Urban Science and Real Estate Dynamics: Insights into Housing, Finance, and Land Use

Topic Information

Dear Colleagues,

The journals of Real Estate, Land, Urban Science, and Architecture invite submissions that explore the complex relationships shaping contemporary urban environments, particularly how housing markets, financial mechanisms, and land use policies interact within the broader framework of urban science. Topics may include housing affordability and supply, land value capture, zoning and regulatory impacts, real estate finance and investment, infrastructure development, urban spatial modeling, and the role of data and technology in understanding urban systems.

We also welcome original research, theoretical contributions, and policy-oriented analyses that examine the role of climate adaptation in housing development, the impact of PropTech on property markets and land economics, and the integration of sustainability goals into urban planning. As urban environments face growing pressures from environmental change and digital disruption, this Topic expands to advance scholarly dialogue on how climate resilience and technological innovation are reshaping real estate and land use. Topics of interest include—but are not limited to—green housing finance, climate risk and property valuation, smart city infrastructure, digital platforms in real estate, and policy mechanisms for sustainable urban growth. Interdisciplinary approaches and empirical studies using novel data or methods are particularly encouraged.

The participants can select one of the four above journals to submit their papers, provided they fall within the scope of the selected journal.

Dr. Xin Janet Ge
Dr. Jyoti Shukla
Dr. Godwin Kavaarpuo
Dr. Shuya Yang
Prof. Dr. Piyush Tiwari
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Architecture architecture	2.1	2.5	2021	21.4 Days	CHF 1200	Submit
Land land	3.5	6.4	2012	16.4 Days	CHF 2600	Submit
Real Estate realestate	-	-	2024	26.9 Days	CHF 1000	Submit
Urban Science urbansci	3.2	3.7	2017	20.8 Days	CHF 1800	Submit

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Published Papers (7 papers)

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23 pages, 2022 KB  

Open AccessArticle

Time-Varying Impact Effects of Housing Financialization on Fiscal Deficits: Mediated by Land Finance and Local Government Debt

by Jinyan Wu, Chenli Meng and Xuewei Zhang

Land 2026, 15(6), 1009; https://doi.org/10.3390/land15061009 - 8 Jun 2026

Viewed by 547

Abstract

The rapid expansion of housing financialization (REF) has profoundly reshaped China’s subnational fiscal landscape, yet the dynamic nature of this relationship remains under-explored. This study investigates how the impact of REF on fiscal deficits (DB) evolves over time and [...] Read more.

The rapid expansion of housing financialization (REF) has profoundly reshaped China’s subnational fiscal landscape, yet the dynamic nature of this relationship remains under-explored. This study investigates how the impact of REF on fiscal deficits (DB) evolves over time and identifies the specific transmission channels mediating this influence. First, we construct a multidimensional REF index by integrating enterprise, household, market, financial, and industry indicators via the fuzzy-TOPSIS method. A Markov Regime Switching model identifies three distinct volatility regimes, revealing that REF dynamics are highly sensitive to policy shifts and exhibit significant path dependency. Second, using a Time-Varying Parameter Vector Autoregression model, we find that REF initially functioned as a fiscal stabilizer providing short-term revenue relief; however, as financialization deepened, REF transformed into a procyclical driver of deficit expansion. Third, we further decompose this mechanism, demonstrating that land finance (LAND) and local government debt (UID) amplify systemic fiscal fragility as dynamic mediating channels. Finally, due to the unsustainability of the current “real estate-land-debt” model, we propose policy interventions including the institutionalization of fiscal-debt firewalls, the formation of counter-cyclical fiscal risk reserve funds, and an accelerated transition toward a stable, tax-oriented revenue structure to mitigate systemic risks. Full article

(This article belongs to the Topic Urban Science and Real Estate Dynamics: Insights into Housing, Finance, and Land Use)

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31 pages, 1160 KB  

Open AccessSystematic Review

Benefits and Challenges of Blockchain Technology in Real Estate: A Systematic Literature Review

by Dengjin Wu, Xin Janet Ge and Jianlong Zhou

Real Estate 2026, 3(2), 6; https://doi.org/10.3390/realestate3020006 - 31 May 2026

Viewed by 1570

Abstract

The real estate sector continues to face challenges such as inefficiencies, fraud risks, and high transaction costs stemming from opaque processes and heavy reliance on intermediaries. These challenges highlight the need for transparent and efficient solutions to support secure real estate transactions and [...] Read more.

The real estate sector continues to face challenges such as inefficiencies, fraud risks, and high transaction costs stemming from opaque processes and heavy reliance on intermediaries. These challenges highlight the need for transparent and efficient solutions to support secure real estate transactions and management. While a growing body of literature has examined blockchain applications in real estate, existing studies are often fragmented and predominantly descriptive, with limited systematic synthesis of evidence and insufficient attention to governance and institutional contexts. This study aims to systematically examine and synthesise the benefits and challenges of blockchain technology in real estate, providing evidence-based insights for practitioners and policymakers. Using a Systematic Literature Review (SLR) approach, peer-reviewed publications from 2016 to 2025 were analysed to identify blockchain applications, reported outcomes, and implementation barriers. The findings reveal that blockchain has been applied in land registration (e.g., Sweden, India, Serbia), valuation systems, decentralised housing finance, and tokenised investment platforms (e.g., Exporo, RealT). The reported benefits include reduced fraud, enhanced transaction efficiency, transparency, and expanded investment access through fractional ownership. However, regulatory uncertainty, scalability limitations, data privacy risks, and low stakeholder awareness remain key barriers. Ethical issues such as digital exclusion and data exposure also require further consideration. Compared with the more advanced adoption observed in Europe and North America, supported by established regulatory frameworks and digital land governance initiatives, this review identifies relatively slower uptake in parts of the Asia-Pacific region, particularly in Australia and Malaysia. It highlights a critical need for future research on legal recognition, privacy-enhancing technologies, and governance frameworks, particularly regarding blockchain applications in property development and urban planning processes. By integrating technological and governance perspectives, this study provides a more comprehensive and structured understanding of blockchain adoption in real estate systems. Full article

(This article belongs to the Topic Urban Science and Real Estate Dynamics: Insights into Housing, Finance, and Land Use)

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16 pages, 1559 KB  

Open AccessArticle

Analysis of Policy Effectiveness for Curbing Real Estate Speculation in Korea—Seoul City Areas Subject to Permission of Land Transaction

by Kyung-Hyun Park, Seung-Ho Cha and Chang-Moo Lee

Land 2026, 15(3), 415; https://doi.org/10.3390/land15030415 - 3 Mar 2026

Viewed by 1193

Abstract

This study empirically examines the impact of the Areas subject to permission of transaction (ASPLT) implemented by Seoul City on local real estate markets. Focusing on the case of the Seoul International District (MICE project area), where the regulated area (the geo-graphical districts [...] Read more.

This study empirically examines the impact of the Areas subject to permission of transaction (ASPLT) implemented by Seoul City on local real estate markets. Focusing on the case of the Seoul International District (MICE project area), where the regulated area (the geo-graphical districts subject to ASPLT) was initially designated, lifted, and later re-imposed, the analysis employs a modified repeat sales Difference-in-Differences (DID) methodology to assess its policy effect on housing price stabilization. The results indicate that the regulated areas experienced more subdued transaction volumes and price increases compared to non-regulated areas, suggesting the policy was effective in curbing short-term speculative demand. Additionally, neighboring areas exhibited signs of spillover effects due to displaced investment interest. The findings highlight both the utility and limitations of localized real estate controls and offer empirical insights for future policy design. Full article

(This article belongs to the Topic Urban Science and Real Estate Dynamics: Insights into Housing, Finance, and Land Use)

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21 pages, 3715 KB  

Open AccessArticle

Mapping and Monitoring Peri-Urban Territorial Dynamics Using Multi-Source Geospatial Data: A Case of the Casablanca Region

by Asmaa Moussaoui, Ilyas Maataoui, Yassir Ait Youssef, Imane Sebari and Kenza Aitelkadi

Urban Sci. 2026, 10(2), 101; https://doi.org/10.3390/urbansci10020101 - 5 Feb 2026

Cited by 3 | Viewed by 1596

Abstract

Peri-urbanization is one of the most complex and rapidly territorial phenomena in African metropolitan areas, including Morocco. This dynamic, characterized by unplanned urban growth, presents significant challenges in terms of land management and sustainable territorial planning. In this context, this work proposes a [...] Read more.

Peri-urbanization is one of the most complex and rapidly territorial phenomena in African metropolitan areas, including Morocco. This dynamic, characterized by unplanned urban growth, presents significant challenges in terms of land management and sustainable territorial planning. In this context, this work proposes a methodology for detecting and analyzing peri-urban areas using a deep learning model based on the Global Human Settlement Layer and Global Land Analysis and Discovery Land Cover data. The Multi-Layer Perceptron model was trained on a manually annotated dataset covering the Casablanca metropolitan region and then used to classify the area into four categories: urban, peri-urban, rural, and water. Model interpretability was ensured through the Shapley Additive Explanations method, and a diachronic analysis was conducted from 2005 to 2025. The model achieved high accuracy (90.6%), with strong performance in identifying urban (F1 ≈ 0.996) and rural (F1 ≈ 0.94) areas. However, peri-urban areas represent some challenges, which result in a lower F1-score of about 0.63 due to transitional land patterns. The results reveal a significant expansion of peri-urban areas (+28,000 ha) at the expense of rural lands. These findings offer valuable insights for policymakers to develop sustainable land-use planning strategies and to anticipate urban sprawl dynamics. Full article

(This article belongs to the Topic Urban Science and Real Estate Dynamics: Insights into Housing, Finance, and Land Use)

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15 pages, 1201 KB  

Open AccessFeature PaperReview

50 Years of Research in Real Estate Brokerage: A Semi-Systematic Literature Review

by Martin Ahlenius, Björn Berggren and Neville Hurst

Real Estate 2025, 2(4), 21; https://doi.org/10.3390/realestate2040021 - 4 Dec 2025

Cited by 3 | Viewed by 2903

Abstract

Intermediaries are central to complex transactions. In housing markets, real estate brokers coordinate information flows, reduce search costs, and guide lay buyers and sellers through legal and financial steps. Despite this importance, scholarship on brokerage is dispersed across disciplines and methods. This paper [...] Read more.

Intermediaries are central to complex transactions. In housing markets, real estate brokers coordinate information flows, reduce search costs, and guide lay buyers and sellers through legal and financial steps. Despite this importance, scholarship on brokerage is dispersed across disciplines and methods. This paper presents a semi-systematic review of peer-reviewed articles published between 1970 and 2021. We map (i) study characteristics (country of origin and field), (ii) the distribution of units of analysis (individual, firm/organization, market), and (iii) the most frequently examined topics. Our synthesis indicates steadily rising academic interest but a fragmented knowledge base. We conclude by highlighting gaps—especially the scarcity of cross-country comparisons and the relative lack of qualitative and mixed-method studies on brokers’ practices and experiences. Full article

(This article belongs to the Topic Urban Science and Real Estate Dynamics: Insights into Housing, Finance, and Land Use)

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23 pages, 852 KB  

Open AccessArticle

Open Data to Promote the Economic and Commercial Development of the Housing Sector: The Case of Spain

by Ricardo Curto-Rodríguez, Rafael Marcos-Sánchez, Alicia Zaragoza-Benzal and Daniel Ferrández

Urban Sci. 2025, 9(7), 277; https://doi.org/10.3390/urbansci9070277 - 17 Jul 2025

Cited by 1 | Viewed by 3149

Abstract

Data is the starting point for generating information and knowledge in the decision-making process. Open data, which is information disclosed free of charge through open licenses and reusable formats, has great potential for value creation. Therefore, the objective of this research is to [...] Read more.

Data is the starting point for generating information and knowledge in the decision-making process. Open data, which is information disclosed free of charge through open licenses and reusable formats, has great potential for value creation. Therefore, the objective of this research is to evaluate Spanish autonomous communities’ open data initiatives in a category of information of vital importance: housing. The methodology employed was a population analysis of datasets labeled as housing, followed by a necessary data cleansing process due to the identification of various errors, which reduced the number of labeled datasets from 1000 to 599. Only 12 of the 17 autonomous communities provided this type of information. The analysis of the results reveals that autonomous communities’ approaches to open data initiatives are highly heterogeneous and that the supply is irregular, with the Basque Country accounting for 70% of the datasets considered in the research. The creation of an indicator that equally assesses the existence of information and file formats (breadth and reusability) continues to identify the Basque Country as the undisputed leader, with Catalonia and Cantabria in second and third place, the only autonomous communities to exceed 50 points out of a possible 100. The study concludes by highlighting that the lack of uniformity in the formulation and implementation of open data policies will limit the use of information and, consequently, its value. Therefore, a series of recommendations is issued in this regard. Full article

(This article belongs to the Topic Urban Science and Real Estate Dynamics: Insights into Housing, Finance, and Land Use)

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30 pages, 14631 KB  

Open AccessArticle

Unsupervised Plot Morphology Classification via Graph Attention Networks: Evidence from Nanjing’s Walled City

by Ziyu Liu and Yacheng Song

Land 2025, 14(7), 1469; https://doi.org/10.3390/land14071469 - 15 Jul 2025

Cited by 5 | Viewed by 2203

Abstract

Urban plots are pivotal links between individual buildings and the city fabric, yet conventional plot classification methods often overlook how buildings interact within each plot. This oversight is particularly problematic in the irregular fabrics typical of many Global South cities. This study aims [...] Read more.

Urban plots are pivotal links between individual buildings and the city fabric, yet conventional plot classification methods often overlook how buildings interact within each plot. This oversight is particularly problematic in the irregular fabrics typical of many Global South cities. This study aims to create a plot classification method that jointly captures metric and configurational characteristics. Our approach converts each cadastral plot into a graph whose nodes are building centroids and whose edges reflect Delaunay-based proximity. The model then learns unsupervised graph embeddings with a two-layer Graph Attention Network guided by a triple loss that couples building morphology with spatial topology. We then cluster the embeddings together with normalized plot metrics. Applying the model to 8973 plots in Nanjing’s historic walled city yields seven distinct plot morphological types. The framework separates plots that share identical FAR–GSI values but differ in internal organization. The baseline and ablation experiments confirm the indispensability of both configurational and metric information. Each type aligns with specific renewal strategies, from incremental upgrades of courtyard slabs to skyline management of high-rise complexes. By integrating quantitative graph learning with classical typo-morphology theory, this study not only advances urban form research but also offers planners a tool for context-sensitive urban regeneration and land-use management. Full article

(This article belongs to the Topic Urban Science and Real Estate Dynamics: Insights into Housing, Finance, and Land Use)

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