Search Results (74)

Megacity regions mark a transformative phase of urbanisation, in which interconnected cities undergo land-use and land-cover change (LUCC) that extends beyond administrative boundaries. However, the drivers of cross-boundary LUCC remain insufficiently examined, particularly before the top-down regional integration. The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) provides a clear empirical case, having experienced cross-boundary LUCC prior to its formal designation as a megacity region in 2018. This study builds a Landsat-derived LUCC and driver dataset for the GBA. Global and local spatial autocorrelation (Moran’s I and LISA) are used to characterise spatial structure and clustering, and geographically weighted regression identifies the socio-economic and environmental determinants of built-up expansion over 1980–2018, spanning the pre-reform decade and the post-1990 land-transfer era. Findings reveal that: (1) LUCC in the GBA already exhibited a cross-border, spatially networked expansion pattern before formal regional integration policies at the national level, with built-up area growth extending beyond core cities into decentralised urban nodes. Two prominent cross-border cores and one cross-administrative core emerged, suggesting that regional integration was co-led by market forces and local governments before an institutional framework was established. (2) Although the GBA showed a clear trend towards integrated development, urban expansion was highly uneven. Such spatial disparities were mainly driven by varying socioeconomic and natural factors, including gross domestic product, population growth, real estate investment, water resource proximity, and infrastructure development. These findings enhance understanding of megacity-region dynamics and offer insights from the GBA for cross-border urbanisation and sustainable spatial governance. Full article

Africa has always been among the top geopolitical priorities for the EU due to the continent’s close geographical proximity and long-standing economic ties. The agro-food trade between the EU27 and Africa is extremely important for both subjects and not only in terms of food security, as it is also a useful tool to secure a long-term partnership between the two continents, making them true and reliable allies ready to give support to each other, especially in the current unstable global situation. The analyzed data were taken from the official publications of the Eurostat (ESTAT). The time frame under analysis is 23 time periods—from 2002 to 2024 inclusive. Such methods and tools of scientific research as textual and tabular methods, empirical, statistical and comparative analyses, as well as the logical method, comprising deductive and inductive reasoning, time series analysis, modelling and forecasting, methods of time series data decomposition, etc. were used while conducting the research presented in the given article. The results for the time series analysis, modelling and forecasting assume the projections for the next four time periods for the EU27 to Africa agro-exports to be around their last observed value, slightly fluctuating or increasing with a delicateslope. The EU27 from Africa agro imports for the next four time periods are projected to increase, with a rather sharp slope. The research and its results can be of great help for public administrators, decision makers, academic community representatives, statisticians, and data analysts. Full article

The aim of this paper is to demonstrate to what extent the ambiguity and excessive detail of the provisions of local spatial development plans (LSDPs) lead to an increase in investment risk and destabilization of the real estate market. The analysis was conducted based on a study of the content of selected LSDPs and their impact on property values and investment processes. The scope of the study includes the analysis of cases of municipalities (local administrative units) with a different approach to spatial planning as well as Polish regulations in the field of spatial planning. Case studies of cities and areas in which the adopted local plans had an impact on investment decisions and property values were taken into account. The conclusions from the analysis will be used to assess the effectiveness of the regulations used and to formulate recommendations regarding the optimization of the spatial planning in a way that enables the harmonious combination of the interests of investors, residents, and local government authorities. Full article

Urban health planning requires a multi-scalar understanding of the territory, capable of capturing socio-economic inequalities and health needs at the local level. In the case of Rome, current administrative subdivisions—Urban Zones (Zone Urbanistiche)—are too large and internally heterogeneous to serve as effective units for equitable health planning. This study presents a methodology for the territorial redefinition of Rome’s Municipality III, aimed at supporting healthcare planning through an integrated analysis of census sections. These were grouped using a combination of census-based socio-demographic indicators (educational attainment, employment status, single-person households) and real estate values (OMI data), alongside administrative and road network data. The resulting territorial units—21 newly defined Mesoareas—are smaller than Urban Zones but larger than individual census sections and correspond to socio-territorially homogeneous neighborhoods; this structure enables a more nuanced spatial understanding of health-related inequalities. The proposed model is replicable, adaptable to other urban contexts, and offers a solid analytical basis for more equitable and targeted health planning, as well as for broader urban policy interventions aimed at promoting spatial justice. Full article

Urban growth often surpasses the actual needs of the population, leading to inefficient land use and long-term environmental challenges. This study provides an integrated perspective on urban landscape transformation by linking socio-demographic dynamics with ecological consequences, notably vegetation loss and increased impervious surfaces. The study area is Năvodari Administrative-Territorial Unit (ATU), a coastal tourist city located along the Black Sea in Romania. By integrating geospatial datasets such as Urban Atlas and Corine Land Cover with population- and construction-related statistics, the analysis reveals a disproportionate increase in urbanized land compared to population growth. Time-series analyses based on the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) from 1990 to 2022 highlight significant ecological degradation, including vegetation loss and increased built-up density. The findings suggest that real estate investment and tourism-driven development play a more substantial role than demographic dynamics in shaping land use change. Understanding urban expansion as a coupled social–ecological process is essential for promoting sustainable planning and enhancing environmental resilience. While this study is focused on the coastal city of Năvodari, its insights are relevant to a broader international context, particularly for rapidly developing tourist destinations facing similar urban and ecological pressures. The findings support efforts toward more inclusive, balanced, and environmentally responsible urban development, aligning with the core principles of Sustainable Development Goal 11, particularly Target 11.3, which emphasizes sustainable urbanization and efficient land use. Full article

3D (three-dimensional) property volume is an important data carrier for 3D land administration by using 3D cadastral technology, which can be used to express the legal space (property rights) scope matching with physical entities such as buildings and land. A 3D property volume is represented by a dense set of 3D coordinate points arranged in a predefined order and is displayed alongside the parcel map for reference and utilization by readers. To store a 3D property volume in the database, it is essential to record the connectivity relationships among the original 3D coordinate points, the associations between points and lines for representing boundary lines, and the relationships between lines for defining surfaces. Only by preserving the data structure that represents the relationships among points, lines, and surfaces can the 3D property volume in a parcel map be fully reconstructed. This approach inevitably results in the database storage volume significantly exceeding the original size of the point set, thereby causing storage redundancy. Consequently, this paper introduces a reversible 3D property volume compression coding method (called 3DPV-CC) to address this issue. By analyzing the distribution characteristics of the coordinate points of the 3D property volume, a specific rule for sorting the coordinate points is designed, enabling the database to have the ability of data storage and recovery by merely storing a reordered point set. The experimental results show that the 3DPV-CC method has excellent support capabilities for 3D property volumes of the vertical and slopped types, and can compress and restore the coordinate point set of the 3D property volume for drawing 3D parcel maps. The compression capacity of our method in the test is between 23.66% and 38.42%, higher than the general data compression methods (ZIP/7Z/RAR: 8.37–10.32%). By means of this method, land or real estate administrators from government departments can store 3D property volume data at a lower cost. This is conducive to enhancing the informatization level of land management. Full article

Urban transformations require balancing private real estate interests with the provision of public spaces that enhance sustainability and ecosystem services. This study proposes a probabilistic model to assess the feasibility of transforming buildable areas while ensuring equitable benefits for both private developers and public administrations, with a focus on three areas to be regenerated within the Municipality of Lucca as case studies. Applying the Monte Carlo (MC) method, two probabilistic models—one with a Uniform distribution and the other with a Normal distribution—estimate the expected Transformation Value (TV) and its associated uncertainty. Results highlight the effectiveness of MC-based assessments in managing financial uncertainty, aiding developers in risk evaluation, and supporting policymakers in designing balanced urban planning indices. It was observed that the Uniform model is better suited to situations in which the initial values of the model’s main variables—such as construction costs, post-transformation market value, or transformation duration—are not fully known, whereas the Normal model provides more accurate estimates when the investment scenario is better understood. The results demonstrate that this approach provides, on the one hand, a robust tool for investment risk analysis to private investors and, on the other hand, a way for public institutions to verify whether urban planning indices enable private promoters to contribute effectively to the development of sustainable cities. Full article

The present research aims at identifying any changes in the market appreciations of the residential segment in Italy caused by the COVID-19 pandemic. With reference to the first half of 2023 (phase III, “post-COVID-19”), in the paper, a logical–operational methodology is implemented: a sample of properties sold in the two-month period January–February 2023 is collected and an econometric analysis is applied for determining (i) the most influential factors on selling prices and (ii) the functional links between prices and each selected explanatory variable. Furthermore, the findings obtained are compared with those related to the phases I, “ante-COVID-19”, and II, “COVID-19 in itinere” (by recalling a previous study of the same authors), to highlight the variations between the periods and provide useful guidelines for the design of domestic spaces in different Italian geographical contexts. In addition, this work conducts a comparison of the outputs derived from the econometric analysis starting from the real estate data collected on the reference markets (revealed preferences) with the results of a direct survey carried out on a sample of individuals through the administration of an ad hoc developed questionnaire and aimed at investigating the opinions of potential buyers of residential properties (stated preferences). The use of the “twin” approach (an analysis of perceptions via the direct survey integrated by the implementation of an econometric technique) allows us to verify the consistence of the real dynamics of market (expressed by the interviewees) with the mathematical model results for investigating the house-scale effects of the COVID-19 pandemic in the considered cities. Full article

The interplay between land management and real estate market dynamics is critical for sustainable development. This study employs behavioral finance theory to explore how irrational behaviors among key market participants, including developers, consumers, and brokers, influence housing prices in China. By examining decision aggregation processes and sociocultural influences, we identify significant behavioral factors such as overconfidence, herding behavior, and availability bias that contribute to real estate price fluctuations. Our empirical analysis, based on data from 2001 to 2018, reveals how these behaviors impact market outcomes and provides insights for improving land administration systems. The findings offer valuable perspectives for policy and strategy development aimed at stabilizing housing markets, promoting sustainable real estate practices, and supporting the achievement of sustainable development goals (SDGs). This research underscores the importance of integrating behavioral finance into land management to enhance the efficiency and security of land tenure systems. Full article

In post-war environments, property valuation encounters obstacles stemming from widespread destruction, population displacement, and complex legal frameworks. This study addresses post-war property valuation by integrating war-related considerations into the ISO 19152 Land Administration Domain Model, resulting in a valuation information model for Syria’s post-war landscape, serving as a reference for property valuation in conflict-affected areas. Additionally, property valuation is enhanced through visualization modeling, aiding the comprehension of war-related attributes amidst and following conflict. We utilize data from a field survey of 243 Condominium Units in the Harasta district, Rural Damascus Governorate. These data were collected through quantitative interviews with real estate companies and residents to uncover facts about property prices and war-related conditions. Our quantitative data are analyzed using inferential statistics of mean housing prices to assess the impact of war-related variables on property values during both wartime and post-war periods. The analysis reveals significant fluctuations in prices during wartime, with severely damaged properties experiencing notable declines (about −75%), followed by moderately damaged properties (about −60%). In the post-war phase, rehabilitated properties demonstrate price improvements (1.8% to 22.5%), while others continue to depreciate (−55% to −65%). These insights inform post-war property valuation standards, facilitating sustainable investment during the post-war recovery phase. Full article

Rapid urban growth necessitates focused attention regarding its policy and governance to ensure affordable housing, transparent and efficient real-world systems, reduce social inequalities, and promote sustainable development. This study delves into the semantics and ontology for developing a Land Administration Domain Model (LADM) profile in the context of Pakistan’s Land Administration Systems (LASs), which currently face issues due to manual record-keeping, lack of transparency, frauds, and disintegration. Establishing a baseline through Record of Rights (RoR) and Property Information Report (PIR), alongside surveying and mapping procedures defined by laws and rules, forms the foundation for LADM profile development. This study explores the transition from manual LAS to 2D/3D representation, using LADM as a conceptual guideline. The LADM profile’s three key packages—PK_Party, PK_Administrative, and PK_SpatialUnit—a sub-package, and external classes are examined, with proposals for digitalisation and modernisation. Additionally, the study includes expert consultation, and highlights the significant support that the LADM implementation offers to achieve Sustainable Development Goals (SDGs) in Pakistan. In conclusion, the study underscores the need for a comprehensive and inclusive approach to address organisational overlaps and ambiguities within LAS, positioning PK LADM as a transformative force for sustainable urban LAS in Pakistan, aligning with broader SDGs. Recommendations include exploring realistic land valuation, integrated ownership and location verification systems, addressing historical survey data challenges, and promoting wider stakeholder adoption for sustainable 2D/3D urban LAS using LADM and its edition II as a way forward towards the creation of a smart city and digital twin. Full article

A growing number of installations for generating energy from renewable sources has provoked an increased response in society. The tendency to support such investments is noticeable. The main actors in the PV market include investors, administrative bodies that issue relevant permits, and communities in locations where such investment projects are planned. Not every property should be allotted for such investments. Some entities are interested in having Renewable Energy Source (RES) installed in their area. This study aims to demonstrate the benefits that local commune governments can gain from implementing PV farms in their area and to perform an analysis of socio-economic and spatial determinants of locating PV farms at the regional level. The scenario method and a multiple regression analysis were applied in this study. The research was conducted for the territory of Poland, taking into consideration the number of PV farms in individual regions/voivodeships (NUTS-2). The results show that the number of PV farms in Poland is not growing evenly. The growth of the investment project number is the greatest in the north and the northwest of Poland. Local commune governments are interested in implementing PV farms because of a much higher income from the real estate tax and because of a decrease in the rate of unemployment among agricultural farm owners. All of these results should be observed from a longer-term perspective to confirm the trends. Full article

With sustainability becoming the new norm, the discussion about followers’ attitudes towards sustainability-oriented leadership is growing globally. Therefore, this study investigates the extent to which employees’ industry and sector background influence their perception of the ideal leader in relation to preferred sustainability orientation. This study also examines preferred sustainability leadership values and the role of culturally endorsed leadership in this process. Using the Preferred Sustainability Leadership Orientation (PSLO) survey, we gathered and analyzed data from 11 countries and 11 industry backgrounds (n = 5530). Our findings show that there is a statistical significance in followers’ valuing a leader with a high sustainability orientation most. Moreover, our results indicate that respondents working in public administration organizations value a leader with a strong sustainability orientation in addition to environmental and equality goals. While respondents associated with agriculture and real estate do not seem to place so much value on an ideal leader focusing on gender equality, in industries such as finance, manufacturing, and real estate, followers seem to value a leader with a stronger focus on profit and less emphasis on promoting gender equality. This research offers implications for the development of the PSLO (preferred sustainable leadership orientation) as a useful sustainability leadership barometer tool for measuring an organization’s sustainability culture and suggests avenues for future research. Full article

Nowadays, European program Copernicus’ Sentinel missions have allowed the development of several application services. In this regard, to strengthen the use of free satellite data in ordinary administrative workflows, this work aims to evaluate the feasibility and prototypal development of a possible service called Sen4MUN for the distribution of contributions yearly allocated to local municipalities and scalable to all European regions. The analysis was focused on the Aosta Valley region, North West Italy. A comparison between the Ordinary Workflow (OW) and the suggested Sen4MUN approach was performed. OW is based on statistical survey and municipality declaration, while Sen4MUN is based on geospatial deep learning techniques on aerial imagery (to extract roads and buildings to get real estate units) and yearly Land Cover map components according to European EAGLE guidelines. Both methods are based on land cover components which represent the input on which the financial coefficients for assigning contributions are applied. In both approaches, buffers are applied onto urban class (LC_b). This buffer was performed according to the EEA-ISPRA soil consumption guidelines to avoid underestimating some areas that are difficult to map. In the case of Sen4MUN, this is applied to overcome Sentinel sensor limits and spectral mixing issues, while in the case of OW, this is due to limits in the survey method itself. Finally, a validation was performed assuming as truth the approach defined by law as the standard, i.e., OW, although it has limitations. MAEs involving LC_b, road lengths and real estate units demonstrate the effectiveness of Sen4MUN. The developed approach suggests a contribution system based on Geomatics and Remote sensing to the public administration. Full article

The Kravarsko area is located in a hilly region of northern Croatia, where numerous landslides endanger and damage houses, roads, water systems, and power lines. Nevertheless, natural hazard management plans are practically non-existent. Therefore, during the initial research, a landslide inventory was developed for the Kravarsko pilot area based on remote sensing data (high-resolution digital elevation models), and some of the landslides were investigated in detail. However, due to the complexity and vulnerability of the area, additional zoning of landslide-susceptible areas was needed. As a result, a slope gradient map, a map of engineering geological units, and a land-cover map were developed as inputs for the landslide susceptibility map. Additionally, based on the available data and a landslide inventory, a terrain stability map was developed for landslide management. Analysis and map development were performed within a geographical information system environment, and the terrain stability map with key infrastructure data was determined to be the “most user-friendly and practically usable” resource for non-expert users in natural hazard management, for example, the local administration. At the same time, the terrain stability map can easily provide practical information for the local community and population about the expected landslide “risk” depending on the location of infrastructure, estates, or objects of interest or for the purposes of future planning. Full article