Konut fiyatlarını etkileyen parametrelerin çoklu regresyon analizi yöntemiyle irdelenmesi ve kentsel dönüşüme katkıları
Examination of parameters effecting the house prices by multiple regression analysis and its contributions to urban transformation
Yazar: BÜŞRA DURMUŞ
Danışman: PROF. DR. HAYRİ HAKAN DENLİ
İstanbul Teknik Üniversitesi / Fen Bilimleri Enstitüsü / Geomatik Mühendisliği Ana Bilim Dalı / Geomatik Mühendisliği Bilim Dalı
Derece: Yüksek Lisans, 2016
Konu: Jeodezi ve Fotogrametri = Geodesy and Photogrammetry

Özet:
Bu araştırma pilot bölge olarak İstanbul ili Ümraniye ilçesini kapsamaktadır. Çalışmanın amacı; konutların fiyatlarına etki edebilecek faktörleri çoklu regresyon analizi ile incelemek ve sonuçları ısı haritalarıyla görselleştirmektir. Çalışmada kullanılan veriler www.hurriyetemlak.com sitesinden temin edilerek Ümraniye geneline yayılan toplam 390 konut için fiziksel ve konumsal özellikleri baz alınarak değerlendirme yapılmıştır. 
Birinci bölümde üzerinde durulan konu tanımlanarak, çalışmanın amacı, kapsamı, yöntemi ve çalışma ile ilgili hipotezler aktarılmıştır.
İkinci bölümde konu ile ilgili yabancı kaynaklar ve Türkiye' de yapılmış olan çalışmalar irdelenerek, konu ile ilgili farklı bakış açıları ve gözlemler hakkında bilgi edinilmiştir 
Üçüncü bölümde konut fiyatlarını etkileyen fiziksel ve konumsal faktörler teorik olarak incelenerek konut tanımı üzerinde durulmuştur.
Dördüncü bölümde seçilen fiziksel ve çevresel faktörlerin konut fiyatları üzerindeki etkileri regresyon analizi ile araştırılarak üç farklı model kurulmuş ve modellerden elde edilen analizlerin sonuçları irdelenerek kıyaslanmıştır.
Beşinci bölümde değer haritalarının oluşturulmaları açıklanmıştır. Haritaların oluşturulmasında kullanılan yöntem ve elde edilen haritalar gösterilmiştir. Ayrıca elde edilen haritaların güvenilirliği test edilmiştir.
Altıncı bölümde elde edilen değer haritalarından metrekare birim fiyat haritası, kentsel dönüşüm uygulamalarında kullanılabilirliği açısından örnek gösterilerek değer haritalarına farklı bir yaklaşım getirilmiştir.
Son bölümde sonuç olarak, yapılan çalışmalar sonucunda elde edilen bulgular değerlendirilmiş, öneriler geliştirilmiştir.
Konutların fiyatlarına etki eden fiziksel faktörler olarak konutun; yaşı, sahip olduğu oda sayısı, metrekaresi, bulunduğu binanın kat adedi ve yer aldığı kat olarak alınmıştır. Konumsal faktörler olarak ise: konutun kendisine en yakın; hastaneye, okula, parka ve karakola uzaklıkları alınmıştır. Toplamda konumsal ve fiziksel olmak üzere 10 adet parametre regresyon analizi ile incelenmiştir. 
Regresyon analizi sonrası Ümraniye ilçesi için değer haritaları oluşturulmuştur. Değer haritaları olarak fiyat haritası, metrekare birim fiyat haritası ve yaş haritaları oluşturulmuştur. 
Oluşturulan haritalardan metrekare birim fiyat haritasının kentsel dönüşüm uygulamalarında kullanılabilirliği araştırılıp farklı bir uygulama geliştirilmiştir. Metrekare birim fiyat haritası ile 15 yıl üzeri yaşlı konutlar haritası üst üste getirilerek ilçede kentsel dönüşüm yapılması durumunda öncelik verilmesi gereken binalar belirlenmiş, kentsel dönüşüme farklı ve yeni bir yorum getirilmiştir.
Araştırmanın sonuçları, gayrimenkul yatırımcılarının ve alıcıların doğru karar vermelerinde ve yerel yönetimin şehrin yapılanmasını etkileyecek donatı alanlarının yer seçimi kararını daha doğru vermelerinde faydalı olacaktır. 
Bu tez çalışması 2016 yılı verilerek kullanılarak gerçekleştirilmiştir.

Abstract:
Land,lan, buildings, offices, housing, immovable property such as factories considered. Immovable land, shop, apartment, villa or know about it as possible without causing harm to the self as a place to move the property from a place that can not be identified with more housing. Because housing, housing is a vital tool that eliminates the need for a high added value economic malt.
Value for the needs beside the immovable properties is a concept which vary according to the severity of the moment, factors affecting the value when determining the real value varies according to local characteristics, also said the current definitive model for each region has changed the perspective on the factors that affect the value of the people living in that area it is difficult.
Value is an economic concept consist of an appreciation of the likely price to be paid for goods and services in a given time based on a specific definition of values is not real data. The concept of value in economic terms, the property on the date of valuation owner or service areas reflects the opinion of the market about the benefits accrued to the person.
Valuation of immovable property and be reflected in the value of the tax is one of the most important economic resources of the developed countries. However, our country still has not established an ideal real estate valuation system, and prune the collection of taxes leads to various problems.
The real estate valuation, "put together by combining the processing of the factors affecting the value and processed based on the data unit as the determination of prices according to market conditions" are defined.
Positional will affect the real value of real estate for valuation should be collected, such as physical characteristics. The data collected by selecting an appropriate value method grouped according to the characteristics of the property value calculation process is completed.
In the real estate market, and every real or sold or leased. by many criteria at the property valuation analysis it developed many approaches to determining its impact on the land value.
Today, real estate property valuation is done by basically 3 methods. These; imputed income and are cost method. In recent years, other techniques developed as a stochastic valuation methods (statistical) is a valuation method.
Multiple linear regression models, one of stochastic methods have been applied in this study. The price is a concept related to the exchange of goods or services. Prices for goods.
It is desirable to amounts paid or offered. After the exchange is performed, the disclosure describes asks whether prices will become no longer a real historical character. 
The aim of this thesis is examining the multiple linear regression analysis using as an example the properties of a selected area and worth the price of housing in the creation of the map. per m² per year to be a rapid increase in prices of houses for sale and 25% due to the work of the third district of Istanbul, the most populous province in terms of population of Istanbul was chosen as the study of Umraniye district. The identification of factors affecting the price of housing in Umraniye district, which has a population of approximately 600000.00 is expected to provide a significant contribution to the Ümraniye housing market.
In this study, the structural characteristics of the building and found housing, environment variables have been examined closer.
Using parameters that affect housing prices, GIS-based map Netcad program with price square meter unit price map map was constructed and age. prospectively related to immovable created using value maps can be informed about fair value are elderly housing in studies to investigate where the cluttering it and a possible earthquake focus will be agreed to be given to building in which the region's priorities during the urban renewal operation.
In this study, a base for housing sales in the next period of Umraniye district has tried to be created work implemented at the local level, increasing the number of samples can be applied at national level if desired.
Factors affecting the price of housing in the study, due to a heterogeneous concept of housing is not only dealt with the physical properties of the spatial features. Only residential real estate, which is only for sale as a residential apartment building if the notices have been selected. Further hypotheses are as follows:
There are social and physical properties that affect housing prices:
	Factors affecting the price of residential housing and the expected properties can vary depending on the environment where the housing.
	The most important factor affecting the size in terms of m² residential housing prices.
	Housing around hospitals, schools, social facilities such as parking and proximity to the station or from the affects housing prices.
This thesis firstly preparing a thesis that have been made previously in similar topics, research, articles are examined, the information related to the topic of the thesis and the comments in the light of the literature was conducted. In literature Turkey was to investigate the factors that affect housing prices have been increasing their work after the year 2012.
Examined in similar studies in the world and the literature is given.
After the analysis has been made compared to the value generated maps and analysis of results for the selected operation.
The method of operation; done the research literature on the conceptual and theoretical aspects related to immovable property valuation concepts and the study of the factors that affect housing sales price determined in 2016 by regression analysis to investigate the effects on housing prices. Creating maps of various values according to the value of housing prices, which have been obtained served as a base will easily understand the value created by interpreting the ring and valuation professionals map.
In the study, the province of Istanbul Ümraniye district across spatial and non-spatial variety of data (physical data) taking advantage of the factors affecting the price of houses assessed with multiple linear regression analysis and found an overall housing equation to determine the price of housing in the Umraniye district.
The scope of work consists of seven separate section of the thesis:
	Defining the focus of the first part, the purpose of the study, scope, methodology and hypotheses regarding the work has been transferred.
	Foreign sources on the subject in the second part, and Turkey made the studies examined were informed about the different perspectives and observations on the subject
	Physical and spatial factors affecting housing prices in the third part focuses on the definition of residential examined theoretically.
	Impact on house prices in the fourth chapter of the physical and environmental factors investigated by regression analysis of the selected set of three different models were compared and examined the results of the analysis obtained from the model.
	In the fifth chapter describes their creation of value map. Method used in the creation of maps, and the resulting map is shown. Also tested the reliability of the map is obtained.
	The value obtained from the map unit price of square meter in the sixth section of the map, showing the example of the availability of urban transformation brought a different approach to application value map.
	In the last chapter, as a result, studies have assessed the findings obtained as a result, proposals have been developed.
The evaluation of real properties is a field which is being worked on constantly by developing countries as well as by developed countries. The changing value of real properties in the transformation process in which the agricultural land turn into urban estates, is a big question mark, not only for the owners of the lands but also for the legislators who try to solve this problem.
Our research seeks to understand how homebuyers and their affinity for certain characteristics of housing have changed over the course of this dramatic drop in the real estate market. What characteristics of housing contribute to the overall value of a residential property in a good economy and is this the same or different in a bad economy? Additionally, why do some houses maintain a fairly consistent value in an economic downturn and why do others experience a decrease?
The purpose of this study is to formulate some particular problems of housing which appear within an area bounded by three important developments of contemporary societies; and to give information on design methods necessary for solving them.
Results of the study will be useful in the real estate investors and buyers in making the right decision and the decision to more accurately place the choice of reinforcing areas that affect the structure of the city's local government.
This study was conducted using the given data during 2016.