Application GIS technology to determine the land price in Ward 10, District 8, Ho Chi Minh City

Determination of land price is one of the most important land management roles. Land prices and changes of land prices are evident in the real estate market. The real estate market plays an important role in the economy of Vietnam. Recently, when the population is increasing, leading to increased housing demand. The distribution of the population is concentrated in big cities. Then the demand for land information, especially land prices are always interested by people. However, real information on land price is always lacking and virtual. If people want the real estate market to develop well, information on land price must be clear and adequate. The land price area map satisfies those requirements. Land price zone map helps managers about land effectively and the land price map also helps the people - participants in the real estate market to grasp the most reliable information of land prices. GIS technology is applied in the paper to zone land prices using land price information collecting in Ward 10, District 8, Ho Chi Minh City

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

Symmetry ◽

10.3390/sym13040616 ◽

2021 ◽

Vol 13 (4) ◽

pp. 616

Author(s):

Sang-Hyang Lee ◽

Jae-Hwan Kim ◽

Jun-Ho Huh

Keyword(s):

Big Data ◽

Data Analysis ◽

Real Estate ◽

Big Data Analysis ◽

Real Estate Market ◽

Land Price ◽

The Real ◽

The Real Estate ◽

Land Prices ◽

The Real Estate Market

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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