Land

34 pages, 6071 KB

Open AccessArticle

Bridging Heritage Systems: Multi-Scale Spatial Coupling Between Tangible and Intangible Cultural Heritage in China Using Hierarchical Bayesian Model and Causal Inference

by Yuxi Liu, Xinyu Du, Yu Bai, Qibing Chen and Shiliang Liu

Land 2025, 14(12), 2386; https://doi.org/10.3390/land14122386 (registering DOI) - 6 Dec 2025

Abstract

Cultural heritage systems play a crucial role in decoding human–environment interactions and social evolution. This study aims to reveal the spatial coupling characteristics of tangible and intangible cultural heritage in China, as well as the heterogeneity of their driving mechanisms. After quantifying heritage [...] Read more.

Cultural heritage systems play a crucial role in decoding human–environment interactions and social evolution. This study aims to reveal the spatial coupling characteristics of tangible and intangible cultural heritage in China, as well as the heterogeneity of their driving mechanisms. After quantifying heritage coupling at three geographic scales, we integrated a hierarchical Bayesian model with a hybrid causal inference framework to identify the correlations, causal effects, and heterogeneity of the driving factors. The empirical results indicate the following: (1) The coupling patterns exhibit scale dependence. The proportion of strongly coupled areas decreases from the prefecture-level scale to the provincial scale but increases at the cultural–geographical unit scale. This suggests that China’s cultural system has a cohesive effect that transcends administrative boundaries. (2) The hierarchical Bayesian model identifies the significant effects of mean annual temperature, population density, GDP–population interaction, transport–hydrological network interaction, and industrial structure. Effect strengths generally peak at the prefecture-level scale and decrease at the provincial scale. (3) Causal inference estimates the causal effects of mean annual temperature, transport–hydrological network interaction, mean annual precipitation, and water network density on coupling. (4) Heterogeneity tests reveal that the positive causal effect of transport–hydrological network interaction and the negative causal effect of mean annual precipitation are significant only in low-temperature regions. By integrating hierarchical modeling with causal verification, this study elucidates the mechanisms underlying heritage coupling. This provides a scientific basis for understanding the spatial patterns of cultural heritage systems and formulating differentiated conservation policies. Full article

(This article belongs to the Special Issue Feature Papers for Land Innovations—Data and Machine Learning: 3rd Edition)

23 pages, 6542 KB

Open AccessArticle

From Rapid Growth to Slowdown: A Geodetector-Based Analysis of the Driving Mechanisms of Urban–Rural Spatial Transformation in China

by Yang Shao and Ren Yang

Land 2025, 14(12), 2385; https://doi.org/10.3390/land14122385 (registering DOI) - 6 Dec 2025

Abstract

Against the backdrop of China’s slowing urbanization and increasing regional disparities, existing research on the spatiotemporal evolution and multidimensional drivers of urban–rural transformation (URT) requires further elaboration, particularly regarding county-level differentiation and the dynamic interactions among these drivers. This study integrates spatiotemporal hot [...] Read more.

Against the backdrop of China’s slowing urbanization and increasing regional disparities, existing research on the spatiotemporal evolution and multidimensional drivers of urban–rural transformation (URT) requires further elaboration, particularly regarding county-level differentiation and the dynamic interactions among these drivers. This study integrates spatiotemporal hot spot analysis with a multi-factor geographical detector model to systematically examine China’s URT from 1990 to 2023. The findings reveal the following: (1) The area of urban–rural construction land increased by 149.54% overall from 1990 to 2023, but the annual average growth rate dropped sharply to 4.32% during 2000–2023, indicating overall deceleration in spatial expansion. (2) Significant structural adjustments occurred at the county level: the proportion of counties with high spatial expansion degree decreased by 20%, while counties experiencing spatial contraction increased by 6%, suggesting that growth dynamics have become increasingly concentrated in limited counties. (3) Spatially, a clear “northern contraction and southern expansion” divergence emerged, which was primarily driven by the synergistic effects of policy reorientation, market-driven factor mobility, and differential natural endowments. (4) Expanding counties benefited from urban agglomeration plans, population influx, industrial upgrading, and favorable terrain, whereas contracting counties were constrained by rigid ecological and farmland conservation policies, population outmigration, undiversified industries, and topographical limitations. These findings provide an important premise for formulating feasible policies on differentiated spatial governance and urban–rural sustainable development. Full article

(This article belongs to the Section Urban Contexts and Urban-Rural Interactions)

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19 pages, 688 KB

Open AccessArticle

Study on the Impact of Land Transfer on Farmers’ Welfare: Theoretical and Empirical Evidence from China

by Zhituan Deng and Jiaojiao Kang

Land 2025, 14(12), 2384; https://doi.org/10.3390/land14122384 (registering DOI) - 6 Dec 2025

Abstract

The transfer of agricultural land has significant effects on farmers’ livelihoods and welfare. This study aims to explore the utility and obstacles of rural land transfer. The research found that in the process of agricultural transformation in developing countries, rural land transfer played [...] Read more.

The transfer of agricultural land has significant effects on farmers’ livelihoods and welfare. This study aims to explore the utility and obstacles of rural land transfer. The research found that in the process of agricultural transformation in developing countries, rural land transfer played a positive role in improving farmers’ welfare. Rural land transfer enables land lessors to obtain physical rent or implicit rent, which increases household income or enhances relationships with relatives and neighbors, generating a positive impact on farmers’ welfare. Land transfer was a comprehensive decision-making of households based on the optimal allocation of factor resources such as land, labor, and capital. Risks associated with land transfer and social security arrangements after transferring land rights have emerged as prominent obstacles. These factors tend to induce anxiety among land-leasing households regarding the livelihood risks their families might face post-transfer, thus making them hesitant and reluctant to engage in land transfer due to lingering concerns over both immediate and long-term interests. The welfare-enhancing effects of land transfer on farmers vary significantly depending on the local rural governance context, household’s social status within the community, and relative importance of internal family opinions in decision-making processes. This study demonstrates that the allocation of production factors should be examined within the overarching framework of urban–rural integration and provides empirical evidence and theoretical insights for central and local governments to refine relevant policy documents. Full article

(This article belongs to the Section Land Socio-Economic and Political Issues)

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28 pages, 1055 KB

Open AccessArticle

A Double-Edged Sword: Farmland Transfer and Productivity Gaps Among Farmers with Diverse Livelihood Capital

by Xueqi Wang, Yuefei Zhuo, Xiaoying Wang, Guan Li and Wei Zou

Land 2025, 14(12), 2383; https://doi.org/10.3390/land14122383 - 5 Dec 2025

Abstract

The modernization of agriculture within developing nations represents a complex challenge at the intersection of social and economic systems. Enhancing agricultural labor productivity (ALP) is the key to increasing farmers’ incomes and promoting rural economic development in low- and middle-income countries. To reveal [...] Read more.

The modernization of agriculture within developing nations represents a complex challenge at the intersection of social and economic systems. Enhancing agricultural labor productivity (ALP) is the key to increasing farmers’ incomes and promoting rural economic development in low- and middle-income countries. To reveal the deep-seated factors that restrict the improvement of ALP, this study, based on the internal and external development constraints of farmers, uses the 2020 data from the China Family Panel Studies (CFPS) database. It systematically analyzes the effects and internal logic of farmers’ livelihood capital and farmland transfer on ALP, employing both an endogenous switching regression model and a generalized structural equation model. The findings of this study are as follows: (1) Physical capital, financial capital and social capital can significantly increase the probability of farmers participating in the farmland transfer and transfer-in. Moreover, physical capital can significantly reduce the probability of farmers participating in the farmland transfer-out. (2) Physical capital is significantly and positively correlated with the ALP of both farmland transfer farmers and non-transfer farmers. Financial capital has a significant positive correlation with the ALP of transfer-in farmers. Social capital is significantly positively correlated with the ALP of non-transfer farmers. (3) Farmland transfer can significantly improve ALP, and the productivity-enhancing effect of farmland transferring-in is considerably more pronounced than that of transferring-out. (4) Mediation analysis reveals that physical and social capital enhance ALP by promoting farmer participation in the farmland transfer market. When classified by different transfer behaviors, physical capital enhances ALP by promoting both the transferring-in and transferring-out of land. Financial capital and social capital can promote farmers’ transfer-in of land to enhance ALP. (5) The heterogeneity analysis shows that, compared with the other two types of farmers, farmland transfer has the most significant effect on improving the ALP of livelihood capital-abundant farmers, while farmland transfer-in has the greatest efficiency improvement effect for capital-deficient farmers, and farmland transfer-out has the greatest efficiency improvement effect for capital-balanced farmers. By providing a detailed, evidence-based model of these complex interactions, this research contributes to the broader understanding of change management and innovation in the pursuit of sustainable and equitable rural futures. Full article

(This article belongs to the Special Issue Spatial Governance Strategies for Enhancing Agricultural Livelihoods at Rural-Urban Transition)

19 pages, 1011 KB

Open AccessArticle

Beyond Rules: Market Logic, Institutional Lag, and the Limits of Floor Space Index Deregulation in Hyderabad

by Raghu Dharmapuri Tirumala and Piyush Tiwari

Land 2025, 14(12), 2382; https://doi.org/10.3390/land14122382 - 5 Dec 2025

Abstract

As rapid urbanisation accelerates in Global South cities, regulatory upzoning is widely promoted as a tool to expand supply and foster compact growth. Yet the interaction between permissive rules, market valuation, and institutional capacity remains underexplored. This article examines Hyderabad’s near two-decade experiment [...] Read more.

As rapid urbanisation accelerates in Global South cities, regulatory upzoning is widely promoted as a tool to expand supply and foster compact growth. Yet the interaction between permissive rules, market valuation, and institutional capacity remains underexplored. This article examines Hyderabad’s near two-decade experiment with Floor Space Index deregulation, introduced through Government Order Ms. No. 86 (2006), which eliminated citywide density caps and allowed premium-based flexibility. Using a geocoded dataset of over 9200 projects matched with government circle rate tables, spatial accessibility measures, and a subset of 2500 properties for regression analysis, this study evaluates how rules, price signals, and institutional arrangements shaped development outcomes through a rules–prices–institutions analytical framework. Results reveal that deregulation produced highly selective verticalisation, with high-rise projects concentrated in the western IT corridor while most of the city retained low-to-mid-rise form. Regression estimates demonstrate that FSI and height are capitalised in market prices but remain statistically insignificant in government valuations, reflecting a systematic undervaluation of high-intensity development in official pricing schedules. Institutional fragmentation and valuation inertia thus created a “capture gap,” where fiscal returns failed to match private value increments. The findings underscore that effective densification requires dynamic alignment of regulatory latitude, real-time valuation, and integrated governance. Hyderabad’s case illustrates broader lessons for Global South cities: the analysis demonstrates that the proposed framework is transferable beyond the empirical setting, and that blanket deregulation without fiscal and institutional reform entrenches inequality and weakens the public dividend from urban growth. Full article

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24 pages, 4622 KB

Open AccessArticle

Fine-Scale Spatiotemporal Variability of Plant Species Composition in Old-Field Succession—The Cycling Heterogeneity Hypothesis Revisited

by Sándor Bartha, Judit Házi, Dragica Purger, Zita Zimmermann, Gábor Szabó, Zsófia Eszter Guller, András István Csathó and Sándor Csete

Land 2025, 14(12), 2381; https://doi.org/10.3390/land14122381 - 5 Dec 2025

Abstract

Spatial heterogeneity of species distributions modulates local interactions and dynamics, playing a key role in the development of diversity and ecosystem functioning during secondary succession. Here, we tested the cycling heterogeneity hypothesis, which predicts fluctuating spatial beta diversity, i.e., alternating periods of high [...] Read more.

Spatial heterogeneity of species distributions modulates local interactions and dynamics, playing a key role in the development of diversity and ecosystem functioning during secondary succession. Here, we tested the cycling heterogeneity hypothesis, which predicts fluctuating spatial beta diversity, i.e., alternating periods of high and low heterogeneity during succession, driven by the changes in the abundance of dominant species. We analyzed long-term monitoring data collected annually along 52 m long permanent transects over 15 years in abandoned fields. Recovery of grassland vegetation was fast due to the humus-rich chernozem soil, the rich species pool, and the fast colonization of native grassland species from adjacent natural meadow steppe. Heterogeneity was quantified by spatial beta diversity as the mean pairwise dissimilarity among sampling units. Incidence-based (Jaccard) and abundance-based (Bray–Curtis) indices were used. We found large temporal fluctuations in spatial heterogeneity, with amplitudes reaching 80–100% of the total beta diversity range across the successional gradient. Two major beta diversity peaks were identified: maximum heterogeneity occurred during transitions between successional phases, whereas periods of minimum heterogeneity coincided with the sequential dominance of a few particular species. Bromus sterilis and Festuca valesiaca were the most important species driving heterogeneity. Similar patterns were recorded at two monitoring sites. Changing the sampling unit size computationally, varying the dissimilarity indices, or excluding dominant species had little influence on the results. Using null models, we removed the effects of species richness and abundance and found an increasing degree of spatial dependence as succession progressed. However, the corresponding beta deviations also showed non-linear, fluctuating patterns. Our results support the cycling heterogeneity hypothesis in secondary grassland succession. Increasing understanding of heterogeneity patterns provides new opportunities to optimize the temporal and spatial design of grassland restoration measures. Full article

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23 pages, 6715 KB

Open AccessArticle

Future Land Use and Cover Modeling in South Korea: Linking SSP-RCP with FLUS Model

by Seongil Han, Youngeun Kang, Hyeryeon Jo, Miyeon Ahn, Taelyn Kim and Seungwoo Son

Land 2025, 14(12), 2380; https://doi.org/10.3390/land14122380 - 5 Dec 2025

Abstract

Accurate prediction of land use and land cover (LULC) change is essential for sustainable development and climate change adaptation planning. This study projects LULC changes across 17 administrative regions of South Korea from 2020 to 2050 using the Future Land Use Simulation (FLUS) [...] Read more.

Accurate prediction of land use and land cover (LULC) change is essential for sustainable development and climate change adaptation planning. This study projects LULC changes across 17 administrative regions of South Korea from 2020 to 2050 using the Future Land Use Simulation (FLUS) model under four integrated SSP-RCP scenarios: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The model was calibrated with land cover data for 2000–2010 and validated against observations for 2010–2020 using socioeconomic variables together with CMIP6 climate projections. In practical terms, FLUS produces scenario-based maps of future land patterns that inform land regulation, infrastructure planning, and climate adaptation. Across all scenarios, urban areas expanded by 488,000–585,000 ha, mainly through the conversion of agricultural land, which accounted for 10–24% of transitions in high-growth regions. Agricultural land decreased by 124,000–174,000 ha, and forests declined by 473,000–572,000 ha. Transformation intensity peaked around 2030 and then slowed in later decades. Urban expansion was greatest under SSP5-8.5, followed by SSP3-7.0, SSP1-2.6, and SSP2-4.5. Gyeonggi Province exhibited the most pronounced spatial change, whereas Seoul showed limited additional growth consistent with its already saturated urban structure. Validation results indicated an overall accuracy range of 57–83% with metropolitan areas generally outperforming provincial regions. These findings reveal spatial and temporal hotspots of land cover change and provide region-specific information that can guide urban development, land and ecosystem management, climate adaptation policy, and progress toward carbon neutrality. Full article

(This article belongs to the Section Land Systems and Global Change)

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21 pages, 8417 KB

Open AccessArticle

Temporal and Spatial Distribution of Sanxingdui (3.7–3.1 ka BP) and Shi’erqiao (3.1–2.6 ka BP) Sites on the Chengdu Plain, Southwest China

by Hui Chao, Xiaolin Chang and Changhao Xu

Land 2025, 14(12), 2379; https://doi.org/10.3390/land14122379 - 5 Dec 2025

Abstract

Understanding the spatial distribution of ancient settlements is essential for reconstructing human–environment dynamics. The Chengdu Plain, a core region of the ancient Shu civilization, provides a key setting for examining early cultural development in Southwest China. This study applies GIS-based spatial analysis to [...] Read more.

Understanding the spatial distribution of ancient settlements is essential for reconstructing human–environment dynamics. The Chengdu Plain, a core region of the ancient Shu civilization, provides a key setting for examining early cultural development in Southwest China. This study applies GIS-based spatial analysis to 116 prehistoric sites, 27 Sanxingdui (3.7–3.1 ka BP) and 89 Shi’erqiao (3.1–2.6 ka BP), to evaluate their relationships with elevation, relief, slope, aspect, and distance from rivers. Sanxingdui settlements show a tightly constrained pattern, clustering at 450–500 m a.s.l. elevation, on gentle slopes (0–5°), within moderate relief (30–150 m), and almost entirely inside the 0–0.01 river buffer, reflecting strong dependence on stable alluvial landscapes. In contrast, Shi’erqiao sites occupy a broader environmental spectrum, spanning 400–650 m a.s.l. in elevation, concentrating in 30–60 m relief zones, and extending beyond the 0.02 hydrological buffer, indicating enhanced adaptability supported by improved water management and sociopolitical reorganization. The transition from Sanxingdui to Shi’erqiao thus represents a shift from selective environmental reliance to more flexible landscape engagement under mid–late Holocene climatic variability. These results underscore the dynamic nature of prehistoric human–landscape interaction on the Chengdu Plain and provide new insights into cultural resilience in the upper Yangtze River basin. Full article

(This article belongs to the Special Issue Archaeological Landscape and Settlement II)

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27 pages, 9791 KB

Open AccessArticle

A GMOP-PLUS-InVEST-GWR Coupled Model for Simulating “Production–Living–Ecological” Functions and Carbon Stock Dynamics in the Chengdu Metropolitan Area

by Meijuan Zhang and Kun Zhang

Land 2025, 14(12), 2378; https://doi.org/10.3390/land14122378 - 5 Dec 2025

Abstract

Terrestrial carbon stocks have a substantial effect on the global carbon balance and promoting regional sustainable development. In the midst of growing urbanisation, the Chengdu metropolitan area—a key development pole in western China—has seen a radical reworking of its Production–Living–Ecology (PLE) functional framework. [...] Read more.

Terrestrial carbon stocks have a substantial effect on the global carbon balance and promoting regional sustainable development. In the midst of growing urbanisation, the Chengdu metropolitan area—a key development pole in western China—has seen a radical reworking of its Production–Living–Ecology (PLE) functional framework. This transition has had a significant impact on the spatiotemporal dynamics of carbon stocks, but the fundamental mechanisms have yet to be comprehensively understood. To address this, this study constructed a GMOP-PLUS-InVEST-GWR coupled model to simulate and analyze the spatiotemporal evolution relationship between PLE functions and carbon stocks under multiple scenarios from 2000 to 2035. Results indicate that the evolution of the PLE functions reveals a trend of enhanced living functions, diminished production functions, and a slight increase in ecological functions. This has resulted in an overall decrease in carbon storage of 1199.63 × 10⁴ t. Simulations indicate that the Ecological Protection Scenario (EPS) represents the optimal pathway for achieving stable carbon sinks and sustainable system development. It maximizes ecological quality improvement (total increase of +454.74 km² across Zone 5) while minimizing carbon loss (−418.38 × 10⁴ t). Conversely, the Economic Development Scenario (EDS) would result in the greatest carbon loss (−613.18 × 10⁴ t). The impact of PLE functions on carbon stocks exhibits spatial heterogeneity: residential functions show negative effects (coefficients: −1.16 to −2.30), ecological functions yield positive effects (coefficients: 0.87 to 1.65), while the influence of production functions gradually shifts toward enhancing carbon sinks, with positively correlated areas increasing to 81.15%. This study provides scientific basis and spatial decision support for coordinating land development and conservation in rapidly urbanizing regions and enhancing regional carbon sink functions. Full article

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23 pages, 2988 KB

Open AccessArticle

Regional Development in Forestry from the Point of View of the Bioeconomy at the EU Member-State Level

by Kateřina Holušová, Zdeněk Šilhan and Otakar Holuša

Land 2025, 14(12), 2377; https://doi.org/10.3390/land14122377 - 4 Dec 2025

Abstract

This study investigates the integration of forestry into strategic planning across territorial levels in the context of the bioeconomy, using the Czech Republic as a case study of an EU member state. This is examined through a qualitative content analysis of regional and [...] Read more.

This study investigates the integration of forestry into strategic planning across territorial levels in the context of the bioeconomy, using the Czech Republic as a case study of an EU member state. This is examined through a qualitative content analysis of regional and territorial local plans, to identify which topics are associated with forestry (n = 67). Using the example of a private forest owner, the specific implementation is then shown. To gather feedback on the assessed strategic documents, we compared economic results for state, municipal, and private forest owners. The research assumption is that the lower the territorial local level, the greater the importance local governments attach to forestry. The main featured topics are the water regime, sustainable forestry, biodiversity support, climate change, maintenance infrastructure, social functions, and economic competitiveness. The results show that the assumption that the lower the territorial planning level, the more forestry is featured in strategies was not confirmed. The relationship is rather the opposite. The presented economic results clearly demonstrate that financial contributions to forest management are a logical consequence of policies. These results correlated with those of the content analysis. The multi-level approach and use of economic data provide valuable empirical depth, and the main finding challenges common assumptions about policy emphasis at lower governance levels. Full article

(This article belongs to the Section Land Socio-Economic and Political Issues)

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26 pages, 4376 KB

Open AccessArticle

Spatiotemporal Mapping of Urban Flood Susceptibility: A Multi-Criteria GIS-Based Assessment in Nangarhar, Afghanistan

by Imtiaz Ahmad, Wang Ping, Sajid Ullah, Khadeijah Yahya Faqeih, Somayah Moshrif Alamri, Eman Rafi Alamery, Asma Abdulaziz Abdullah Abalkhail and Haji Muhammad Bilal Jan

Land 2025, 14(12), 2376; https://doi.org/10.3390/land14122376 - 4 Dec 2025

Abstract

Urban Flooding is one of the most prevalent natural hazards worldwide, leading to substantial human and economic losses. Therefore, the assessment and mapping of flood hazard levels are essential for reducing the impact of future flood disasters. This study develops and integrates a [...] Read more.

Urban Flooding is one of the most prevalent natural hazards worldwide, leading to substantial human and economic losses. Therefore, the assessment and mapping of flood hazard levels are essential for reducing the impact of future flood disasters. This study develops and integrates a methodology to evaluate urban flood susceptibility in Nangarhar Province, Afghanistan, a semi-arid region with limited prior research. Landsat imagery from 2004 to 2024 was used to analyze land use land cover change (LULCC), indicating that built-up areas increased from 124 to 180 km² in 2004 to 2024, respectively, while agricultural land decreased from 1978 km² to 1883 km² during the same period. Climate data exhibit increases in temperatures and intensifying rainfall, exacerbating flood hazards. Geospatial analysis of elevation, slope, drainage density, and proximity to water bodies highlights the high susceptibility of low-lying areas. The Analytical Hierarchy Process (AHP) was employed to integrate diverse flood risk factors and produce accurate flood hazard maps. The findings show that very-high flood susceptibility zones expanded from 1537 to 1699 km² in 2004 to 2024, whereas low-susceptibility zones declined from 131 km² to 110 km². Socioeconomic indicators such as population density, built-up density, and education accessibility were also incorporated into the assessment. This study underscores the need for adaptive land use planning, resilient drainage systems, and community-based flood risk reduction strategies. The findings provide actionable insights for sustainable flood management and demonstrate the value of combining GIS, remote sensing, and multi-criteria analysis in data-scarce, conflict-affected regions. Full article

(This article belongs to the Special Issue Advances in Urban Flood Modeling: Exploring the Impacts of Land Use, Climate Change, and Green Infrastructure on Flood Risks and Mitigation Strategies)

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25 pages, 1229 KB

Open AccessArticle

Determinants of Property Reuse for Age-Friendly Social Housing Development in Shrinking and Ageing Cities: Evidence from Latvia

by Rashmi Jaymin Sanchaniya, Jurgita Cerneckiene, Ineta Geipele, Antra Kundzina, Leo Jansons, Edgars Pudzis and Peteris Drukis

Land 2025, 14(12), 2375; https://doi.org/10.3390/land14122375 - 4 Dec 2025

Abstract

Demographic decline and population ageing present unprecedented challenges to housing systems in post-socialist Europe. With one of the European Union (EU)’s fastest shrinking populations, an underdeveloped social housing sector, and an ageing housing stock dominated by Soviet-era multi-family blocks, Latvia exemplifies these difficulties. [...] Read more.

Demographic decline and population ageing present unprecedented challenges to housing systems in post-socialist Europe. With one of the European Union (EU)’s fastest shrinking populations, an underdeveloped social housing sector, and an ageing housing stock dominated by Soviet-era multi-family blocks, Latvia exemplifies these difficulties. Adaptive property reuse—repurposing underutilised buildings into age-friendly social housing—offers a potential solution, but its feasibility depends on complex economic, regulatory, social, and environmental determinants. This study investigated these determinants using a mixed-methods approach. Data were drawn from 312 survey responses, 15 policymaker interviews, 10 developer interviews, and focus group of 25 senior residents across Latvia. Exploratory Factor Analysis (EFA) was used to extract six determinant clusters: site selection, feasibility analysis, design and planning, implementation strategies, monitoring and evaluation, and scaling strategies. The findings demonstrate: (1) economic feasibility and regulatory clarity dominate stakeholder concerns, with financing gaps receiving the lowest ratings (M = 2.91); (2) implementation strategies emerged as the highest-priority determinant, emphasising governance capacity and structured execution; (3) significant trust deficits exist between developers and municipal authorities, undermining collaboration; (4) seniors prioritise design inclusivity and social integration, while developers emphasise cost efficiency and regulatory certainty; and (5) environmental sustainability consistently ranked lower (M ≈ 3.34) across all stakeholder groups due to pressing affordability concerns. Although municipal officers were intentionally oversampled (58%) due to their central role in Latvia’s housing governance, robustness checks confirmed the six-factor structure remained stable across stakeholder groups. This study contributes theoretically by contextualising adaptive reuse within shrinking cities and ageing societies and practically by providing a determinant-based framework for housing policy. Full article

(This article belongs to the Special Issue Sustainable Development and Urban Land Use Efficiency: Strategies for Effective Land Management)

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26 pages, 5156 KB

Open AccessArticle

An Integrated Conceptual Approach for Biodiversity Risk Assessment: How Do Biodiversity Risk Patterns Respond to the Simultaneous Impacts of Climate Change and Urbanization?

by Hye In Chung, Yuyoung Choi, Gregory S. Biging, Woo-Kyun Lee, Dong Kun Lee, Jinhyung Chon, Hyun Chan Sung, Kyungil Lee and Seong Woo Jeon

Land 2025, 14(12), 2374; https://doi.org/10.3390/land14122374 - 4 Dec 2025

Abstract

As biodiversity continues to decline under the combined pressures of climate change and urbanization, there is an urgent need for comprehensive risk assessment. Given the close interconnection between biodiversity and ecosystem functions, two major risk factors have been identified: (1) habitat loss (destruction) [...] Read more.

As biodiversity continues to decline under the combined pressures of climate change and urbanization, there is an urgent need for comprehensive risk assessment. Given the close interconnection between biodiversity and ecosystem functions, two major risk factors have been identified: (1) habitat loss (destruction) and (2) habitat gain expansion (disturbance). To address these challenges, this study proposes an integrated approach for biodiversity risk assessment that spatially and quantitatively evaluates risks from a holistic perspective. Specifically, an integrative modeling framework (BIOMOD2–LCM–MigClim) was developed to predict biodiversity patterns under the simultaneous impacts of climate change and urbanization. In parallel, novel indices, the Persistence Index (PI) and Disturbance Index (DI), were designed to assess biodiversity risks from multidimensional temporal and spatial perspectives. Based on the biodiversity risk types defined as Risk 1 (habitat loss; climate change risk species) and Risk 2 (habitat gain–expansion; invasive species), the study derived spatial distribution patterns and conducted a time series analysis of risk characteristics. Results highlight the dynamic ecological interactions in competitive areas, where Risk 2 advances by intruding into Risk 1 zones, thereby accelerating Risk 1 retraction. These findings confirm the need for integrated methodologies to capture shifting biodiversity responses and provide robust decision support for fundamental biodiversity policies. Full article

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25 pages, 29600 KB

Open AccessArticle

Spatiotemporal Dynamics and Drivers of Ecological Carrying Capacity in the Dongting Lake Region Using Remote Sensing and Spatial Modeling

by Ying Ning, Yan Jiang, Shuchen Yu, Shuguang Liu, Yongcai Lou and Juan Zou

Land 2025, 14(12), 2373; https://doi.org/10.3390/land14122373 - 4 Dec 2025

Abstract

Ecological Carrying Capacity (ECC) represents an ecosystem’s ability to sustain human activities without compromising its ecological integrity, yet fine-scale quantification of its spatiotemporal dynamics remains limited. Focusing on the ecologically vital Dongting Lake Region (DTLR) in China, this study established a finer resolution [...] Read more.

Ecological Carrying Capacity (ECC) represents an ecosystem’s ability to sustain human activities without compromising its ecological integrity, yet fine-scale quantification of its spatiotemporal dynamics remains limited. Focusing on the ecologically vital Dongting Lake Region (DTLR) in China, this study established a finer resolution ECC assessment framework by integrating multi-source remote sensing data within the Driving Forces–Pressure–State–Impact–Response–Management (DPSIRM) model. ECC and its driving mechanisms were examined across the DTLR and its surrounding buffer zone from 2000 to 2020. Results revealed a pronounced U-shaped trajectory of ECC in the DTLR, with an initial decline followed by a sustained recovery after 2010, while the buffer zone consistently maintained a 15–20% higher ECC throughout. Subsystem analysis indicated steady improvements in Management capacity, whereas Pressure, State, and Impact subsystems peaked mid-period before declining. Projections suggest continued ECC enhancement, reflecting rising regional resilience. Spatially, ECC patterns jointly emerged from the interaction of anthropogenic stressors and ecological restoration. Geographically weighted regression (GWR) identified proximity to green spaces as the strongest positive driver, while impervious surface (−27%) and infrastructure density (−19%) exerted significant negative effects. These findings offer a scalable, remote sensing-based framework for ecosystem-oriented spatial planning, highlighting the strategic role of green infrastructure in sustaining ecological resilience. Full article

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25 pages, 5587 KB

Open AccessArticle

Urban Heat on Hold: A Remote Sensing-Based Assessment of COVID-19 Lockdown Effects on Land Surface Temperature and SUHI in Nowshera, Pakistan

by Waqar Akhtar, Jinming Sha, Xiaomei Li, Muhammad Jamal Nasir, Waqas Ahmed Mahar, Syed Hamid Akbar, Muhammad Ibrahim and Sami Ur Rahman

Land 2025, 14(12), 2372; https://doi.org/10.3390/land14122372 - 4 Dec 2025

Abstract

The COVID-19 pandemic presented an unprecedented opportunity to assess the environmental effects of reduced anthropogenic activity on urban climates. This study investigates the impact of COVID-19-induced lockdowns on land surface temperature (LST) and the intensity of the surface urban heat island (SUHI) in [...] Read more.

The COVID-19 pandemic presented an unprecedented opportunity to assess the environmental effects of reduced anthropogenic activity on urban climates. This study investigates the impact of COVID-19-induced lockdowns on land surface temperature (LST) and the intensity of the surface urban heat island (SUHI) in Nowshera District, Khyber Pakhtunkhwa Province, Pakistan, which is experiencing rapid urbanization. Using Landsat 8/9 imagery, we assessed thermal changes across three periods: pre-lockdown (April 2019), during lockdown (April 2020), and post-lockdown (April 2021). Remote sensing indices, including NDVI and NDBI, were applied to evaluate the relationship between land cover and LST. Our results show a significant reduction in average LST during lockdown, from 31.38 °C in 2019 to 25.34 °C in 2020, a 6 °C decrease. Urban–rural LST differences narrowed from 9 °C to 6 °C. A one-way ANOVA confirmed significant differences in LST across the three periods (F (2, 3) = 3691.46, p < 0.001), with Tukey HSD tests indicating that the lockdown period differed significantly from both the pre- and post-lockdown periods (p < 0.001). SUHI intensity fell from 35.10 °C to 28.89 °C during lockdown, then rebounded to 35.37 °C post-lockdown. The indices analysis shows that built-up and rangeland areas consistently recorded the highest LST (e.g., 35.36 °C and 37.09 °C in 2021, respectively), while vegetation and water bodies maintained lower temperatures (34.68 °C and 32.69 °C in 2021). NDVI confirmed the cooling effect of green areas, while high NDBI values correlated with increased LST in urban areas. These findings underscore the impact of human activity on urban heat dynamics and highlight the role of sustainable urban planning and green infrastructure in enhancing climate resilience. By exploring the relationships among land cover, anthropogenic activity, and urban climate resilience, this research offers policymakers and urban planners’ valuable insights for developing adaptive, low-emission cities amid rapid urbanization and climate change. Full article

(This article belongs to the Special Issue Young Researchers in Land–Climate Interactions)

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27 pages, 14100 KB

Open AccessArticle

Official Projection vs. Public Perception: Measuring the Perceptual Discrepancy of Creative Industry Parks in the Industrial Heritage Category Using Large Language Models

by Xiaoke Yang, Bin Hu and Jingwei Zhao

Land 2025, 14(12), 2371; https://doi.org/10.3390/land14122371 - 4 Dec 2025

Abstract

Industrial tourism serves as a medium for disseminating industrial culture and strengthening public awareness. Quantifying the discrepancies between official projections and public perceptions is essential for shaping the destination image and enhancing appeal and competitiveness. This study examines five industrial heritage creative industry [...] Read more.

Industrial tourism serves as a medium for disseminating industrial culture and strengthening public awareness. Quantifying the discrepancies between official projections and public perceptions is essential for shaping the destination image and enhancing appeal and competitiveness. This study examines five industrial heritage creative industry parks using large language models (LLMs) and multimodal data to address this issue. The results indicate the following: (1) Multimodal data fusion improves feature representation. (2) A clear discrepancy exists between official projections and public perceptions. The official perspective emphasizes the Cultural value of heritage, in contrast to the public’s greater concern with the Service experience perception. Despite this divergence, there is alignment in the recognition of the Creative industry form dimension. (3) Public sentiment regarding the parks is predominantly positive. However, an analysis of negative sentiments reveals that insufficient supporting facilities and poor consumption experience are the primary sources of dissatisfaction. Through large language models and multimodal data, this study proposes a framework for quantifying the gaps between official projections and public perceptions. It also provides practical insights and empirical support for the management and planning of industrial heritage creative industry parks. Full article

(This article belongs to the Special Issue Big Data-Driven Urban Spatial Perception)

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24 pages, 10210 KB

Open AccessArticle

Spatiotemporal Dynamics of Local Climate Zones and Their Impacts on Land Surface Temperature in the Guangdong–Hong Kong–Macao Greater Bay Area

by Yang Lu and Dawei Wen

Land 2025, 14(12), 2370; https://doi.org/10.3390/land14122370 - 4 Dec 2025

Abstract

Understanding how long-term local climate zone (LCZ) dynamics interact with rapid urbanization and land surface temperature (LST) changes is essential for sustainable planning in megaregion-scale urban clusters. In this paper, we propose a multi-feature local sample transfer method to obtain LCZ maps from [...] Read more.

Understanding how long-term local climate zone (LCZ) dynamics interact with rapid urbanization and land surface temperature (LST) changes is essential for sustainable planning in megaregion-scale urban clusters. In this paper, we propose a multi-feature local sample transfer method to obtain LCZ maps from 2000 to 2020 in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) and then analyze spatiotemporal changes in LCZs and their impacts on surface thermal environments. Results show the following: (1) The proposed multi-feature local sample transfer approach significantly improves the efficiency of long-term LCZ mapping by greatly reducing the effort required for sample acquisition. (2) The built types (LCZ1–10) increased by 1.34% overall, with large low-rise (LCZ8) showing the greatest expansion (4.72%). The compact low-rise (LCZ3) was the only built type to decline, decreasing by 2.02%. (3) Urbanization has produced a contiguous warming core that expands outward from the central metropolitan zones, thereby promoting the UHI coalescence. (4) Dense trees (LCZA) and large low-rise (LCZ8) exerted the strongest influence on LST. Large low-rise (LCZ8) consistently exhibited the highest warming contribution in Foshan, Zhongshan, and Dongguan. In coastal cities including Shenzhen, Hong Kong, and Macao, the largest LST increases occurred when water (LCZG) areas were converted to bare rock or paved (LCZE) or cs (LCZ1–10). Overall, the results highlight the strong coupling between urbanization and surface heating, providing critical insights for urban climate adaptation and integrated land-use planning in rapidly urbanizing megaregions. Full article

(This article belongs to the Special Issue Assessment of Spatial and Temporal Landscape Patterns Under Land Use Change)

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32 pages, 3830 KB

Open AccessArticle

Towards a Standardized Framework: Analyzing and Systematizing Urban Sustainability Indicators to Guide Effective City Development

by Felicia Di Liddo, Marco Locurcio, Pierluigi Morano and Francesca Fariello

Land 2025, 14(12), 2369; https://doi.org/10.3390/land14122369 - 4 Dec 2025

Abstract

Urban sustainability has become a central theme in contemporary city planning and policy-making, reflecting the growing need to address complex environmental, social, and economic challenges. However, the range of metrics used to measure sustainability often results in fragmentation and inconsistency, limiting their practical [...] Read more.

Urban sustainability has become a central theme in contemporary city planning and policy-making, reflecting the growing need to address complex environmental, social, and economic challenges. However, the range of metrics used to measure sustainability often results in fragmentation and inconsistency, limiting their practical application. The present study aims to analyze and systematize the urban sustainability indicators most commonly found in the literature and employed at the international level. The research seeks to develop a comprehensive framework of economic, environmental, and social indicators, providing a more coherent and standardized tool to support informed and effective urban regeneration strategies. In particular, in this work a critical examination of the indicators is carried out, highlighting the inherent limitations, potential distortions, and the standardizability level. To ensure more reliable and transparent measurement tools, the outcome of the analysis is the definition of a structured abacus of key urban sustainability indicators, classified across three main domains (economic, environmental, and social), able to orient the choices processes to promote sustainable cities development. Overall, a total of 85 indicators have been identified (27 economic, 36 environmental, 22 social), of which 47 show a high degree of standardization, 37 a moderate level, and only 1 a low level. The majority of the selected indicators are fully operational at the city scale, strengthening their applicability in supporting local governance and urban transformation processes. Full article

(This article belongs to the Special Issue Urban Resilience and Heritage Management (Second Edition))

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30 pages, 5186 KB

Open AccessArticle

Optimizing Urban Land-Use Through Deep Reinforcement Learning: A Case Study in Hangzhou for Reducing Carbon Emissions

by Jie Shen, Fanghao Zheng, Tianyi Chen, Wu Deng, Anthony Bellotti, Fiseha Berhanu Tesema and Elena Lucchi

Land 2025, 14(12), 2368; https://doi.org/10.3390/land14122368 - 3 Dec 2025

Abstract

Urban land-use optimization plays a vital role in mitigating the escalating carbon emissions of rapidly growing cities. This study employs advanced computational intelligence to address urban carbon reduction through optimized spatial configurations. A Deep Reinforcement Learning (DRL) framework is proposed that integrates Points [...] Read more.

Urban land-use optimization plays a vital role in mitigating the escalating carbon emissions of rapidly growing cities. This study employs advanced computational intelligence to address urban carbon reduction through optimized spatial configurations. A Deep Reinforcement Learning (DRL) framework is proposed that integrates Points of Interest (POI), Areas of Interest (AOI), and Transportation System Data (TSD) to generate fine-grained carbon emission maps guiding land-use adjustments. In the case study of Hangzhou, China, results show that a carefully designed reward function enables the DRL agent to selectively optimize land-use structures, prioritizing the centralization of residential, dining, and commercial areas to form high-density, mixed-use urban clusters. This spatial reorganization leads to notable reductions in carbon emissions and improvements in resource-use efficiency. The proposed DRL-based framework provides a scientific basis for policy development toward sustainable land-use and urban density optimization. By merging advanced AI techniques with urban planning, this research contributes to the creation of low-carbon, resilient, and environmentally sustainable cities capable of addressing global climate challenges. The optimized DRL agent achieved carbon emission reductions of up to 15% compared to baseline configurations in the Hangzhou case study. Spatial concentration analysis revealed a 23% increase in residential area clustering and 31% increase in commercial zone centralization over 400 training episodes. The PPO-based model demonstrated superior performance compared to genetic algorithm and linear regression baselines, with lower policy loss (converging to <0.01) and critic loss (converging to <0.005) after early stopping at 400 episodes. However, this study is limited by its deterministic environment model, geographic specificity to Hangzhou, and exclusive focus on carbon reduction without incorporating socioeconomic constraints. Full article

(This article belongs to the Special Issue Energy and Landscape: Consensus, Uncertainties and Challenges)

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