Special Issue "Property in the Space: Real Estate Spatial Analysis, Land Use, Urban-Rural Interactions, Management and Valuation"

A special issue of Land (ISSN 2073-445X).

Deadline for manuscript submissions: 20 December 2021.

Special Issue Editors

Prof. Dr. Mirosław Bełej
E-Mail Website
Guest Editor
Department of Spatial Analysis and Real Estate Market, University of Warmia and Mazury in Olsztyn, 15 Prawocheńskiego St., 10-720 Olsztyn, Poland
Interests: real estate economics; socio-economic geography; land management; spatial econometrics; housing market analysis; property valuation; cadastral systems, catastrophe theory
Prof. Dr. Małgorzata Krajewska
E-Mail Website
Guest Editor
Department of Geodesy, Spatial Management and Real Estate, UTP University of Science and Technology, Bydgoszcz, Al. prof. S. Kaliskiego 7, 85-796 Bydgoszcz, Poland
Interests: real estate economics; property valuation; market analysis; socio-economic geography; land management; spatial planning; urbanization
Dr. Izabela Rącka
E-Mail Website
Guest Editor
Department of Public Management and Law, Calisia University – Kalisz, Poland, ul. Nowy Świat 4, 62-800 Kalisz, Poland
Interests: real estate economics, property valuation, housing, market analysis, urbanization, urban renewal
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Human economic and social activity takes place in a multi-dimensional space which can be viewed in terms of geographic, economic, natural, social, cultural, and planning dimensions. Rational management in a market economy requires making decisions in the conditions of several spatial conflicts. Strong competition in spatial solutions results most often from the convergence of preferences of individual entities, both public and private, as to specific places in space. The land is the most direct realization of this abstract concept of space, the result of which is a phenomenon of strong competition between different types of land use. The consequence of these processes is the need for administration, management, spatial planning, land tenure, and land valuation. This Special Issue focuses on urban and rural real estate development perspectives in terms of social, economic, and environmental impact. The multidimensionality of real estate creates an opportunity to present interdisciplinary research, as the area of ​​real estate market research is a multifaceted platform for many scientific disciplines. We encourage authors to submit manuscripts on theoretical and practical solutions to spatial conflicts, taking into account the specificity of real estate. The previously mentioned topics are recommended, but the Special Issue is not limited to them. We believe the results of studies on the impact of the Covid-19 pandemic on property prices and land use, as well as gender discrimination and inequality in the acquisition of property rights could be expected.

Prof. Dr. Mirosław Bełej 
Prof. Dr. Małgorzata Krajewska
Dr. Izabela Rącka
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Prof. Dr. Małgorzata Krajewska
Prof. Dr. Mirosław Bełej
Dr. Izabela Rącka
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • land management
  • land use and spatial planning
  • land administration systems
  • land tenure
  • land valuation and mass appraisal
  • integrated rural development
  • sustainable urban development
  • suburbanization
  • landscape ecology
  • real estate market
  • spatial heterogeneity
  • geographic information system and GIS analysis

Published Papers (3 papers)

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Research

Communication
Territorial Extrapolation of Basic Data as a Solution of the Problem of Its Deficiency during Mass Appraisal
Land 2021, 10(7), 750; https://doi.org/10.3390/land10070750 - 17 Jul 2021
Viewed by 548
Abstract
The article is devoted to the application of the territorial extrapolation of basic data method during a mass (cadastral) assessment of a territory that is characterized by an acute lack of market information. In the framework of the study, an acute lack is [...] Read more.
The article is devoted to the application of the territorial extrapolation of basic data method during a mass (cadastral) assessment of a territory that is characterized by an acute lack of market information. In the framework of the study, an acute lack is understood as the conditions when for the assessing territory there are less than five transaction (offer) prices suitable for regression models. The idea of the method is to use market information of territories that are comparable in a composition of pricing factors and the nature of their influence on the cost, as well as in terms of price levels. The developed method includes such stages as collection of basic data, creation of thematic maps, grouping of estimated territories by price level and composition of pricing factors and modeling. The method was applied to assess land plots that have the type of permitted use “for individual housing construction” and belong to the mass appraisal segment “gardening and horticulture, low-rise residential buildings” in the settlements of the Republic of Udmurtia. The results of approbation shown that the method of territorial extrapolation helps to overcome an acute shortage of market information and build statistically significant models of the cadastral values of land plots. Full article
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Article
Novel Exploratory Spatiotemporal Analysis to Identify Sociospatial Patterns at Small Areas Using Property Transaction Data in Dublin
Land 2021, 10(6), 566; https://doi.org/10.3390/land10060566 - 28 May 2021
Viewed by 1027
Abstract
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 [...] Read more.
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. Full article
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Article
Property Mass Valuation on Small Markets
Land 2021, 10(4), 388; https://doi.org/10.3390/land10040388 - 08 Apr 2021
Viewed by 540
Abstract
The main bases for land taxation are its area or value. In many countries, especially in Eastern Europe, reforms of property taxation, including land taxation, are being carried out or planned, introducing property value as a tax base. Practice and research in this [...] Read more.
The main bases for land taxation are its area or value. In many countries, especially in Eastern Europe, reforms of property taxation, including land taxation, are being carried out or planned, introducing property value as a tax base. Practice and research in this area indicate that such a change in the tax system leads to large changes in land use and reallocation. The taxation of land value requires construction of mass valuation system. Different methodological solutions can serve this purpose. However, mass land valuation requires a large amount of information on property transactions. Such data are not available in every case. The main objective of the paper is to evaluate the possibility of applying selected algorithms of machine learning and a multiple regression model in property mass valuation on small, underdeveloped markets, where a scarce number of transactions takes place or those transactions demonstrate little volatility in terms of real property attributes. A hypothesis is verified according to which machine learning methods result in more accurate appraisals than multiple regression models do, considering the size of training datasets. Three types of models were employed in the study: a multiple regression model, k nearest neighbor regression algorithm and XGBoost regression algorithm. Training sets were drawn from a larger dataset 1000 times in order to draw conclusions for averaged results. Thanks to the application of KNN and XGBoost algorithms, it was possible to obtain models much more resistant to a low number of observations, a substantial number of explanatory variables in relation to the number of observations, a low property attributes variability in the training datasets as well as collinearity of explanatory variables. This study showed that algorithms designed for large datasets can provide accurate results in the presence of a limited amount of data. This is a significant observation given that small or underdeveloped real estate markets are not uncommon. Full article
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