Spatial Analysis of Residential Land Price in Urban Area of Jimo City Based on GIS

DOI

10.2991/icache-16.2016.22How to use a DOI?

Keywords

spatial analysis; residential land price; urban area; GIS

Abstract

In this paper, land prices of the 234sample points are chosen from the collected bargaining points in Jimo city by using the approaches of market comparison, residual and income. Then, SPSS is applied to carry out normality tests of the sample data and eliminate the outlier data. The trend of land price and spatial interpolation of remaining sample data are depicted with the help of GIS, respectively. The results show that apart from the forth level land, the land price of total samples follows normal distribution, and it is more realistic to use the combination of Q-Q figure and level grading to eliminate the abnormal points. Meanwhile, the spatial distribution of residential land price basically follows the rules that the land price decreases from the city center to the outside area. It is the highest in the city center. Moreover, the land price changes slower in the latitudinal direction than in the longitudinal direction, and both of them follows quadratic parabola. The obtained results conform with the reality in Jimo city, which can be helpful in the management of estate price to avoid malicious overestimation or underestimation.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ming Li Chen
AU  - Shu Jian He
AU  - Ji Fang Cui
AU  - Xiao Guang Zhang
AU  - Pei Ru Liu
AU  - Rui Hao
PY  - 2016/11
DA  - 2016/11
TI  - Spatial Analysis of Residential Land Price in Urban Area of Jimo City Based on GIS
BT  - Proceedings of the 2016 2nd International Conference on Architectural, Civil and Hydraulics Engineering (ICACHE 2016)
PB  - Atlantis Press
SP  - 108
EP  - 112
SN  - 2352-5401
UR  - https://doi.org/10.2991/icache-16.2016.22
DO  - 10.2991/icache-16.2016.22
ID  - Chen2016/11
ER  -