by Landscape Factors: Big Data Analysis ApproachSang-Hyang Lee0Jae-Hwan Kim1Jun-Ho Huh2Department of Data Informatics, (National) Korea Maritime and Ocean University, Busan 49112, KoreaDepartment of Data Informatics, (National) Korea Maritime and Ocean University, Busan 49112, KoreaDepartment of Data Informatics, (National) Korea Maritime and Ocean University, Busan 49112, KoreaIn real estate, there are various variables for the forecasting of future land prices, in addition to the macro and micro perspectives used in the current research. Examples of such variables are the economic growth rate, unemployment rate, regional development and important locations, and transportation. Therefore, in this paper, data on real estate and national price fluctuation rates were used to predict the ways in which future land prices will fluctuate, and macro and micro perspective variables were actively utilized in order to conduct land analysis based on Big Data analysis. We sought to understand what kinds of variables directly affect the fluctuation of the land, and to use this for future land price analysis. In addition to the two variables mentioned above, the factor of the landscape was also confirmed to be closely related to the real estate market. Therefore, in order to check the correlation between the landscape and the real estate market, we will examine the factors which change the land price in the landscape district, and then discuss how the landscape and real estate can interact. As a result, re-explaining the previous contents, the future land price is predicted by actively utilizing macro and micro variables in real estate land price prediction. Through this method, we want to increase the accuracy of the real estate market, which is difficult to predict, and we hope that it will be useful in the real estate market in the future.https://www.mdpi.com/2073-8994/13/4/616landscapemicro factormacro factorreal estate marketBig Data analysisBig Data
spellingShingle Sang-Hyang Lee
Jae-Hwan Kim
Jun-Ho Huh
Land Price Forecasting Research by Macro and Micro Factors and Real Estate Market Utilization Plan Research by Landscape Factors: Big Data Analysis Approach
Symmetry
landscape
micro factor
macro factor
real estate market
Big Data analysis
Big Data
title Land Price Forecasting Research by Macro and Micro Factors and Real Estate Market Utilization Plan Research by Landscape Factors: Big Data Analysis Approach
title_full Land Price Forecasting Research by Macro and Micro Factors and Real Estate Market Utilization Plan Research by Landscape Factors: Big Data Analysis Approach
title_fullStr Land Price Forecasting Research by Macro and Micro Factors and Real Estate Market Utilization Plan Research by Landscape Factors: Big Data Analysis Approach
title_full_unstemmed Land Price Forecasting Research by Macro and Micro Factors and Real Estate Market Utilization Plan Research by Landscape Factors: Big Data Analysis Approach
title_short Land Price Forecasting Research by Macro and Micro Factors and Real Estate Market Utilization Plan Research by Landscape Factors: Big Data Analysis Approach
title_sort land price forecasting research by macro and micro factors and real estate market utilization plan research by landscape factors big data analysis approach
topic landscape
micro factor
macro factor
real estate market
Big Data analysis
Big Data
url https://www.mdpi.com/2073-8994/13/4/616
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AT jaehwankim landpriceforecastingresearchbymacroandmicrofactorsandrealestatemarketutilizationplanresearchbylandscapefactorsbigdataanalysisapproach
AT junhohuh landpriceforecastingresearchbymacroandmicrofactorsandrealestatemarketutilizationplanresearchbylandscapefactorsbigdataanalysisapproach