Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Investigation of housing valuation models based on spatial and non-spatial techniques
Download
index.pdf
Date
2015
Author
Boza, Ertuğrul
Metadata
Show full item record
Item Usage Stats
233
views
259
downloads
Cite This
The aim of this thesis is to develop hedonic housing valuation models based on spatial (SAR-simultaneous spatial autoregression and GWR - geographically weighted regression) and non-spatial (OLS - ordinary least squares) techniques, to compare the performances of these models and to investigate significant factors affecting housing value. The developed housing valuation models were tested at the Çankaya and Keçiören districts of Ankara province, Turkey. The results of the analyses revealed that significant spatial non-stationarity exists between the dependent and independent variables. A semi-logarithmic hedonic model was used in order to interpret the coefficients easily and minimize the problem of heteroscedasticity. The results show that Area, Security and Distance to Shopping Center are common significant factors for both Çankaya and Keçiören districts in Ankara. Other important factors are the Type of Property and Distance to Subway for Çankaya and the Floor and Household variables for Keçiören. The SAR and the GWR spatial models gave a better approximation to the observed house values than the traditional non-spatial regression model. The SAR model showed the best performance in Çankaya and the GWR model indicated high performance in Keçiören. The GWR maps displayed the variation of the coefficients of each variable clearly.
Subject Keywords
Housing
,
Housing
,
Geospatial data.
,
Geographic information systems.
URI
http://etd.lib.metu.edu.tr/upload/12618846/index.pdf
https://hdl.handle.net/11511/24722
Collections
Graduate School of Natural and Applied Sciences, Thesis
Suggestions
OpenMETU
Core
The dynamics of the differentiation of housing production in metropolitan areas: the case of Eskişehir
Aslaner, Arzu; Balaban, Osman; Department of City and Regional Planning (2019)
The aim of this study is to determine the factors affecting the housing production processes in Eskişehir and the effects of these processes on the existing urban development dynamics. Similar to the growth trend across the country, there has been a growth in construction investments, especially in new housing production in Eskişehir after 2000. In addition, metropolitan districts, namely Tepebaşı and Odunpazarı, dominate the total new housing production in the city. In this regard, focusing on the period a...
Atmospheric correction and image classification on MODIS images by nonparametric regression splines
Kuter, Semih; Düzgün, H. Şebnem; Işık, Oğuz; Department of Geodetic and Geographical Information Technologies (2014)
In this study, two novel applications of nonparametric regression splines are introduced within the frame of remote sensing: (i) For the first time ever, atmospheric correction models are generated for moderate resolution imaging spectroradiometer (MODIS) images by using multivariate adaptive regression splines (MARS), and its recently introduced version, conic multivariate adaptive regression splines (CMARS). The obtained models are applied on the predefined test areas of twenty four different MODIS scenes...
Development of free/libre and open source spatial data analysis system fully coupled with geographic information system
Kepoğlu, Volkan Osman; Düzgün, H. Şebnem; Department of Geodetic and Geographical Information Technologies (2011)
Spatial Data Analysis (SDA) is relatively narrower and constitutes one of the areas of Spatial Analysis. Geographic Information System (GIS) offers a potentially valuable platform for supporting SDA techniques. Integration of SDA with GIS helps SDA to benefit from the data input, storage, retrieval, data manipulation and display capabilities of GIS. Also, GIS can benefit from SDA techniques in which the integration of these techniques can increase the analysis capabilities of GIS. This integration serves fo...
A fuzzy software prototype for spatial phenomena: case study precipitation distribution
Yanar, Tahsin Alp; Akyürek, Sevda Zuhal; Department of Geodetic and Geographical Information Technologies (2010)
As the complexity of a spatial phenomenon increases, traditional modeling becomes impractical. Alternatively, data-driven modeling, which is based on the analysis of data characterizing the phenomena, can be used. In this thesis, the generation of understandable and reliable spatial models using observational data is addressed. An interpretability oriented data-driven fuzzy modeling approach is proposed. The methodology is based on construction of fuzzy models from data, tuning and fuzzy model simplificatio...
Analysis of correlated circular and extremal data with a flexible cylindrical distribution
Kalaylıoğlu Akyıldız, Zeynep Işıl (2021-08-01)
In this article, we introduce a flexible cylindrical distribution for modeling and analysis of dependent extremal and directional observations. The distribution can be used to investigate the connection between two related phenomena, such as the daily fastest wind speed and its direction. The proposed model is applicable for the analysis of a wide variety of cylindrical data, including datasets with asymmetrically distributed directional observations. The model enjoys the advantages of interpretable model p...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
E. Boza, “Investigation of housing valuation models based on spatial and non-spatial techniques,” Ph.D. - Doctoral Program, Middle East Technical University, 2015.