To see the other types of publications on this topic, follow the link: Real Estate Market.; Spatial analyses; GIS.
Journal articles on the topic 'Real Estate Market.; Spatial analyses; GIS'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Real Estate Market.; Spatial analyses; GIS.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Erdoğan, Saffet, and Abdulkadir Memduhoğlu. "A spatiotemporal exploratory analysis of real estate sales in Turkey using GIS." Journal of European Real Estate Research 12, no. 2 (August 8, 2019): 207–26. http://dx.doi.org/10.1108/jerer-06-2018-0024.
Full textAbstract:
PurposeThe purpose of this paper is to examine the real estate sales in Turkey on a district basis to reveal the current state of real estate sales and any meaningful changes in the last period. The real estate market is important and is an indicator of the country’s general economic health, as real estate is seen as an investment.Design/methodology/approachAs a powerful method of spatial analysis and evaluation, geographic information systems have been used to examine real estate data in both spatial and temporal ways. In this study, 14 years of sales data covering the years 2004 to 2017 obtained from government agencies on a district basis were evaluated using spatiotemporal methods. Several maps were produced using Getis-Ord Gi* and local Moran’s I indices, which showed the spatiotemporal change of sales and sales rates.FindingsWhen looking at the maps, provinces such as Istanbul, Ankara, Izmir, Antalya and their surrounding districts have buoyant real estate markets compared to the other side of the country. Real estate sales are more stagnant in the eastern and northern parts of the country. In addition, the authors found that the growth rate of annual average real estate sales was approximately seven times higher than the annual average population growth.Originality/valueThis spatiotemporal study, which presents 14 years of performance data of the real estate market and, by extension, the economic situation, also highlights the regions that stand out for investment planning throughout the country. The results of spatiotemporal analysis also present a new way of real estate market visualization using maps with well-designed categorizations.
2
Bełej, Mirosław, and Marta Figurska. "3D Modeling of Discontinuity in the Spatial Distribution of Apartment Prices Using Voronoi Diagrams." Remote Sensing 12, no. 2 (January 9, 2020): 229. http://dx.doi.org/10.3390/rs12020229.
Full textAbstract:
An immanent feature of the housing market is a large spatial dispersion of real estate prices along with their simultaneous high stratification. Application of classic methods of data interpolation results in an excessive simplification of the outcome because of a conversion of the dispersed data sets into areas of spatial continuity by reducing the above-average real estate prices. The main aim of the article was to search for spatial discontinuities of real estate prices’ distribution with 3D modeling using Voronoi diagrams as a method of irregular division of this space. Used methods of geospatial analyses with GIS tools enabled to identify clusters of high housing market activity and to avoid an excessive generalization of data resulting from the reduction of the above-average real estate prices. The research was conducted for over 7000 real estate transactions in years 2010–2017 in Olsztyn, the capital city of Warmia and Mazury in Poland, resulting in a 3D visualization of real estate prices for the chosen market, including the discontinuity in their spatial distribution.
3
Zhang, Min Li, and Guo Chao Han. "Application of Spatial Decision Support System in Real Estate Appraisal." Applied Mechanics and Materials 174-177 (May 2012): 3286–90. http://dx.doi.org/10.4028/www.scientific.net/amm.174-177.3286.
Full textAbstract:
After the economic crisis in 2009, the real estate market has gone through a temporary prosperity, but now it is undergoing the country’s another round of macro control. In order to comply with the national’s implementation of "one-room, one- price" policy and make second-hand housing market standardized. A comprehensive analysis of our country’s real estate prices and the latest development trends is made in this paper, besides; the analysis is based on the real estate evaluation theory. This paper presents a novel real estate estimation method based on spatial decision support system, theoretical analysis and the application of computer technology, this approach is an integration of decision support systems (DSS) and Geographic Information Systems (GIS). Meanwhile, it can make our country’s real estate evaluation more regular and scientifically.
4
Bartoněk, Dalibor, and Stanislava Dermeková. "The Permanent Residential Housing: Geographic Information System-Based Evaluation Considering the Legislation." Journal of Computational and Theoretical Nanoscience 14, no. 1 (January 1, 2017): 284–90. http://dx.doi.org/10.1166/jctn.2017.6318.
Full textAbstract:
The paper deals with the conception of multi-criteria analysis geographic information system (GIS). The set of criteria has great influence on the whole project in GIS. This fact is described in chapter “materials and methods” where a new model is discussed. In these model is included influence of legislative which restrict the set of criteria. The selected criteria have also determine the input dataset. It leads to proper and optimal selecting of set of input data in GIS. The advantage is the optimization of input data and selects the best variant in combination with strategies in spatial decision making. The article proposes the evaluation process which is user oriented and consists of several multi-criteria methods. In this paper the authors proposed a mathematical model which includes input data containing hypothesis of the stakeholders (input criteria) and output data representing proposed variants for different solutions. Experimental results are focused on GIS based evaluation of permanent residential housing. As main method of multi-criterial analysis is used sensitive analysis. A team of experts and stakeholders sett importance of the various criteria and thus determine the values of weights for their quantification. These parameters are determined in the model as the main criteria for strategic planning in the real estate engineering. The weights are also numerically quantified using different methods of decision theory. Selected and restricted criteria (by legislative) determine the set of spatial analytical functions. Spatial analyses create an important part of this method. Spatial analyses serve as an attractive cartographic presentation of the project to users appearing in the real estate market using static and of interactive maps. Graphically and numerically multi-criteria analyses are presented as the final result which report analyzing the effectiveness of various factors. These factors affect the real estate market and the price of real estate. From an economic point of view, it is possible to determine these factors by the supply and demand for a particular type of property. The proposed method is a new approach to comprehensive evaluation criteria for the purposes of the real estate market. The existing MCDA methods are integrated into one unit and evaluated through an optimal variant.
5
Cichociński, Piotr, and Janusz Dąbrowski. "Spatio-Temporal Analysis of the Real Estate Market Using Geographic Information Systems." Real Estate Management and Valuation 21, no. 2 (June 1, 2013): 72–82. http://dx.doi.org/10.2478/remav-2013-0019.
Full textAbstract:
Abstract The paper proposes the use of geographic information system tools for the analysis of spatial and temporal aspects of the real estate market. In particular, it focuses on the graphical presentation of the spatial distribution of price and its variability over time. The possibility of presenting an image of the spatial distribution of prices in the form of a 3D model is studied. A topographic surface is proposed as an alternative to traditional methods of spatial interpolation. Visual verification and numerical comparison have shown its superiority over other previously used methods. The best method of presenting four-dimensional data - the variation in time of the spatial distribution of house prices - was sought. The possibility of taking time into account as one of the attributes of the analyzed and presented objects, available in advanced GIS software, was used for this purpose. The undertaken activities were based on formal guidelines for the registration of time set out in the ISO 19100 series of standards dedicated to geographic information. Potential sources of data for this kind of analysis were identified and their availability was examined. The paper also presents how to build a spatial database on the basis of the available information, which is a starting material for further analysis. The carried out research demonstrated the benefits of the spatial approach to trends of changes in real estate prices, which can be used, among others, for mass appraisal.
6
COROIAN, Iulia, Mircea Emil NAP, Ioana Delia POP, Florica MATEI, Tudor SĂLĂGEAN, Jutka DEAK, Silvia CHIOREAN, Elemer Emanuel ȘUBA, Ioan LUPUȚ, and Diana FICIOR. "Using GIS Analysis to Assess Urban Green Space in Terms of Real Estate Development." Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca. Horticulture 78, no. 1 (May 14, 2021): 36. http://dx.doi.org/10.15835/buasvmcn-hort:2020.0061.
Full textAbstract:
Urban green spaces (UGS) contribute to the development of the ecosystem, especially in crowded urban areas such as cooling effect, air and noise pollution mitigation, recreation, aesthetic pleasure, quality of life and public health, as well as economic benefits, such as raising the price of the real state in the vicinity of UGS. The aim of the paper is to realize a study on green spaces and an urban distribution of the size of a systematic planning of functional and aesthetic qualities. This study examines the distribution and amount of green space, as well as the size and rates per capita are assessed. Even the distribution of distance and the accessibility of green areas throughout the city are closely linked to ensuring recreational needs. Spatial statistics using GIS have made possible the development of correct, coherent explanatory UGS variables such as distance, size, density, connectivity, sight and accessibility. The parks and all green spaces composed of polygons were digitized from the ArcGIS Attribute Table for the evaluation of per capita rates and the execution of a plan to combat the deficit of green spaces. In order to make an assessment of the green spaces, a comparative study of the area of interest from 2010 and 2020 was considered. According to the spatial analyses from ArcGis, during the 10 years, an intense real estate market was developed, affecting the distribution of green spaces per capita.
7
Chen, Shaopei, Dachang Zhuang, and Huixia Zhang. "GIS-Based Spatial Autocorrelation Analysis of Housing Prices Oriented towards a View of Spatiotemporal Homogeneity and Nonstationarity: A Case Study of Guangzhou, China." Complexity 2020 (April 23, 2020): 1–16. http://dx.doi.org/10.1155/2020/1079024.
Full textAbstract:
In the past decades, the booming growth of housing markets in China triggers the urgent need to explore how the rapid urban spatial expansion, large-scale urban infrastructural development, and fast-changing urban planning determine the housing price changes and spatial differentiation. It is of great significance to promote the existing governing policy and mechanism of housing market and the reform of real-estate system. At the level of city, an empirical analysis is implemented with the traditional econometric models of regressive analysis and GIS-based spatial autocorrelation models, focusing in examining and characterizing the spatial homogeneity and nonstationarity of housing prices in Guangzhou, China. There are 141 neigborhoods in Guangzhou identified as the independent individuals (named as area units), and their values of the average annual housing prices (AAHP) in (2009–2015) are clarified as the dependent variables in regressing analysis models used in this paper. Simultaneously, the factors including geographical location, transportation accessibility, commercial service intensity, and public service intensity are identified as independent variables in the context of urban development and planning. The integration and comparative analysis of multiple linear regression models, spatial autocorrelation models, and geographically weighted regressing (GWR) models are implemented, focusing on exploring the influencing factors of house prices, especially characterizing the spatial heterogeneity and nonstationarity of housing prices oriented towards the spatial differences of urban spatial development, infrastructure layout, land use, and planning. This has the potential to enrich the current approaches to the complex quantitative analysis modelling of housing prices. Particularly, it is favorable to examine and characterize what and how to determine the spatial homogeneity and nonstationarity of housing prices oriented towards a microscale geospatial perspective. Therefore, this study should be significant to drive essential changes to develop a more efficient, sustainable, and competitive real-estate system at the level of city, especially for the emerging and dynamic housing markets in the megacities in China.
8
Bartoněk, Dalibor, Jiří Bureš, and Otakar Švábenský. "Evaluation of Influence of the Environment on the Choice of Buildings for Residential Living." Sustainability 12, no. 12 (June 16, 2020): 4901. http://dx.doi.org/10.3390/su12124901.
Full textAbstract:
In the CR (Czech Republic), there are a lot of prefabricated housing estates built in the 70s and 80s of the 20th century, which are at the end of their life cycle. The main goal of the project was to evaluate the rate of energy savings in the long term due to the revitalization of prefabricated apartment buildings, and thus provide feedback to the relevant authorities on its effectiveness. Another goal was to evaluate selected parameters of living comfort in the locality for the purposes of the real estate market with the possibility of providing them to those interested in living in the locality. A complex of methods was used, which evaluate criteria from various spheres, such as environment, spatial relationships, social aspects, etc. The authors used a combination of multi-criterial analysis methods (MCA) and spatial analysis within a Geographical Information System (GIS). Of all MCA methods, weighted linear combination (WLC) was chosen as the most suitable. In the spatial analyses, the matter of solution was, above all, the distance to the center and the transport within the given locality. The above-mentioned methods served as a model for evaluating whether a panel house in question is or is not suitable for reconstruction. The input data of the model are spatial data—national map series of the CR, environmental data (noise maps, energy demands of buildings)—and statistical data obtained from various sources (city administration of Brno, relevant organizations, and interviews with respondents). Within Inquiry Form 3, potential groups of respondents were addressed: Group A—people over fifty, group B—young families with children, group C—students under 25. The projected model was tested in Brno city in the locality of Nový Lískovec (CR). The proposed model provided information on the quality of housing in a given locality in terms of energy intensity, noise pollution, transport accessibility, and civic amenities. The output is a multi-criteria model with GIS support, which is generally applicable. The results of the model analyses led to the demonstration of the effectiveness of revitalization. The results can be used for estate offices or other organizations in the form of graphical outputs of appropriate variants on the basis of solving a lot of criteria when searching for a suitable residence.
9
Adebayo, Adejimi Alli, Paul Greenhalgh, and Kevin Muldoon-Smith. "Investigating retail property market dynamics through spatial accessibility measures." Journal of European Real Estate Research 12, no. 2 (August 8, 2019): 155–72. http://dx.doi.org/10.1108/jerer-01-2018-0009.
Full textAbstract:
Purpose The retail property market is constantly adopting to the continuous demand of retailers and their consumers. This paper aims to investigate retail property market dynamics through spatial accessibility measures of the City of York street network. It explores how spatial accessibility metrics (SAM) explain retail market dynamics (RMD) through changes in the city’s retail rental values and stock. Design/methodology/approach Valuation office agency (VOA) data sets (aspatial) and ordnance survey map (spatial) data form the empirical foundation for this investigation. Changes in rental value and retail stock between 2010 and 2017 VOA data sets represent the RMD variables. While, the configured street network measures of Space Syntax, namely, global integration, local integration, global choice and normalised angular choice form the SAM variables. The relationship between these variables is analysed through geo-visualisation and statistical testing using GIS and SPSS tools. Findings The study reveals that there has been an overall negative changes of 15 and 22% in rental value and retail stock, respectively, even though some locations within the sampled city (York, North Yorkshire, England) indicated positive changes. The study further indicated that changes in retail rental value and stock have occurred within locations with good accessibility index. It also verifies that there are spatial and statistical relationship between variables and 22% of RMD variability was jointly accounted for by SAM. Originality/value This research is first to investigates changes in retail property market variables through spatial accessibility measures of space syntax. It contributes to the burgeoning research field of real estate and Space Syntax.
10
Chilton, Ken, Robert Silverman, Rabia Chaudhrey, and Chihaungji Wang. "The Impact of Single-Family Rental REITs on Regional Housing Markets: A Case Study of Nashville, TN." Societies 8, no. 4 (September 20, 2018): 93. http://dx.doi.org/10.3390/soc8040093.
Full textAbstract:
The U.S. Congress authorized the creation of real estate investment trusts (REITs) in 1960 so companies could develop publically traded real estate investment portfolios. REITs focus on commercial property, retail property, and rental property. During the last decade, REITs became more active in regional housing markets across the U.S. Single-family rental (SFR) REITs have grown tremendously, buying up residential properties across the country. In some regional housing markets, SFR REITs own noticeable shares of single-family homes. In those settings, SFR REITs take large numbers of housing units off of real estate markets where homeownership transactions occur and manage these properties as part of commercial rental inventories. This has resulted in a new category of multiple property owners, composed of institutional investors as opposed to individual investors, which further exacerbates property wealth concentration and polarization. This study examines the socio–spatial distribution of properties in SFR REIT portfolios to determine if SFR REIT properties tend to cluster in distinct areas. This study will focus on the regional housing market in Nashville, TN. Nashville has one of the most active SFR REIT sectors in the country. County tax assessor records were used to identify SFR REIT properties. These data were joined with U.S. Census data to create a profile of communities. The data were analyzed using SPSS statistical software and GIS software. Our analysis suggests that neighborhoods with clusters of SFR REITs fit the SFR REIT business model. Clusters occur in communities with newer homes, residents with higher levels of educational attainment, and middle to upper-middle incomes. The paper concludes with several recommendations for future research on SFR REITs.
11
Chung, You, Ducksu Seo, and Jaehwan Kim. "Price Determinants and GIS Analysis of the Housing Market in Vietnam: The Cases of Ho Chi Minh City and Hanoi." Sustainability 10, no. 12 (December 11, 2018): 4720. http://dx.doi.org/10.3390/su10124720.
Full textAbstract:
Since the introduction of the Doi Moi economic reform in 1986, the real estate market in Vietnam has witnessed a sharp increase in foreign investment inflows and a remarkable growth in the housing market, particularly for high-rise apartments in large cities. This study investigates the determinants of apartment prices in Ho Chi Minh City (HCMC) and Hanoi, the two most representative cities in Vietnam. The spatial distribution of apartments and their price determinants were addressed by the spatial analysis of Geographic Information System (GIS) and the hedonic model. The price determinants of both cities were closely associated with downtown-related factors; moreover, the externalities of urbanization affected each city. While HCMC was more related to the locational attributes of urban amenities and community density as well as programs because of unmanaged urbanization, Hanoi was more related to housing attributes, since the majority of apartment projects were developed under urban infrastructure development supported by the central government. Apartment cluster maps of each city clearly show the contrast of housing distribution. Our findings clarify the impact of government policies on housing price determinants and can be a reference for private- and public-sector stakeholders seeking to undertake economically and socially sustainable housing development projects in Vietnam.
12
Dolean, Bogdan-Eugen, Ștefan Bilașco, Dănuț Petrea, Ciprian Moldovan, Iuliu Vescan, Sanda Roșca, and Ioan Fodorean. "Evaluation of the Built-Up Area Dynamics in the First Ring of Cluj-Napoca Metropolitan Area, Romania by Semi-Automatic GIS Analysis of Landsat Satellite Images." Applied Sciences 10, no. 21 (October 31, 2020): 7722. http://dx.doi.org/10.3390/app10217722.
Full textAbstract:
The accentuated dynamics of the real estate markets of the last 20 years, determined that a large part of the territories in the immediate vicinity of the big urban centers, to change their category of land use, in an accelerated rhythm. Most of the time, the land use changes according to the market requirements, the predominantly agricultural lands being occupied by constructions with residential or industrial functions. Identifying these changes is a difficult task due to the heterogeneity of spatial databases that come from different real estate development projects, so determining and implementing new methods to track land changes are currently highly required. This paper presents a methodologically innovative index-based approach for the rapid mapping of built-up areas, using Landsat-5, Landsat-7, and Landsat-8 satellite imagery. The approach described in this study differs from other conventional methods by the way the analysis was performed and also by the thematic indices used in the processes of built-up area delineation. The method, structured in a complex model, based on Remote Sensing and GIS techniques, can be divided into three distinct phases. The first stage is related to the pre-processing of the remote sensing data. The second stage involves the calculation of the normalized difference vegetation index (NDVI), the modified normalized difference water index (MNDWI), and the bare soil index (BI) correlated with the extraction of all areas not covered by vegetation; respectively, the elimination from the result of all areas covered by water, bare land, or uncultivated arable land. The result of this stage is represented by a distinct thematic layer that contains only built-up areas and other associated territories. The last step of the model is represented by the validation of the results, which was performed based on statistical methods and also by direct comparison with field reality, obtaining a validation coefficient which is generally above 85% for any of the methods used. The validation process shows us that by applying this method, the fast mapping of the built-up areas is significantly enhanced and the model is suitable to be implemented on a larger scale in any practical and theoretical application that aims at the rapid mapping of the built-up areas and their evolutionary modeling.
13
Bełej, Mirosław, Radosław Cellmer, and Michał Głuszak. "The Impact of Airport Proximity on Single-Family House Prices—Evidence from Poland." Sustainability 12, no. 19 (September 24, 2020): 7928. http://dx.doi.org/10.3390/su12197928.
Full textAbstract:
Airports in Poland are obliged to observe the sustainable development principle and therefore to reduce their environmental impact by creating so-called limited use areas (LUA) related to aircraft-generated noise. The research authors analyzed airports’ impact on the prices of single-family homes located in the vicinity of airports. The LUA is therefore defined as the area designated to study the airport’s specific impact on the single-family housing market. This is a formal limit which determines the examination of price changes and the decision-making conditions of market participants. This methodical approach is justified because no excessive noise is expected outside the LUA. Therefore, two markets in the vicinity of airports were examined. One is in an LUA which is closer to the airport, and the other market is outside the LUA where external noise effects are not present. Thus, we consider that real estate located outside the LUA is not subject to a significant negative impact from the airport. The study covered the Gdańsk Lech Walesa Airport and the Warsaw Chopin Airport in Poland in adjacent areas with the research time horizon of 2013–2017. The study examined single-family house prices. We used a time series analysis, a classic multiple regression model, a spatial autoregressive model, and geographically weighted regression models in our research. Additionally, Geographical Information System (GIS) tools were used to visualize the results of our study. The research result was to demonstrate different impact levels of airports on the prices of single-family houses located in limited-use areas in Gdańsk and Warsaw. This research carries significant implications for the general public and airports’ economic decisions in resolving conflicts between the airport and residential property owners in airports’ vicinities.
14
Nistor, Constantin, Marina Vîrghileanu, Irina Cârlan, Bogdan-Andrei Mihai, Liviu Toma, and Bogdan Olariu. "Remote Sensing-Based Analysis of Urban Landscape Change in the City of Bucharest, Romania." Remote Sensing 13, no. 12 (June 13, 2021): 2323. http://dx.doi.org/10.3390/rs13122323.
Full textAbstract:
The paper investigates the urban landscape changes for the last 50 years in Bucharest, the capital city of Romania. Bucharest shows a complex structural transformation driven by the socialist urban policy, followed by an intensive real-estate market development. Our analysis is based on a diachronic set of high-resolution satellite imagery: declassified CORONA KH-4B from 1968, SPOT-1 from 1989, and multisensor stacked layers from Sentinel-1 SAR together with Sentinel-2MSI from 2018. Three different datasets of land cover/use are extracted for the reference years. Each dataset reveals its own urban structure pattern. The first one illustrates a radiography of the city in the second part of the 20th century, where rural patterns meet the modern ones, while the second one reveals the frame of a city in a full process of transformation with multiple constructions sites, based on the socialist model. The third one presents an image of a cosmopolitan city during an expansion process, with a high degree of landscape heterogeneity. All the datasets are included in a built-up change analysis in order to map and assess the spatial transformations of the city pattern over 5 decades. In order to quantify and map the changes, the Built-up Change Index (BCI) is introduced. The results highlight a particular situation linked to the policy development visions for each decade, with major changes of about 50% for different built-up classes. The GIS analysis illustrates two major landscape transformations: from the old semirural structures with houses surrounded by gardens from 1968, to a compact pattern with large districts of blocks of flats in 1989, and a contemporary city defined by an uncontrolled urban sprawl process in 2018.
15
Anselin, Luc. "GIS Research Infrastructure for Spatial Analysis of Real Estate Markets." Journal of Housing Research 9, no. 1 (January 1, 1998): 113–33. http://dx.doi.org/10.1080/10835547.1998.12091930.
Full text
16
Siejka, Monika. "THE ROLE OF SPATIAL INFORMATION SYSTEMS IN DECISION-MAKING PROCESSES REGARDING INVESTMENT SITE SELECTION." Real Estate Management and Valuation 25, no. 3 (September 26, 2017): 62–72. http://dx.doi.org/10.1515/remav-2017-0023.
Full textAbstract:
Abstract One of the main tasks of real estate management is making decisions concerning the location of investments. Taking into consideration the fact that any investment affects, directly or indirectly, the economic development of a commune, it has a significant impact on the local real estate market. Investments that have a negative impact on the environment can contribute to a reduction in the activity of the local real estate market. Upon performing tasks related to the economic development of a region and to an increase in the inhabitants’ quality of life, the activity of the local real estate market increases. The paper presents the role of spatial information systems as a source of data used in decision-making processes related to local investment site selection. Currently, there are spatial information systems functioning as a platform for multi-level information systems on real estate and GIS, on local, regional, national and international markets. In this way, the resources of spatial information are available to all institutions, natural and legal persons. As a result, the acquisition of a series of data can take place at any time and at no cost.
17
Kobylińska and Cellmer. "Modelling and Simulation of Selected Real Estate Market Spatial Phenomena." ISPRS International Journal of Geo-Information 8, no. 10 (October 10, 2019): 446. http://dx.doi.org/10.3390/ijgi8100446.
Full textAbstract:
This paper presents a novel approach to the modelling and simulation of real estate transactions. The main purpose of the study was to develop the theoretical foundations for building simulation models of transaction locations and real estate prices. Pursuing this objective involved a spatial market analysis based on geostatistics to develop maps of the dynamics and spatial activity of the real estate market. The research was conducted by presenting the issue against the background of the literature of the subject and by conducting an experiment, which involved developing an original procedure of providing simulated market data. The study deals with the market for non-built-up land real estate with a residential function in the city of Olsztyn (Poland). The time range concerned the years 2004–2015. Information on 932 real estate transactions was adopted for the study. A set of additional information on virtual transactions was generated during the study; this information can supplement market data for markets of low activity or if there are information gaps. Geoinformation analyses were performed in order to determine new trends in price levels and spatial activity of a real estate market. Overall, this resulted in generating maps of simulated transaction densities, a map of simulated prices and a map of the probability of a specific price occurring.
18
Szczepańska, Agnieszka, Dariusz Gościewski, and Małgorzata Gerus-Gościewska. "A GRID-Based Spatial Interpolation Method as a Tool Supporting Real Estate Market Analyses." ISPRS International Journal of Geo-Information 9, no. 1 (January 14, 2020): 39. http://dx.doi.org/10.3390/ijgi9010039.
Full textAbstract:
The spatial distribution of prices is closely linked with the urban real estate market. Property prices are one of the key indicators of economic activity because they influence economic decisions. Decision-makers and consumers often need information about the spatial distribution of prices, but spatial-temporal analyses of the real estate market are based on the prices quoted in different locations across years (epochs). Due to this idiosyncrasy, the resulting datasets are dispersed (different across years) and difficult to compare. For this reason, the existing interpolation methods are not always effective in analyses of the real estate market. A different approach to interpolating real estate prices that supports the generation of continuous interpolated surfaces while maintaining the values of measurement points is thus needed. This paper proposes a method for replacing dispersed spatial data with a regular GRID structure. The GRID structure covers the measured object with a regular network of nodes, which supports uniform interpolation at every point of the analyzed space and a comparison of interpolation models in successive epochs (years). The proposed method was tested on a selected object. The results indicate that the GRID structure can be used in analyses of highly complex real estate markets where input data are incomplete, irregular and dispersed.
19
Renigier-Bilozor, Malgorzata, Artur Janowski, and Marek Walacik. "Geoscience Methods in Real Estate Market Analyses Subjectivity Decrease." Geosciences 9, no. 3 (March 16, 2019): 130. http://dx.doi.org/10.3390/geosciences9030130.
Full textAbstract:
Real estate management, including real estate market analysis, is part of a so-called geosystem. In recent years, the popularity of creating various types of systems and automatic solutions in real estate management, including those related to property classification and valuation, has been growing in the world, mainly to reduce the impact of human subjectivity, to increase the scope of analyses and reduce research time. A very important fact that should be underlined is that properties are strongly related to geolocation (space) and strongly determine it. Authors proposed in the paper solutions that highlight implementation of geoscience and “geo-approach” combined with fuzzy logic methods that allow to decrease subjectivity in property analyses and diminish uncertainty in decision making process. The proposed methodology involves three main problematic components of decision support system in property investment analyses development with the use of geo-technologies such as: determination of the database model; elaboration geo-property-zones with geoprocessing activities; identification of homogeneous group of properties transactions. The influence of spatial decision factor determined in the study lead to objective and precise calculation of value differentiation from 22 to 43% depending on the property’s remoteness to the sea.
20
Cellmer, Radosław. "The Possibilities and Limitations of Geostatistical Methods in Real Estate Market Analyses." Real Estate Management and Valuation 22, no. 3 (October 1, 2014): 54–62. http://dx.doi.org/10.2478/remav-2014-0027.
Full textAbstract:
Abstract In the traditional approach, geostatistical modeling involves analyses of the spatial structure of regionalized data, as well as estimations and simulations that rely on kriging methods. Geostatistical methods can complement traditional statistical models of property transaction prices, and when combined with those models, they offer a comprehensive tool for spatial analysis that is used in the process of developing land value maps. Transaction prices are characterized by mutual spatial correlations and can be considered as regionalized variables. They can also be regarded as random variables that have a local character and a specific probability distribution. This study explores the possibilities of applying geostatistical methods in spatial modeling of the prices of undeveloped land, as well as the limitations associated with those methods and the imperfect nature of the real estate market. The results are discussed based on examples, and they cover both the modeling process and the generated land value maps.
21
Cymerman, Joanna, and Wojciech Cymerman. "Geographical Diversification of Gmina Revenue from Real Estate Market in Poland." Folia Oeconomica Stetinensia 18, no. 1 (June 1, 2018): 39–53. http://dx.doi.org/10.2478/foli-2018-0004.
Full textAbstract:
Abstract The paper discusses the local government revenue from the real estate market, focusing mainly on identifying the spatial differentiation of municipal income from the real estate market. The study covered all communes (gminas) in Poland (2,478). The temporal scope of the study was a decade between 2005 and 2015. The analyses focused on the following three groups of revenue from a real estate market: recurrent property taxes, revenue from municipal assets, and taxes in respect of the ownership right transfer. The main research hypothesis was made that the community located in central and north-western Poland gain higher income from the real estate market, than other gminas. The analyses were carried out on the basis of particular types of gminas (municipalities, urban-rural communities, and rural communities ‒ in the voivodeship arrangement). Voivodeship capitals were subjected to separate analyses because of the specific central character of their public functions. The data came from the Local Data Bank of the Polish Central Statistical Office. The data analysis was conducted by means of statistical and econometric methods.
22
Barreca, Alice, Rocco Curto, and Diana Rolando. "Housing Vulnerability and Property Prices: Spatial Analyses in the Turin Real Estate Market." Sustainability 10, no. 9 (August 28, 2018): 3068. http://dx.doi.org/10.3390/su10093068.
Full textAbstract:
In the literature, several vulnerability/resilience indicators and indexes are based and assessed by taking into account and combining different dimensions. Housing vulnerability is one of these dimensions and is strictly related to the buildings’ physical features and to the socio-economic condition of their occupants. This research aims to study housing vulnerability in relation to the real estate market by identifying possible indicators and spatially analyzing their influence on property prices. Assuming the city of Turin and its territorial segmentation as a case study, spatial analyses were performed to take into account the presence of spatial dependence and to identify the variables that significantly influence the process of property price determination. The results of this study highlighted the fact that two housing vulnerability indicators, representative of fragile buildings’ physical features, were spatially correlated with property prices and had a significant and negative influence on them. In addition, their comparison with two social vulnerability indicators demonstrated that the presence of economical buildings and council houses was spatially correlated with the presence of people with a low education level. The results of the spatial regression model also confirmed that one of the social vulnerability indicators had the highest and most negative explanatory power in the property price determination process.
23
Clapp, John, and Mauricio Rodriguez. "Using a GIS for Real Estate Market Analysis: The Problem of Spatially Aggregated Data." Journal of Real Estate Research 16, no. 1 (January 1, 1998): 35–56. http://dx.doi.org/10.1080/10835547.1998.12090939.
Full text
24
Barreca, Alice, Rocco Curto, and Diana Rolando. "Urban Vibrancy: An Emerging Factor that Spatially Influences the Real Estate Market." Sustainability 12, no. 1 (January 1, 2020): 346. http://dx.doi.org/10.3390/su12010346.
Full textAbstract:
Urban vibrancy is defined and measured differently in the literature. Originally, it was described as the number of people in and around streets or neighborhoods. Now, it is commonly associated with activity intensity, the diversity of land-use configurations, and the accessibility of a place. The aim of this paper is to study urban vibrancy, its relationship with neighborhood services, and the real estate market. Firstly, it is used a set of neighborhood service variables, and a Principal Component Analysis is performed in order to create a Neighborhood Services Index (NeSI) that is able to identify the most and least vibrant urban areas of a city. Secondly, the influence of urban vibrancy on the listing prices of existing housing is analyzed by performing spatial analyses. To achieve this, the presence of spatial autocorrelation is investigated and spatial clusters are identified. Therefore, spatial autoregressive models are applied to manage spatial effects and to identify the variables that significantly influence the process of housing price determination. The results confirm that housing prices are spatially autocorrelated and highlight that housing prices and NeSI are statistically associated with each other. The identification of the urban areas characterized by different levels of vibrancy and housing prices can effectively support the revision of the urban development plan and its regulatory act, as well as strategic urban policies and actions. Such data analyses support a deep knowledge of the current status quo, which is necessary to drive important changes to develop more efficient, sustainable, and competitive cities.
25
Barreca, Alice, Rocco Curto, and Diana Rolando. "Is the Real Estate Market of New Housing Stock Influenced by Urban Vibrancy?" Complexity 2020 (October 22, 2020): 1–22. http://dx.doi.org/10.1155/2020/1908698.
Full textAbstract:
The attractiveness and vibrancy of an urban area are very complex aspects that both Public Administrations and real estate developers and construction companies have to carefully consider in order to correctly address their investments and sustainable urban development projects. The aim of this paper is to study urban vibrancy and its relationship with the neighbourhood services and the real estate market of new housing stock. Spatial analyses are performed to study the influence of the Neighbourhood Services Index (NeSI) and its Principal Components (PCs) on listing prices and the construction activity. Spatial autoregressive (SAR) models are applied both with lattice data and data points, in order to manage spatial dependence and to identify the variables that significantly influence housing prices and construction site density. Findings highlight that the NeSI significantly influences the real estate market of new housing stock and that above the analysed neighbourhood services and the retail activities have a great, significant, and positive influence on the density of housing construction sites. The results of this study represent a real support for both public and private bodies to identify the most and least attractive and vibrant urban areas and to deal with important aspects of urban complexity.
26
Szopińska, Kinga, and Małgorzata Krajewska. "Methods of Assessing Noise Nuisance of Real Estate Surroundings." Real Estate Management and Valuation 24, no. 1 (March 1, 2016): 19–30. http://dx.doi.org/10.1515/remav-2016-0002.
Full textAbstract:
Abstract Testing what factors create the market value of real estate is key information when preparing property valuations as well as other opinions and professional evaluations on the basis of which court verdicts or administrative decisions are made. One of the factors influencing the value of some real estate is the level of noise present in the surroundings, which can lead to the occurrence of noise nuisance negatively affecting social relations. Due to the fact that the analysis of the attractiveness of a location is the basis for properly determining the market value of real estate, the present article is dedicated to the methodology of assessing the noise nuisance of real estate surroundings. Four methods of assessment are proposed in the work: two of an objective nature, based on the measurements of noise and spatial analyses of data included in a strategic noise map, as well as two of a subjective nature, accounting for, among others, the individual perceptions of real estate users. The results of studies using the above methods can serve as a source of information on real estate as well as aid decision processes in the scope of real estate management. Theoretical deliberations were supported by a sample assessment of the noise nuisance of real estate surroundings carried out using two of the presented study methods.
27
Barreca, Alice, Elena Fregonara, and Diana Rolando. "EPC Labels and Building Features: Spatial Implications over Housing Prices." Sustainability 13, no. 5 (March 5, 2021): 2838. http://dx.doi.org/10.3390/su13052838.
Full textAbstract:
The influence of building or dwelling energy performance on the real estate market dynamics and pricing processes is deeply explored, due to the fact that energy efficiency improvement is one of the fundamental reasons for retrofitting the existing housing stock. Nevertheless, the joint effect produced by the building energy performance and the architectural, typological, and physical-technical attributes seems poorly studied. Thus, the aim of this work is to investigate the influence of both energy performance and diverse features on property prices, by performing spatial analyses on a sample of housing properties listed on Turin’s real estate market and on different sub-samples. In particular, Exploratory Spatial Data Analyses (ESDA) statistics, standard hedonic price models (Ordinary Least Squares—OLS) and Spatial Error Models (SEM) are firstly applied on the whole data sample, and then on three different sub-samples: two territorial clusters and a sub-sample representative of the most energy inefficient buildings constructed between 1946 and 1990. Results demonstrate that Energy Performance Certificate (EPC) labels are gaining power in influencing price variations, contrary to the empirical evidence that emerged in some previous studies. Furthermore, the presence of the spatial effects reveals that the impact of energy attributes changes in different sub-markets and thus has to be spatially analysed.
28
Curto, Rocco, and Elena Fregonara. "Monitoring and Analysis of the Real Estate Market in a Social Perspective: Results from the Turin’s (Italy) Experience." Sustainability 11, no. 11 (June 4, 2019): 3150. http://dx.doi.org/10.3390/su11113150.
Full textAbstract:
In Italy, it has always been difficult to collect reliable data on real estate given the opacity of the information available. Keeping into consideration the actual availability of data and information, the possibility to have a structure for permanently monitoring and analysing the real estate market is fundamental. Focusing on developing and disseminating knowledge related to practices in this context, in this paper the Turin’s (Northern Italy) experience is presented, through the Real Estate Market Observatory (TREMO): This structure is based on a data-warehouse, implemented over time, with databases that lead to historic price observations of the residential market. The data warehouse is the basis for investigating methodologies and analyses, assuming the spatial requisites of the data and its georeferencing as the main discriminant in choosing among descriptive statistics, multi-varied or spatial analysis methods. In twenty years, several studies have been developed, allowing us not only to explore the applicability of models and operative modalities, but also to obtain results with a high potential impact under a social viewpoint. In this paper, the methodologies developed for implementing the monitoring structure are presented, specifically the “quality process” and computerized analysis procedures, followed by some representative research experiences with reference to aims, models and results.
29
Rabiei-Dastjerdi, Hamidreza, and Gavin McArdle. "Novel Exploratory Spatiotemporal Analysis to Identify Sociospatial Patterns at Small Areas Using Property Transaction Data in Dublin." Land 10, no. 6 (May 28, 2021): 566. http://dx.doi.org/10.3390/land10060566.
Full textAbstract:
The residential real estate market is very important because most people’s wealth is in this sector, and it is an indicator of the economy. Real estate market data in general and market transaction data, in particular, are inherently spatiotemporal as each transaction has a location and time. Therefore, exploratory spatiotemporal methods can extract unique locational and temporal insight from property transaction data, but this type of data are usually unavailable or not sufficiently geocoded to implement spatiotemporal methods. In this article, exploratory spatiotemporal methods, including a space-time cube, were used to analyze the residential real estate market at small area scale in the Dublin Metropolitan Area over the last decade. The spatial patterns show that some neighborhoods are experiencing change, including gentrification and recent development. The extracted spatiotemporal patterns from the data show different urban areas have had varying responses during national and global crises such as the economic crisis in 2008–2011, the Brexit decision in 2016, and the COVID-19 pandemic. The study also suggests that Dublin is experiencing intraurban displacement of residential property transactions to the west of Dublin city, and we are predicting increasing spatial inequality and segregation in the future. The findings of this innovative and exploratory data-driven approach are supported by other work in the field regarding Dublin and other international cities. The article shows that the space-time cube can be used as complementary evidence for different fields of urban studies, urban planning, urban economics, real estate valuations, intraurban analytics, and monitoring sociospatial changes at small areas, and to understand residential property transactions in cities. Moreover, the exploratory spatiotemporal analyses of data have a high potential to highlight spatial structures of the city and relevant underlying processes. The value and necessity of open access to geocoded spatiotemporal property transaction data in social research are also highlighted.
30
Gurov, Sergey. "Approaches to mapping the regional housing market to provide visualization of the National Project “Housing and Urban Environment”." InterCarto. InterGIS 26, no. 1 (2020): 503–15. http://dx.doi.org/10.35595/2414-9179-2020-1-26-503-515.
Full textAbstract:
The article shows various ways of mapping the regional residential real estate market, which can be used in the future to visualize the National Project “Housing and Urban Environment”, implemented until 2024. The author demonstrates different types of cartodiagrams. It is shown that the equipment of residential real estate is more convenient to display a petal cartodiagram. Attention is paid to the use of cartodiagram with stroke, the semicircular and mesh cartodiagram. The author gives a significant place in the publication to the method of mapping housing affordability for citizens, as one of the important tasks of the National Project “Housing and Urban Environment” is to create conditions for increasing the level of affordability of residential real estate acquisition. There are 4 availability indicators that can be displayed on the map using special cartograms and the cartogram method. The most successful option, according to the author, is a combination of two techniques for the image of a cartogram on one map. Attention and rather rare means of socio-economic mapping, in particular the pseudoisolines (of isopleth). The author notes that this method is one of the most obvious in mapping the residential real estate market, especially the price situation. The article, by building isoprices, it was clearly shown how to identify the main geographical factors in the pricing of the housing market. Attention is paid to the geoinformation component of the isopleth construction. The algorithm of working with them using the Spatial Analyst module of the ArcView GIS program is shown. According to the author, cartographic research should be completed with the construction of synthetic maps. One example of synthesis in mapping the housing market is a map of its geographical segmentation. Such maps can be supplemented with matrix legends. The author emphasizes the importance of moving away from primitive maps with one or two cartographic methods to complex maps.
31
Kutasi, Dávid, and Milán Csaba Badics. "Valuation methods for the housing market: Evidence from Budapest." Acta Oeconomica 66, no. 3 (September 2016): 527–46. http://dx.doi.org/10.1556/032.2016.66.3.8.
Full textAbstract:
Different valuation methods and determinants of housing prices in Budapest, Hungary are examined in this paper in order to describe price drivers by using an asking price dataset. The hedonic regression analysis and the valuation method of the artificial neural network are utilised and compared using both technical and spatial variables. In our analyses, we conclude that according to our sample from the Budapest real estate market, the Multi-Layer Preceptron (MLP) neural network is a better alternative for market price prediction than hedonic regression in all observed cases. To our knowledge, the estimation of housing price drivers based on a large-scale sample has never been explored before in Budapest or any other city in Hungary in detail; moreover, it is one of the first papers in this topic in the CEE region. The results of this paper lead to promising directions for the development of Hungarian real estate price statistics.
32
Szczepańska, Agnieszka. "Expansion of the Transport System as a Factor Affecting the Real Estate Market, with the Construction of the Olsztyn Ring-Road as an Example." Real Estate Management and Valuation 27, no. 4 (December 1, 2019): 39–52. http://dx.doi.org/10.2478/remav-2019-0034.
Full textAbstract:
Abstract Improvement of spatial accessibility, associated with changes in the transport system, can affect the local real estate market. This is because better transport accessibility and reducing the time of a journey home affects the location-related attractiveness of real estate. A ring-road in a town is an example of changes in the transport system of an urban functional area. Such an investment project is being carried out in the Olsztyn suburban zone. The aim of the study was to verify whether the execution of this road construction project affects the local real estate market in the suburban area in the plot segment. The scope of the study included the change of activity and price level. The study period included the years 2007-2018. The analyses were based on descriptive statistics. This paper presents the effect of transport accessibility on real estate prices, the importance of the ring-road under construction arising from the strategic document analysis, the methodology applied, and the conclusions of the study. The results indicate a systematic increase in the number of transactions and average unit prices of building plots from the moment a permit for carrying out a road construction project was issued.
33
Unbehaun, Florian, and Franz Fuerst. "Cap rates and risk: a spatial analysis of commercial real estate." Studies in Economics and Finance 35, no. 1 (March 5, 2018): 25–43. http://dx.doi.org/10.1108/sef-11-2016-0267.
Full textAbstract:
Purpose This study aims to assess the impact of location on capitalization rates and risk premia. Design/methodology/approach Using a transaction-based data series for the five largest office markets in Germany from 2005 to 2015, regression analysis is performed to account for a large set of asset-level drivers such as location, age and size and time-varying macro-level drivers. Findings Location is found to be a key determinant of cap rates and risk premia. CBD locations are found to attract lower cap rates and lower risk premia in three of the five largest markets in Germany. Interestingly, this effect is not found in the non-CBD locations of these markets, suggesting that the lower perceived risk associated with these large markets is restricted to a relatively small area within these markets that are reputed to be safe investments. Research limitations/implications The findings imply that investors view properties in peripheral urban locations as imperfect substitutes for CBD properties. Further analysis also shows that these risk premia are not uniformly applied across real estate asset types. The CBD risk effect is particularly pronounced for office and retail assets, apparently considered “prime” investments within the central locations. Originality/value This is one of the first empirical studies of the risk implications of peripheral commercial real estate locations. It is also one of the first large-scale cap rate analyses of the German commercial real estate market. The results demonstrate that risk perceptions of investors have a distinct spatial dimension.
34
Cajias, Marcelo, and Sebastian Ertl. "Spatial effects and non-linearity in hedonic modeling." Journal of Property Investment & Finance 36, no. 1 (February 5, 2018): 32–49. http://dx.doi.org/10.1108/jpif-10-2016-0080.
Full textAbstract:
Purpose The purpose of this paper is to test the asymptotic properties and prediction accuracy of two innovative methods proposed along the hedonic debate: the geographically weighted regression (GWR) and the generalized additive model (GAM). Design/methodology/approach The authors assess the asymptotic properties of linear, spatial and non-linear hedonic models based on a very large data set in Germany. The employed functional form is based on the OLS, GWR and the GAM, while the estimation methodology was chosen to be iterative in forecasting, the fitted rents for each quarter based on their 1-quarter-prior functional form. The performance accuracy is measured by traditional indicators such as the error variance and the mean squared (percentage) error. Findings The results provide evidence for a clear disadvantage of the GWR model in out-of-sample forecasts. There exists a strong out-of-sample discrepancy between the GWR and the GAM models, whereas the simplicity of the OLS approach is not substantially outperformed by the GAM approach. Practical implications For policymakers, a more accurate knowledge on market dynamics via hedonic models leads to a more precise market control and to a better understanding of the local factors affecting current and future rents. For institutional researchers, instead, the findings are essential and might be used as a guide when valuing residential portfolios and forecasting cashflows. Even though this study analyses residential real estate, the results should be of interest to all forms of real estate investments. Originality/value Sample size is essential when deriving the asymptotic properties of hedonic models. Whit this study covering more than 570,000 observations, this study constitutes – to the authors’ knowledge – one of the largest data sets used for spatial real estate analysis.
35
Waldhoff, G., S. Eichfuss, and G. Bareth. "INTEGRATION OF REMOTE SENSING DATA AND BASIC GEODATA AT DIFFERENT SCALE LEVELS FOR IMPROVED LAND USE ANALYSES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-3/W3 (August 19, 2015): 85–89. http://dx.doi.org/10.5194/isprsarchives-xl-3-w3-85-2015.
Full textAbstract:
The classification of remote sensing data is a standard method to retrieve up-to-date land use data at various scales. However, through the incorporation of additional data using geographical information systems (GIS) land use analyses can be enriched significantly. In this regard, the Multi-Data Approach (MDA) for the integration of remote sensing classifications and official basic geodata for a regional scale as well as the achievable results are summarised. On this methodological basis, we investigate the enhancement of land use analyses at a very high spatial resolution by combining WorldView-2 remote sensing data and official cadastral data for Germany (the Automated Real Estate Map, ALK). Our first results show that manifold thematic information and the improved geometric delineation of land use classes can be gained even at a high spatial resolution.
36
Nieścioruk, Kamil. "The Cartographic Method of Research in Exploring the Real Estate Market - A Case of Using Maps for the Introductory Analyses of the Lublin Suburban Commune of Konopnica." Real Estate Management and Valuation 23, no. 2 (June 1, 2015): 17–26. http://dx.doi.org/10.1515/remav-2015-0012.
Full textAbstract:
Abstract The paper deals with the introductory analysis of the real estate market of a suburban commune located near a big (voivodeship capital) city. The analysis is based mainly of the cartographic method of research. Besides data mining and preparation, maps play an important role here, presenting values acquired directly from the register of notarial deeds of estate sales and purchases, as well as values resulting from statistic computation, for example mean values of area or price, absolute numbers of transactions or real estate type. The spatial factor is also taken into consideration when it comes to more complex or specific analyses. The influence of distance understood as a metric and time factor, as well as regression analysis results are also visualized on maps. Such presentation is a good step towards advanced analyses providing maps are prepared according to the rules of cartography. The paper stresses that a map can be a great tool in aiding every stage of research, but may also cause misinterpretations and false conclusions when at least basic rules are not complied with.
37
Inoue, Ryo, Rihoko Ishiyama, and Ayako Sugiura. "Identifying local differences with fused-MCP: an apartment rental market case study on geographical segmentation detection." Japanese Journal of Statistics and Data Science 3, no. 1 (January 17, 2020): 183–214. http://dx.doi.org/10.1007/s42081-019-00070-y.
Full textAbstract:
AbstractAs the variety and quality of spatial data increase in recent times, the potential to analyze local characteristics based on spatial data is getting stronger. Previous spatial analysis methods structuralize the spatial autocorrelation of data by the distances between data observation points and the contiguity of the data-observed regions. It is significant for the estimation of global characteristics of spatial data. However, these approaches are not suitable for identifying local differences from the data since they assume a smooth spatial autocorrelation structure. Generalized fused lasso, which can detect local differences in spatial data, has been proposed in machine learning studies. Its limitation is that the estimated parameters are biased toward zero; however, methods that overcome the limitation have also been proposed. Fused-MCP is one of those methods and is expected to be useful in spatial analyses. This study applies fused-MCP to spatial analyses. As an example of spatial analyses based on fused-MCP, this study analyzes the structure of geographical segmentation of the real estate market in central Tokyo. Fused-MCP is utilized to extract areas where the valuation standard is the same. The results reveal that the geographical segmentation displays hierarchal patterns. Specifically, the market is divided by municipalities, railway lines and stations, and neighborhoods. The case study confirmed the applicability of fused-MCP to spatial analyses.
38
Cajias, Marcelo, Philipp Freudenreich, Anna Freudenreich, and Wolfgang Schäfers. "Liquidity and prices: a cluster analysis of the German residential real estate market." Journal of Business Economics 90, no. 7 (August 2020): 1021–56. http://dx.doi.org/10.1007/s11573-020-00990-2.
Full textAbstract:
Abstract This paper analyses the highly under-researched German residential real estate market. Quality- and spatial-adjusted price and liquidity indices are calculated separately for the investment and rental market on a regional basis. Applying the “Partitioning Around Medoids (PAM)” clustering algorithm, the regions are clustered with respect to their price and liquidity development after the average silhouette method is applied to find the optimal number of clusters. The dataset underlying this analysis comprises more than 4.5 million observations in 380 German regions from 2013 Q1 to 2018 Q4. The clusters are then analysed by means of further economic and socioeconomic data in order to identify similarities. Furthermore, the clusters are interpreted from a geographic perspective. We find that the allocation to cluster 1 is always supported by higher growth rates in the variables, population, working population and real GDP, implying higher demand for space. Moreover, in each of the analysed categories cluster 1 reveals a lower unemployment rate as well as a higher disposable income. One of the most interesting implications is, that apparently a large part of the German population has developed into professional real estate investors. In Germany the largest share of landlords is the one of the so-called non-professional landlords. As the regions assigned to cluster 1, displaying the most significant price increase, seem to be chosen based on a very sophisticated market analysis by identifying the regions with the strongest fundamental data, it seems like the dominating market players have significantly increased their knowledge and approach for investing in residential real estate.
39
Benduch, Piotr. "The study of dependency between land-use coverage and parcel boundaries." E3S Web of Conferences 86 (2019): 00006. http://dx.doi.org/10.1051/e3sconf/20198600006.
Full textAbstract:
Land-use constitutes a part of the earth’s surface which is used in a specific, unitary manner. In Poland, data concerning land-uses are registered in the Real Estate Cadastre. This data plays an important role, inter alia, in the context of land properties taxation as well as performing statistical analyses in the field of spatial structure and land development form on various levels of administrative division of a country. Data on land-uses also form basis for activities aimed to agricultural and forest land protection. In this article, the study concerning identification of dependency between parcel boundaries and land-use coverage has been conducted. Occurrence of such a dependency is determined by the characteristics of Polish legal regulations and the fact of carrying out the Real Estate Cadastre in the form of informational system. On this basis it could be concluded that parcel boundary is one of determinants influencing the coverage shape of specific land use form. Using GIS tools, the assessment of size of this impact has been performed at the level of individual land properties as well as the whole cadastral districts. The spatial structure of land-uses in selected cadastral districts in southern Poland has been also compared. The results of analysis were presented both in graphical and analytical form.
40
Liu, Fengyun, Chuanzhe Liu, and Honghao Ren. "Urban Housing Price Fluctuations and Regional Systemic Financial Risks: Panel Spatial Economic Models in Jiangsu, China." Sustainability 10, no. 10 (September 27, 2018): 3452. http://dx.doi.org/10.3390/su10103452.
Full textAbstract:
The regional systemic financial risks driven by escalating urban housing prices have been of great concern recently. Based on the theoretical analyses on the mechanism of formation of regional systemic financial risk driven by urban housing price fluctuations, this paper builds panel spatial economic models to empirically analyze the relationship between urban housing price fluctuations and regional systemic financial risks, in addition to their spatial linkages, in 13 cities in Jiangsu, a representative province of China. The empirical results show the following. (1) The excessive investment or speculation of local governments, banks, real estate developers, individuals, and families on the housing market stimulate the escalation in urban housing prices, leading to the systemic financial risks; (2) Urban housing prices and the land supply price of local governments have strong spatial contagion effects among cities, which will diffuse risks to adjacent cities, causing regional systemic financial risk; (3) Compared with North Jiangsu, South Jiangsu has more serious investment expansion from real estate developers and stronger spatial contagion effects, suggesting the existence of heavier regional systemic financial risks derived from housing price fluctuations; (4) North Jiangsu has slightly stronger “imitative behavior” among local governments, and fewer “substitution effects” of central cities’ demand to adjacent cities’ demand than does South Jiangsu.
41
Ali, Rao Hamza, Josh Graves, Stanley Wu, Jenny Lee, and Erik Linstead. "A Machine Learning Approach to Delineating Neighborhoods from Geocoded Appraisal Data." ISPRS International Journal of Geo-Information 9, no. 7 (July 17, 2020): 451. http://dx.doi.org/10.3390/ijgi9070451.
Full textAbstract:
Identification of neighborhoods is an important, financially-driven topic in real estate. It is known that the real estate industry uses ZIP (postal) codes and Census tracts as a source of land demarcation to categorize properties with respect to their price. These demarcated boundaries are static and are inflexible to the shift in the real estate market and fail to represent its dynamics, such as in the case of an up-and-coming residential project. Delineated neighborhoods are also used in socioeconomic and demographic analyses where statistics are computed at a neighborhood level. Current practices of delineating neighborhoods have mostly ignored the information that can be extracted from property appraisals. This paper demonstrates the potential of using only the distance between subjects and their comparable properties, identified in an appraisal, to delineate neighborhoods that are composed of properties with similar prices and features. Using spatial filters, we first identify regions with the most appraisal activity, and through the application of a spatial clustering algorithm, generate neighborhoods composed of properties sharing similar characteristics. Through an application of bootstrapped linear regression, we find that delineating neighborhoods using geolocation of subjects and comparable properties explains more variation in a property’s features, such as valuation, square footage, and price per square foot, than ZIP codes or Census tracts. We also discuss the ability of the neighborhoods to grow and shrink over the years, due to shifts in each housing submarket.
42
Cellmer, Bełej, and Konowalczuk. "Impact of a Vicinity of Airport on the Prices of Single-Family Houses with the Use of Geospatial Analysis." ISPRS International Journal of Geo-Information 8, no. 11 (October 23, 2019): 471. http://dx.doi.org/10.3390/ijgi8110471.
Full textAbstract:
This article analyses the adverse impact of Chopin Airport in Warsaw on the prices of single-family houses located within the aircraft noise impact zone. The specific feature of the largest airport in Poland is its location within the city limits and the resulting direct surroundings of both multi- and single-family housing developments. Not only is the nuisance due to the proximity of the airport resulting from the actual exposure to an excessive noise level but also from legal restrictions associated with the Limited Use Area (LUA). The study used statistical modeling by applying a classic multiple regression model, spatial autoregressive model and geographically weighted regression model. Moreover, Geographical Information System (GIS) tools and geostatic modeling were used to visualise the results. The modeling results clearly show the significant impact of the neighborhood nuisance and the related spatial distribution of real estate prices. In addition, the geographically weighted regression model indicates that the proximity to an airport adversely affects the rate of price changes over time.
43
Batunova, Elena, and Maria Gunko. "Housing issue in shrinking Russian cities: mapping the reality." Abstracts of the ICA 1 (July 15, 2019): 1–2. http://dx.doi.org/10.5194/ica-abs-1-25-2019.
Full textAbstract:
<p><strong>Abstract.</strong> In Russia, housing issue has been remaining one of the most important political concerns since the beginning of the 20th century. In the recent political discourse, it is associated mainly with the need to provide new housing area and the improvement of housing conditions regardless of the difference in the development of regions or cities. However, the fact that over 70% of Russia’s cities shrink (Batunova and Gunko, 2018) requires developing specific approaches to housing policy’s formulation within depopulating territories.</p><p> The phenomenon of urban shrinkage is generally understood as population decline which results in physical urban infrastructure surplus & degradation. Dilapidated or abandoned houses become the most evident sign of a city’s decline and one of the most important challenges for the local authorities. However, most examples known from the existing literature come from the countries of Western Europe and the US, where economic factors are the main drivers of urban depopulation. The real estate market reacts to the population decline by falling prices (Follain, 2010), which worsens the economic situation in the city and leads to a vicious circle of economic/population decline.</p><p> Less is known about what happens with the housing stock of, in words of J. B. Hollander (2018), ‘atypical shrinking cities’, where demographic aspects are the primary causes of depopulation: the excess of mortality over fertility and ageing. Hollander applied the term ‘atypical’ to Japanese shrinking cities, but in Russia, urban shrinkage is also foremost a result of demographic change (Karachurina, 2013). International migration to Russia does not compensate natural population decline, while the national policies are oriented towards promoting growth in large metropolitan areas (Kinossian, 2013) which intensifies internal migration flows from cities which are not the foci of national development. Consequently, for many Russian cities, especially small peripheral ones, urban shrinkage is an inevitable process.</p><p> Less is known about what happens with the housing stock of, in words of J. B. Hollander (2018), ‘atypical shrinking cities’, where demographic aspects are the primary causes of depopulation: the excess of mortality over fertility and ageing. Hollander applied the term ‘atypical’ to Japanese shrinking cities, but in Russia, urban shrinkage is also foremost a result of demographic change (Karachurina, 2013). International migration to Russia does not compensate natural population decline, while the national policies are oriented towards promoting growth in large metropolitan areas (Kinossian, 2013) which intensifies internal migration flows from cities which are not the foci of national development. Consequently, for many Russian cities, especially small peripheral ones, urban shrinkage is an inevitable process.</p><p> Against this background our research questions are as follows: What happens to housing stock in shrinking Russian cities? What are the preconditions (tools, regulations) for managing housing stock in shrinking Russian cities: official discourse of urban shrinkage, reaction to the transformation of housing demand-supply, main approaches to manage housing excess?</p><p> To answer the first question, we turned to cartographic methods of research. The study of housing in selected shrinking cities (Vorkuta, Komi Republic and Apatity, Murmansk region) was based on visualization of statistical information, crowdsourcing of spatial data and visual decoding of remote sensing data, based on the theory of decryption features for the recognition of objects. To interpret high-resolution images direct (geometry, brightness, and structural) and indirect signs were used. The utilized data includes images from WorldView 1/2/3, QuickBird, GeoEye, which are published on the web mapping services of Yandex.Maps, GoogleMaps, BingMaps (Microsoft), ArcGIS.Imagery (ESRI), Roscosmos Geoportal. Maps of scale 1:10000 and 1:100000 became cartographic data sources. For comparison of data on separate structures regional statistical data of BTI (Technical Inventory Bureau) were used, to identify and verify abandoned houses and apartments field observations were also conducted. The main stage of work was the logical organization of data and the development of the geodatabase structure for the future geoinformation analytical system. All presented information is divided into two types: spatial datasets of different geometry (layers) and tabular data with thematic attribute information. This integrated approach to the state of the urban environment has been implemented for the first time in Russia and, supplemented by the capabilities of automatic spatial analysis in GIS, will identify the most ‘acute’ issues for territorial planning and housing management in shrinking cities. In addition, a series of maps were created visualizing housing features and condition which were presented to the local administrations of the case study cities.</p><p> To answer the second question, we conducted an analysis of the local strategic, planning and policy document as well as interviews with the local stakeholders. The results vary in two cities. While local planning and policy in the realm of housing in Vorkuta are adequate to the identifies housing issues, in Apatity local development plans still serve land provision for the future ‘dreamt’ housing construction, needs of which are calculated based on over-optimistic demographic projections that do not consider the real factors influencing population development.</p>
44
Polic, Darko, and Aleksandra Stupar. "Urban heritage reconsidered: Redefining the planning approach to historical areas of Novi Sad." Spatium, no. 33 (2015): 92–99. http://dx.doi.org/10.2298/spat1533092p.
Full textAbstract:
The beginning of the 21st century was marked by significant socio-economic changes in Serbia, which influenced urban environment and development strategies. Novi Sad, the capital of the Serbian province of Vojvodina, also followed this pattern, adjusting to the new social and spatial dynamic. The shift from a socialist to a neo-liberal model of planning was visible in different spheres - the system of stakeholders was altered, public funds were substituted with small private investors, while existing regulations were either overlooked or interpreted in a questionable manner. Simultaneously, the newly established real estate market mostly focused on the areas around the traditional urban core which underwent a process of quasi-regeneration. Used only as an opportunity for new speculative development, it did not have any respect for either tangible or intangible heritage. However, a decline in real estate development (since 2009) has created a setting for a different planning approach to include consideration of problems of heritage areas. Considering the socio-economic background of recent urban transformations in Novi Sad?s inner-city neighbourhoods, this article analyses the context of the problem, provides recommendations for improvements in the approach to planning, and introduces guidelines and rules for site-sensitive urban and architectural design.
45
Kazak, Jan, Tong Wang, and Szymon Szewrański. "Analysis Of Land Use Transformation Potential In Spatial Management." Real Estate Management and Valuation 23, no. 1 (March 1, 2015): 5–14. http://dx.doi.org/10.1515/remav-2015-0001.
Full textAbstract:
Abstract The current system of spatial planning in Poland does not provide an effective and efficient tool for controlling planning decisions at a level higher than local. The result is an unrealistic approach to adopting development policies. Nowadays there is strong competition among local governments to attract investors, which results in excessive designation of investment areas and, consequently, an imbalance between supply and demand on the real estate market. An extremely important factor from the point of view of local authorities is also the financial burden on government budgets related to the implementation of the provisions of previously adopted policies. An improper spatial development policy can therefore generate costs without delivering the expected results, due to the lack of demand for the offered resources. A step in the right direction in optimizing how the spatial policy process is shaped may include conducting analyses and forecasts to support the decision-making process. Such analyses are needed both in terms of the amount of areas designed for each type of land use as well as their spatial distribution. Our considerations are focused on the second aspect. Analysis of land use transformation potential can be used in spatial management by selecting areas most where land use is most likely to change. The paper presents the simplified mechanisms of such analyses which can be adopted by the use of cellular automata. The final potential of an area is affected by variables such as the neighborhood, accessibility and suitability. As a result of the integration of these variables, it is possible to determine land use transformation potential. These considerations relate to the MOLAND (Monitoring Land Use/Cover Dynamics) research project and works on the development of the Metronamica decision support system, conducted in Western Europe.
46
Nzau, Bernard, and Claudia Trillo. "Affordable Housing Provision in Informal Settlements through Land Value Capture and Inclusionary Housing." Sustainability 12, no. 15 (July 24, 2020): 5975. http://dx.doi.org/10.3390/su12155975.
Full textAbstract:
Public-driven attempts to provide decent housing to slum residents in developing countries have either failed or achieved minimal output when compared to the growing slum population. This has been attributed mainly to shortage of public funds. However, some urban areas in these countries exhibit vibrant real estate markets that may hold the potential to bear the costs of regenerating slums. This paper sheds light on an innovative hypothesis to achieve slum regeneration by harnessing the real estate market. The study seeks to answer the question “How can urban public policy facilitate slum regeneration, increase affordable housing, and enhance social inclusion in cities of developing countries?” The study approaches slum regeneration from an integrated land economics and spatial planning perspective and demonstrates that slum regeneration can successfully be managed by applying land value capture (LVC) and inclusionary housing (IH) instruments. The research methodology adopted is based on a hypothetical master plan and related housing policy and strategy, aimed at addressing housing needs in Kibera, the largest slum in Nairobi, Kenya. This simulated master plan is complemented with economic and residual land value analyses that demonstrate that by availing land to private developers for inclusionary housing development, it is possible to meet slum residents’ housing needs by including at least 27.9% affordable housing in new developments, entirely borne by the private sector. Findings suggest that under a robust public-led governance umbrella, market forces can (1) significantly contribute to fill the financial gap in order to achieve the end of slums by 2050 in coherence with the United Nations Agenda 2030 targets and principles, and (2) increase both affordable and market housing in upgraded neighbourhoods, hence enhancing social inclusion in cities of developing countries.
47
Lao, L. J., and B. J. Harder. "GATEWAY: A GEOSPATIAL ANALYTICS SYSTEM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W19 (December 23, 2019): 283–88. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w19-283-2019.
Full textAbstract:
Abstract. This paper presents an overview of the Gateway web platform, a proprietary geospatial analytics system developed by Cobena Business Analytics and Strategy, Inc.1 The application is intended to serve as a user-friendly and easily-accessible tool for spatial data analysis and visualization geared toward non-technical specialists. Gateway’s core functionalities hinge on mapping and data visualization (choropleths and points) alongside traditional scoring methods and built-in machine learning algorithms for area prioritization and site selection. Gateway provides an interactive, cloud-based environment that abstracts and simplifies common location-based analyses. A core strength of the platform is also its heavy localization to the Philippine context through a curated database of market information — with future plans to create local counterparts across SEA — which reduces the need for extensive external market data collection and reconciliation. The paper gives a brief review of the system design and key features of the platform. It also highlights some key applications across industries such as real estate, consumer goods, and retail in informing expansion and distribution strategies, prioritizing resource allocation, and analyzing historical performance against market factors.
48
Gergelova, Marcela Bindzarova, Zofia Kuzevicova, Slavomir Labant, Stefan Kuzevic, Diana Bobikova, and Jozef Mizak. "Roof’s Potential and Suitability for PV Systems Based on LiDAR: A Case Study of Komárno, Slovakia." Sustainability 12, no. 23 (November 30, 2020): 10018. http://dx.doi.org/10.3390/su122310018.
Full textAbstract:
The case study focuses on evaluating the suitability of roof surfaces in terms of their solar potential based on their geometric parameters. The selected processing methodology detects segments of roof surfaces from the LiDAR base, supplemented with spatial information (orthophoto map, real estate cadastre (REC)—footprint, basic database for the geographic information system (ZBGIS)—classification of buildings—current use). The approach based on spatial analyses takes into account the limit conditions for determining the impact of solar radiation resulting from the roof area, slope, aspect, and hillshade. Considering to the available subsidy scheme for family houses in the conditions of the Slovak Republic, a narrower sample of 35 family houses was selected from the total number of typologically represented buildings (194). A 3D model of the building created by combining REC and LiDAR substrates shows the roof surface without overlap, while another 3D model made of LiDAR substrates alone represents the actual dimension of the roof surface. The results presented for each selected building show good agreement with each other, and their visualizations were obtained using two GIS environment approaches. In the area of family houses, up to 94% of the roof areas of buildings registered in the REC meet the conditions for the installation of a PV system with an output of 2.6/3.3 kW.
49
Salama, Ashraf M., Florian Wiedmann, Alain Thierstein, and Wafa Al Ghatam. "KNOWLEDGE ECONOMY AS AN INITIATOR OF SUSTAINABLE URBANISM IN EMERGING METROPOLISES: THE CASE OF DOHA, QATAR." International Journal of Architectural Research: ArchNet-IJAR 10, no. 1 (April 26, 2016): 274. http://dx.doi.org/10.26687/archnet-ijar.v10i1.927.
Full textAbstract:
This paper is a comprehensive coverage of a research project of the National Priority Research Program of the Qatar National Research Fund, entitled ‘Investigating the Qualities of the Urban Environment in Emerging Regional Metropolises’, and carried out between 2011 and 2014 through the joint collaboration of Qatar University and Technische Universität München. Through the shift of global economic forces Gulf cities, such as Qatar’s capital Doha, are developed as central hubs between developed economies in the West and the rising economies of Asia. In the context of international competition between cities new challenges are emerging where cities need to find ways to sustain and extend their position in a globalizing world. Therefore the research process placed emphasis on the complex interrelationship of knowledge economies and spatial developments in the Gulf region. The work is premised on the assumption that non-physical economic aspects and the qualities of the urban environment are interdependent. It analyses the qualities of the urban environment of Doha as an important regional metropolis through a comprehensive investigation utilizing a set of interdisciplinary research methods that include analysis of historic documents, Delphi interview series, company network analysis, GIS analysis, cognitive mapping, behavioural studies, media surveys, attitude surveys, and space syntax analysis. The outcomes promise important results regarding urban qualities in the city of Doha culminating into various recommendations aimed at potential beneficiaries including public sector organizations, private sector and real estate development companies, and academia.
50
Wójciak, Ewelina. "The Essence of Equivalent Markets in Determining the Market Value of Land Property for Variable Planning Factors." Real Estate Management and Valuation 24, no. 3 (September 1, 2016): 71–82. http://dx.doi.org/10.1515/remav-2016-0022.
Full textAbstract:
Abstract The leading local legislation act defining the spatial policy is the local development plan, the financing of which is the commune’s responsibility. The beneficiary of activities aimed at the transformation of the intended property use is its owner or its perpetual lessee – with lessees incurring the costs of adopting the local development plans through so-called zoning fees, the amount of which, often controversial, has become the source of numerous lawsuits. The presented problem of an outside-business and often radical change of land value corresponds to the market dilemmas in determining equivalent markets, and establishing price-setting factors and their impact on the value of real estate. Circles of analysts and appraisers determine equivalent markets radially. This means that the analyzed or valued property is the central point of the monitored area, incorrectly “enclosed” within the geometry of a circle. Such a perception of the dispersion of transaction prices does not reflect the actual nature of the market, as evidenced by the analyses of land property values according to their planning factors, carried out as part of the present paper. The focal point of the article is a continuous map of land value developed for properties located within the cadastral unit of Podgórze of the city of Krakow which indicates that it is not legitimate to arbitrarily take on the radial approach when designating equivalent markets, which was indirectly approved by Waldo Tobler claiming that: “Everything is related to everything else, but near things are more related than distant things” (Tobler 1970).