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Public–Private Partnerships in Urban Regeneration: Comparative Insights and Lessons from Brazil, Italy, and the UK
Analysis of Soil δ¹³C and δ¹⁵N Along Precipitation Gradient: Critical Insights into Tree–Grass Interactions and Soil C Sequestration in Savannas

Journal Description

Land

Land is an international, cross-disciplinary, peer-reviewed, open access journal on land system science, landscape, soil and water, urban study, land–climate interactions, water–energy–land–food (WELF) nexus, biodiversity research and health nexus, land modelling and data processing, ecosystem services, multifunctionality and sustainability, and is published monthly online by MDPI. The International Association for Landscape Ecology (IALE), International Federation of Landscape Architects (IFLA), European Land-use Institute (ELI), Landscape Institute (LI) and Urban Land Institute (ULI) are affiliated with Land, and their members receive discounts on the article processing charges.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, SSCI (Web of Science), GEOBASE, PubAg, AGRIS, GeoRef, RePEc, and other databases.
Journal Rank: JCR - Q2 (Environmental Studies) / CiteScore - Q1 (Nature and Landscape Conservation)
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.5 days after submission; acceptance to publication is undertaken in 2.5 days (median values for papers published in this journal in the second half of 2025).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Companion journal: Drylands.
Journal Cluster of Environmental Science: Sustainability, Land, Clean Technologies, Environments, Nitrogen, Recycling, Urban Science, Safety, Air, Waste, Aerobiology and Toxics.

Impact Factor: 3.2 (2024); 5-Year Impact Factor: 3.4 (2024)

Imprint Information Journal Flyer Open Access ISSN: 2073-445X

Latest Articles

31 pages, 21527 KB

Open AccessArticle

Decoupling Effects and Nonlinear Mechanisms of Land-Use Carbon Emissions in Rural Revitalization: A Case Study of Western China

by Feng Wang, Ziyi Wang, Huizhi Gao and Sidong Zhao

Land 2026, 15(6), 916; https://doi.org/10.3390/land15060916 - 26 May 2026

The governance of land use carbon emissions is pivotal to achieving the goals of carbon peak and carbon neutrality. Rural revitalization significantly shapes the spatiotemporal patterns and evolutionary dynamics of land use carbon emissions, yet this relationship has received inadequate attention in existing [...] Read more.

The governance of land use carbon emissions is pivotal to achieving the goals of carbon peak and carbon neutrality. Rural revitalization significantly shapes the spatiotemporal patterns and evolutionary dynamics of land use carbon emissions, yet this relationship has received inadequate attention in existing literature. This study employs a combination of decoupling models, the Boston Matrix, spatial analysis, and interpretable machine learning models to conduct an empirical analysis of 124 regions in western China. The findings reveal diversified spatiotemporal evolution trends in rural revitalization land use carbon emissions. The decoupling relationship between rural revitalization and carbon emissions demonstrates a polarized nature, with over half of the assessed regions experiencing negative decoupling effects. The role of impact factors in decoupling relationships is characterized by a mixed nature, hierarchical intensity, nonlinear pathways, spatial heterogeneity and autocorrelation. The pathways of factor effects display nonlinear forms such as wave-like, inverted U-shaped, and U-shaped patterns, with the nature and intensity of effects dynamically shifting between “threshold mutations” and “inflection reversals” as factors evolve. The spatiotemporal evolution patterns, decoupling relationships, and SHAP values all exhibit significant spatial autocorrelation and form “spatial clusters” of various shapes. The decoupling of rural revitalization and carbon emissions in western China constitutes a complex systemic endeavor, necessitating comprehensive analysis from multiple dimensions—encompassing spatiotemporal evolution patterns, decoupling relationship, nonlinear mechanisms, and spatial effects—followed by the formulation of differentiated and precision-targeted governance strategies. Full article

(This article belongs to the Special Issue Carbon-Focused Land Use Strategies: Pathways to Climate Resilience)

21 pages, 8537 KB

Open AccessReview

Geographically Weighted Regression: A Systematic Review of Methods, Development, and Applications

by Ronglei Yang, Tiyan Shen, Wenqing Yin and Hanchen Yu

Land 2026, 15(6), 915; https://doi.org/10.3390/land15060915 - 26 May 2026

Over the past three decades, geographically weighted regression (GWR) and multiscale geographically weighted regression (MGWR) have become essential tools for spatial analysis in urban, environmental, and land-use research. This scoping review systematically maps and synthesizes the global literature on GWR and MGWR published [...] Read more.

Over the past three decades, geographically weighted regression (GWR) and multiscale geographically weighted regression (MGWR) have become essential tools for spatial analysis in urban, environmental, and land-use research. This scoping review systematically maps and synthesizes the global literature on GWR and MGWR published between 1996 and 2026, aiming to identify the research hotspots, evolutionary paths, and cutting-edge trends. Bibliometrics and CiteSpace visualization tools are used to conduct a multi-dimensional visual analysis of thousands of selected articles, including countries, institutions, core authors, highly cited keywords, and key documents. The results show that the current research focuses on spatial heterogeneity, multiscale analysis, GWR model optimization, non-stationarity characterization, and simulation of urban land-use change. Potential future directions include the construction of spatiotemporal integrated models, the integration of high-performance computing, and the expansion of interdisciplinary applications. The results of this study can help scholars fully understand the current research status and future directions, and provide a scientific spatial analysis framework for practitioners in urban planning, land resource management, and environmental assessment. Furthermore, the conclusions can provide theoretical support and a decision-making basis for the government to formulate intelligent and refined urban development policies. Full article

(This article belongs to the Special Issue Effects of Rural–Urban Migration on Urban Infrastructure in Fast-Growing Cities)

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31 pages, 11219 KB

Open AccessArticle

A Basin-Scale Framework for Identifying Hydro-Cultural Heritage Corridor Patterns and Guiding Graded Protection: Evidence from the Xiangjiang River Basin, China

by Yifan Wu, Sheng Jiao, Wenting Liu, Yan Yu and Kaiyin Xiao

Land 2026, 15(6), 914; https://doi.org/10.3390/land15060914 - 26 May 2026

Hydro-cultural heritage is shaped by strong hydrological dependence and historical accessibility. To address insufficient identification of river-basin heritage linkages and their weak translation into graded protection, this study develops an analytical framework integrating heritage-site evaluation, cultural source identification, resistance-surface construction, potential corridor extraction, [...] Read more.

Hydro-cultural heritage is shaped by strong hydrological dependence and historical accessibility. To address insufficient identification of river-basin heritage linkages and their weak translation into graded protection, this study develops an analytical framework integrating heritage-site evaluation, cultural source identification, resistance-surface construction, potential corridor extraction, network grading, and protection guidance, and applies it to the Xiangjiang River Basin, China. Heritage sites were evaluated by protection level, historical continuity, spatial proximity, and hydro-cultural relevance. Cultural source areas were identified using weighted kernel density analysis, potential corridors were extracted using the minimum cumulative resistance model, and the graded corridor network was examined using network-structure indices. The results show river-oriented clustering, localized nucleation, and belt-like extension. Eight primary and fourteen supplementary cultural source areas were identified. Potential corridors are concentrated along the Xiangjiang main stem and major tributaries. In the resistance-surface construction, distance to the water system received the highest AHP-derived resistance weight, while GeoDetector showed that it had the highest, although modest, single-factor explanatory power among the tested variables for corridor spatial differentiation. The corridor network exhibits a primary–secondary–tertiary graded structure. This study reveals the spatial continuity and hierarchy of hydro-cultural heritage corridors and provides a methodological reference for river-basin conservation. Full article

(This article belongs to the Section Land Planning and Landscape Architecture)

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26 pages, 1253 KB

Open AccessArticle

The Impact of the Low-Carbon City Pilot Policy on Energy Intensity: Evidence from a Staggered Difference-in-Differences Design

by Tianyu Wang and Yanying Wei

Land 2026, 15(6), 913; https://doi.org/10.3390/land15060913 - 25 May 2026

Under China’s dual-carbon agenda, a central question is whether the Low-Carbon City (LCC) pilot policy reduces energy intensity, whether this effect can be credibly interpreted as causal, and under which conditions and through which channels it operates. Using a balanced panel of 282 [...] Read more.

Under China’s dual-carbon agenda, a central question is whether the Low-Carbon City (LCC) pilot policy reduces energy intensity, whether this effect can be credibly interpreted as causal, and under which conditions and through which channels it operates. Using a balanced panel of 282 prefecture-level and higher-level cities from 2006 to 2023, this study develops a problem-oriented framework that integrates effect identification, credibility validation, and heterogeneity and mechanism analysis. The average treatment effect is estimated using staggered difference-in-differences, while dynamic effects are identified with interaction-weighted and imputation-based event-study estimators, and selection concerns are further addressed through propensity score matching difference-in-differences and a battery of stability checks. The results show that the LCC pilot policy reduces urban energy intensity, with the baseline estimate implying a decline of about 15%–16%, and that the policy effect accumulates over time rather than appearing immediately. This finding remains stable across alternative specifications, placebo tests, and matched-sample estimation. The policy effect is stronger in cities with higher initial energy intensity and higher levels of economic development. Mechanistic evidence indicates that adjustments in fixed asset investment and changes in AI-related resource allocation are two observable channels associated with the decline in energy intensity. By focusing on energy intensity as a process-oriented performance indicator, this study provides more direct evidence on the energy-efficiency consequences of low-carbon urban governance and clarifies the conditional and structural foundations of policy effectiveness. Full article

(This article belongs to the Special Issue United Nations Sustainable Development Goals in Land-Use Systems from Resource-Nexus Perspectives)

18 pages, 1754 KB

Open AccessArticle

Integrated Assessment of Soil Environmental Capacity for Heavy Metals in a Selenium-Rich Geological Agricultural Region: A Novel Framework Combining Source Apportionment and Dynamic Modeling

by Daokun Chen, Dongxiang Jiang, Liang Wang, Xinbin Li, Boyuan Chen, Zhanbin Wang and Ke Yang

Land 2026, 15(6), 912; https://doi.org/10.3390/land15060912 - 25 May 2026

Addressing capacity assessment uncertainties in high-geological-background areas, this study develops a source-oriented risk assessment framework integrating spatial interpolation, source apportionment, and dynamic capacity modeling. Analysis of 39 surface soil samples (As, Cr, Ni, Cu, Zn, Cd, Pb, Se, pH) from ankang basin, China, [...] Read more.

Addressing capacity assessment uncertainties in high-geological-background areas, this study develops a source-oriented risk assessment framework integrating spatial interpolation, source apportionment, and dynamic capacity modeling. Analysis of 39 surface soil samples (As, Cr, Ni, Cu, Zn, Cd, Pb, Se, pH) from ankang basin, China, reveals: Two heavy metal sources were quantitatively identified via APCS-MLR. Natural sources (71.94%) dominate, contributing Se, Cd, Cu, Zn, and Ni, with Cd primarily geogenic. Anthropogenic sources (28.06%) from industrial, transportation, and agricultural activities contribute Cr, As, Pb, and Ni. Static capacity assessment identifies Cd as the primary limiting element (average capacity 0.22). Dynamic model predictions indicate that the 20-year dynamic capacity of all elements is only 14–20% of the theoretical static capacity (Q_i), representing 16–47% of the current existing capacity, and will approach dynamic equilibrium after 40 years. Source-oriented capacity indices reveal natural sources pose the highest comprehensive risk (SPI = 0.916), mainly driving Cd capacity stress (SPICd = 0.34). Anthropogenic sources remain safe (SPI > 1.255) but warrant Pb monitoring. This framework supports precise management of selenium-rich lands, shifting strategies from emission control to avoiding high-risk geological units. Full article

(This article belongs to the Special Issue Soil Contamination—Ecological Environment Risk Assessment and Remediation: 2nd Edition)

15 pages, 1250 KB

Open AccessProject Report

Prospective Carbon Sequestration Assessment of National Reserve Forest Restoration Using Biomass Expansion Factor-Based Accounting

by Liqing Zhu, Benyun Song and Jie Kong

Land 2026, 15(6), 911; https://doi.org/10.3390/land15060911 - 25 May 2026

Restoration-oriented forest management is increasingly recognized as an important strategy for enhancing long-term carbon sequestration and rehabilitating degraded peri-urban forest landscapes. This study presents a scenario-based assessment of projected carbon sequestration trajectories under a National Reserve Forest Project implemented in peri-urban Wuhan, central [...] Read more.

Restoration-oriented forest management is increasingly recognized as an important strategy for enhancing long-term carbon sequestration and rehabilitating degraded peri-urban forest landscapes. This study presents a scenario-based assessment of projected carbon sequestration trajectories under a National Reserve Forest Project implemented in peri-urban Wuhan, central China. Thirteen silvicultural models were grouped into three management pathways: intensive plantation cultivation, transformation of existing degraded stands, and tending of young and middle-aged forests. Carbon sequestration was evaluated over a 40-year assessment period (2024–2063) using a Biomass Expansion Factor-based accounting framework incorporating above- and belowground biomass, harvested wood products, and conservative baseline deductions consistent with national and provincial methodologies. The results indicate a sustained long-term increase in projected carbon sequestration despite periodic short-term declines associated with planned thinning and harvesting cycles. Transformation-oriented pathways contributed the largest cumulative project-scale sequestration and generally exhibited relatively strong area-normalized sequestration performance compared with intensive plantation and tending pathways. Intensive plantation systems displayed greater temporal fluctuation associated with shorter rotation cycles and repeated harvesting events. The analysis also highlights the importance of distinguishing between area-normalized sequestration efficiency and cumulative project-scale contribution, as models with moderate per-hectare performance generated substantial total carbon benefits because of their larger implementation area. The findings suggest that restoration-oriented management of existing degraded stands may provide a relatively stable long-term carbon-sequestration pathway in peri-urban forest systems where land availability for large-scale afforestation is constrained. The study also demonstrates the applicability of conservative scenario-based accounting frameworks for restoration-oriented forest carbon assessment and planning under data-limited conditions. Full article

(This article belongs to the Special Issue United Nations Sustainable Development Goals in Land-Use Systems from Resource-Nexus Perspectives)

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24 pages, 7070 KB

Open AccessArticle

Spatiotemporal Dynamics, Spatial Spillover Effects, and Driving Mechanisms of Non-Grain Use of Cultivated Land in an Ecologically Fragile Region

by Yao Cui, Hongrui Sun, Yaolin Liu, Ligang Wang, Yanfang Liu, Rui An, Xinyue Zhang, Yifan Xie, Lin Zhang and Jiwei Xu

Land 2026, 15(6), 910; https://doi.org/10.3390/land15060910 - 25 May 2026

Non-grain use of cultivated land (NGUCL) in ecologically fragile regions has become a major challenge to food security and land sustainability, yet its spatiotemporal dynamics, spatial spillover effects, and associated factors remain insufficiently understood. Taking Ningxia, China, as a typical semi-arid to arid [...] Read more.

Non-grain use of cultivated land (NGUCL) in ecologically fragile regions has become a major challenge to food security and land sustainability, yet its spatiotemporal dynamics, spatial spillover effects, and associated factors remain insufficiently understood. Taking Ningxia, China, as a typical semi-arid to arid transition zone, this study developed a phenology-informed framework that combined multi-temporal Landsat imagery, random forest classification, spatial autocorrelation analysis, centroid and standard deviation ellipse models, and a spatial lag model to identify and analyze NGUCL in 2005, 2010, 2015, and 2020. Within the cultivated land boundary, NGUCL was further decomposed into cash crop-cultivated farmland (CCCF) and farmland abandonment (FA). The results show that the classification framework achieved robust performance, with overall accuracies above 85% across the benchmark years. Food-crop mapping reached an OA of 86.38–90.12% and a Kappa of 0.80–0.85, while FA mapping reached an OA of 85.60–86.74% and a Kappa of 0.70–0.72. NGUCL in Ningxia exhibited strong subregional differentiation under the gradients of northern irrigation, central arid, and southern mountainous conditions. CCCF was more closely associated with irrigated and agriculturally productive areas, whereas FA was concentrated in ecologically constrained counties and showed stronger dispersion and migration complexity. Spatial econometric results further indicate significant spatial spillover effects, suggesting that NGUCL-related processes in one county are associated with those in neighboring counties. The effects of natural, socioeconomic, and agricultural production factors also varied by type and period, indicating that NGUCL in ecologically fragile regions is not a homogeneous land-use transition process. By distinguishing CCCF from FA, this study provides a more nuanced interpretation of NGUCL and offers empirical evidence for understanding cultivated land transition and governance in ecologically fragile areas. Full article

(This article belongs to the Section Land Use, Impact Assessment and Sustainability)

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19 pages, 5173 KB

Open AccessArticle

Spatial Heterogeneity of Soil Organic Matter and Its Driving Mechanisms in the Dayangshu Area of the Songnen Plain

by Yongliang Wang, Surigala Tai, Yongchun Li, Rong She and Wenpeng Shi

Land 2026, 15(6), 909; https://doi.org/10.3390/land15060909 - 25 May 2026

Understanding the spatial heterogeneity of deep soil organic matter is critical for terrestrial carbon cycling, yet its driving mechanisms remain elusive due to a historical research bias toward surface layers. This study develops a 3D spatial prediction and mechanistic framework for Soil organic [...] Read more.

Understanding the spatial heterogeneity of deep soil organic matter is critical for terrestrial carbon cycling, yet its driving mechanisms remain elusive due to a historical research bias toward surface layers. This study develops a 3D spatial prediction and mechanistic framework for Soil organic matter(SOM) across a 0–200 cm profile in the Mollisols of the Songnen Plain, Northeast China. By integrating systematic sampling with Random Forest modeling and a comprehensive suite of multi-source environmental covariates, we identified pronounced vertical stratification in SOM distribution and its governing factors. Our results reveal that surface SOM is primarily driven by climate, vegetation, and anthropogenic activities, whereas deep soil organic matter is dictated by intrinsic physicochemical properties and surface matrix compositions. Furthermore, significant interaction effects between topography and soil attributes further enhance SOM accumulation. This research clarifies the depth-dependent processes of carbon stabilization, providing a robust scientific basis for the targeted conservation and carbon sequestration enhancement of Mollisols. Full article

37 pages, 16579 KB

Open AccessArticle

Urban Green Network Design as an Adaptation Strategy of Mediterranean Cities to Rising Temperatures

by Antonia Marketaki, Areti Tseliou, Evgenia Tousi, Athina Mela and Efthimios Zervas

Land 2026, 15(6), 908; https://doi.org/10.3390/land15060908 - 25 May 2026

Rising temperatures within the urban context, as a result of climate change and the Urban Heat Island effect, have deteriorated thermal comfort conditions in outdoor urban spaces, especially during hot, Mediterranean summer days. This study investigates the potential cooling effects of integrating individual [...] Read more.

Rising temperatures within the urban context, as a result of climate change and the Urban Heat Island effect, have deteriorated thermal comfort conditions in outdoor urban spaces, especially during hot, Mediterranean summer days. This study investigates the potential cooling effects of integrating individual urban green spaces into a connected network, with the aim of improving thermal conditions in public areas. Thermal conditions of an 800 m² urban area in the city of Athens, Greece, were evaluated for a typical summer day using the environmental model ENVI-met. Based on an assessment of the current microclimatic conditions, a potential thermal adaptation strategy was developed, aiming to redesign the study area as a network of green-blue infrastructure. This includes a 1.5 km walking route connecting various spaces, such as squares, parks, and schools. Air temperature (Tair) and the bioclimatic index PET (Physiologically Equivalent Temperature) were used to evaluate the thermal conditions of the study area. In addition, a new function of the ENVI-met model, Dynamic Comfort, has been implemented to calculate the dynamic Physiological Equivalent Temperature (dPET) index for the selected route. The results revealed significant Tair and PET reductions compared to the current layout, indicating that the integration of open spaces into a network of green-blue infrastructure can improve thermal conditions and reduce the hazardous effects of thermal stress on people. Some notable results include the spatial and temporal decrease of the Tair of up to 6 °C, mainly in the proximity of buildings and fountains. Similarly, PET values decreased mainly by 3 to 5 °C. The Dynamic PET showed a slight reduction during the hours of maximum temperature and a higher decrease during the evening, ranging from 1 to 2 °C. Full article

(This article belongs to the Special Issue Emerging Technologies Towards Sustainable Urban Transitions)

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27 pages, 488 KB

Open AccessArticle

Digital Economy and Urban Green Land Use Efficiency: Evidence on Pathways Through Spatial Compactness in China

by Yinghao Zhang, Zhaoxin Liu, Xuechun Sun, Conghui Zhu and Jinghui Zhao

Land 2026, 15(6), 907; https://doi.org/10.3390/land15060907 - 25 May 2026

The rapid expansion of the digital economy is reshaping urban systems, yet the pathways through which digitalization drives urban green land use transition remain insufficiently understood. Using panel data from 279 Chinese cities, we measure Urban Green Land Use Efficiency (UGLUE) via a [...] Read more.

The rapid expansion of the digital economy is reshaping urban systems, yet the pathways through which digitalization drives urban green land use transition remain insufficiently understood. Using panel data from 279 Chinese cities, we measure Urban Green Land Use Efficiency (UGLUE) via a super-efficiency Slack-Based Measure (SBM) model and estimate digital economy effects through double machine learning (DML). We find that digital technology, digital industry, and digital infrastructure all positively influence UGLUE, with digital technology exerting the strongest effect, followed by digital industry, while digital infrastructure exerts the weakest direct effect. Urban spatial compactness (USC) mediates this relationship, functioning as a dominant transmission channel for both digital industry and digital technology, and a supplementary yet significant pathway for digital infrastructure, indicating that digitalization enhances UGLUE in part by promoting more compact urban forms. Effects are heterogeneous, as resource-based and old industrial cities benefit more from technological upgrades, while cities with higher administrative status gain more from broader digital development. These findings identify USC as a key transition pathway linking digitalization to sustainable land use outcomes, and provide evidence-based support for governance-differentiated digital economy policies that steer urban land use transition toward green and compact development trajectories. Full article

(This article belongs to the Special Issue Land Use Transition Pathways: Governance, Resources, and Policies)

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16 pages, 1440 KB

Open AccessArticle

Closer to Home, More Trusted? Territorial Disparities in Government Trust Across Thai Regions

by Sanyarat Meesuwan and Jenn-Jaw Soong

Land 2026, 15(6), 906; https://doi.org/10.3390/land15060906 - 25 May 2026

From the Red Shirt heartlands of the North and Northeast to the conservative South and the fragmented middle-class electorate of Bangkok, Thailand’s regional divisions reflect a deeply contested relationship with centralized power. How these divisions shape citizens’ relative trust in local versus central [...] Read more.

From the Red Shirt heartlands of the North and Northeast to the conservative South and the fragmented middle-class electorate of Bangkok, Thailand’s regional divisions reflect a deeply contested relationship with centralized power. How these divisions shape citizens’ relative trust in local versus central government remains an open empirical question. Drawing on three waves of the Asian Barometer Survey conducted between 2014 and 2022 (pooled N = 3600), this study examines whether territorial location produces differential trust in local relative to central government. The findings are mixed. Regional differences are observable in baseline models, but their explanatory power diminishes once individual-level evaluations of political institutions and economic conditions are taken into account. Rural residents exhibit a smaller trust gap, indicating a weaker relative preference for local over central government, consistent with central welfare transfers sustaining support for the central tier. At the contextual level, higher regional poverty rates are associated with a compression of the trust gap between levels of government. Once poverty is introduced, the overall temporal increase observed by 2022 is no longer statistically significant. Structural economic geography explains much of the aggregate shift. Regional dynamics, however, are not uniform. The Northeast diverges sharply in the final wave, and the pattern holds across model specifications. The shift points to accumulated political alienation rooted in repeated episodes of electoral disenfranchisement. The findings carry direct implications for decentralization policy and territorial development strategy. Where regional trust gaps are driven by fiscal constraints on local government and accumulated political alienation, administrative redesign alone cannot restore citizen confidence in sub-national governance. Full article

(This article belongs to the Special Issue Decentralization and Development: Territorial Dimension and Spatial Disparities Mitigation)

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22 pages, 4367 KB

Open AccessArticle

Sustainable Governance of Photovoltaic Desert Control from the Perspective of Evolutionary Game Theory: A Case Study in Xinjiang, China

by Xin Zhang, Anming Bao, Siyu Chen and Shaobo Cai

Land 2026, 15(6), 905; https://doi.org/10.3390/land15060905 - 24 May 2026

Photovoltaic desert control (PVDC), an innovative model integrating clean energy development and desertification control, faces complex coordination challenges among local governments, local communities, and photovoltaic enterprises. This study constructs a tripartite evolutionary game model to identify the conditions that drive PVDC toward coordinated [...] Read more.

Photovoltaic desert control (PVDC), an innovative model integrating clean energy development and desertification control, faces complex coordination challenges among local governments, local communities, and photovoltaic enterprises. This study constructs a tripartite evolutionary game model to identify the conditions that drive PVDC toward coordinated governance. The model defines a three-dimensional strategy space: government regulatory intensity (Strong vs. Lax), community willingness to cooperate (Active Cooperation vs. Passive Resistance), and enterprise ecological integration (Active Ecological Integration vs. Passive Land Occupation). Replicator dynamic equations are derived to characterize nonlinear interactions, and the stability conditions of eight pure-strategy equilibrium points are identified through Jacobian matrix eigenvalue analysis. Numerical simulations are conducted using a baseline parameter set that satisfies the Evolutionary Stable Strategy conditions for the ideal equilibrium E8, namely Strong Regulation, Active Cooperation, and Active Ecological Integration. The results show that the system can converge to E8 when higher-level rewards cover government regulation, subsidy, and community-support costs; when community cooperation benefits exceed livelihood opportunity costs and compensation incentives from resistance; and when enterprises’ effective ecological integration costs are lower than the combined benefits of subsidies, avoided fines, and long-term returns. Sensitivity analysis further indicates that government subsidies, fines, community support, cooperation income, and enterprise long-term benefits are key drivers of system evolution, while excessive regulation costs, high opportunity costs, and high ecological integration costs may hinder coordination. Qualitative evidence from four PVDC-related cases in Xinjiang provides practical illustrations broadly consistent with the model mechanisms. This study offers a dynamic analytical framework for designing incentive-compatible governance mechanisms in PVDC and similar multi-stakeholder ecological restoration projects. Full article

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26 pages, 2287 KB

Open AccessArticle

Have Low-Carbon City Pilot Programs Improved Urban Land Use Efficiency? Evidence from 285 Prefecture-Level Cities in China

by Wuyun Wu, Chenghao Zhao and Chunmin Zhang

Land 2026, 15(6), 904; https://doi.org/10.3390/land15060904 - 24 May 2026

Against the backdrop of China’s “dual carbon” goals and urban green transition, improving urban land use efficiency is essential for shifting land development from extensive expansion to intensive and low-carbon use. Using the Low-Carbon City Pilot Program as a quasi-natural experiment, this study [...] Read more.

Against the backdrop of China’s “dual carbon” goals and urban green transition, improving urban land use efficiency is essential for shifting land development from extensive expansion to intensive and low-carbon use. Using the Low-Carbon City Pilot Program as a quasi-natural experiment, this study examines panel data from 285 prefecture-level cities in China from 2007 to 2023. We apply a multi-period difference-in-differences model, a threshold regression model, and a spatial Durbin model to assess the program’s impact on urban land use efficiency. The results show that the pilot program significantly improves urban land use efficiency, and the effect persists over time. This finding remains robust across a series of robustness checks. Heterogeneity analysis shows that the efficiency gains are stronger in cities with lower air pollution control pressure, higher industrial pollution control pressure, and lower fiscal pressure. Further threshold analysis shows that digital connectivity is a key condition for strengthening the policy effect. The spatial analysis suggests that the policy effect shows some spatial association. However, the decomposed indirect and total effects are not robust, so the spatial results should be interpreted with caution. This study provides empirical evidence on how low-carbon city pilots affect urban land governance and land use efficiency. Its conclusions, however, remain subject to limitations related to efficiency measurement, policy identification, and the availability of city-level data. Full article

(This article belongs to the Special Issue Advances in Urban Planning and Sustainable Mobility)

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32 pages, 4734 KB

Open AccessArticle

Multi-Source Remote Sensing–Driven Spatiotemporal Monitoring and SHAP-Based Driver Attribution of Soil Salinization in Arid Northwest China

by Yanrun Ren, Yaonan Zhang, Yufang Min and Yanbo Zhao

Land 2026, 15(6), 903; https://doi.org/10.3390/land15060903 - 23 May 2026

Soil salinization threatens agricultural sustainability in arid zones, yet quantitative attribution of its spatiotemporal dynamics to multi-source drivers remains scarce at regional scales. To address this, we developed an explainable framework merging Sentinel-1/2, ERA5-Land, and topographic-hydrological indices with XGBoost, trained under weak supervision [...] Read more.

Soil salinization threatens agricultural sustainability in arid zones, yet quantitative attribution of its spatiotemporal dynamics to multi-source drivers remains scarce at regional scales. To address this, we developed an explainable framework merging Sentinel-1/2, ERA5-Land, and topographic-hydrological indices with XGBoost, trained under weak supervision with proxy labels and independently validated using field-measured ECe. A 7-group, 44-feature ensemble with spatial block 5-fold cross-validation ensured robust assessment. SHapley Additive exPlanations (SHAP) quantified driver contributions and enabled a novel dominant driver zoning (DDZ) framework. Monitoring the Hexi Corridor and Tarim Basin (2017–2024) revealed contrasting trajectories: Hexi’s dynamics were primarily climate-driven (Aridity Index), whereas 19.2% of Tarim showed significant salinization along oasis–desert margins co-dominated by elevation, soil indices, and temperature. The model achieved spatial cross-validation R² values around 0.65. DDZ mapping showed climate dominance in 98.2% of Hexi compared to 76.5% in Tarim, where terrain and optical factors were more influential. The weak supervision strategy overcomes scarce in-situ measurements, while the DDZ maps identified that Land-use-dominated zones recorded the highest salinity, offering clear directives for targeted salinity control in arid basins. Full article

(This article belongs to the Section Land Use, Impact Assessment and Sustainability)

28 pages, 9922 KB

Open AccessArticle

A GeoAI-Based Physics-Enhanced Framework for Robust Short-Term Urban Waterlogging Prediction

by Xianyu Wu, Guanhao Jin, Yanting Zhong and Hui Lin

Land 2026, 15(6), 902; https://doi.org/10.3390/land15060902 - 23 May 2026

Accurate short-term prediction of urban waterlogging depth is essential for real-time flood risk management in rapidly urbanizing areas under climate variability. Departures from quasi-stationary operating conditions, caused by changes in drainage efficiency, inflow patterns, or measurement quality, weaken historical rainfall–water depth relationships, making [...] Read more.

Accurate short-term prediction of urban waterlogging depth is essential for real-time flood risk management in rapidly urbanizing areas under climate variability. Departures from quasi-stationary operating conditions, caused by changes in drainage efficiency, inflow patterns, or measurement quality, weaken historical rainfall–water depth relationships, making purely data-driven models prone to error accumulation. In this study, a GeoAI-based, physics-enhanced machine learning framework is proposed, which translates the water balance principle into Physical Violation Scores (PVSs) and incorporates them as additional input features. PVSs remain zero under expected rainfall–water depth behavior and become positive only under departure scenarios, providing sparse and lightweight diagnostic signals without modifying model structures or loss functions. The framework is implemented on five algorithms (Support Vector Machine, Multilayer Perceptron, Random Forest, Extremely Randomized Trees, and XGBoost) to construct physics-enhanced models (PEMs). These are evaluated against original feature models (OFMs) across 1 h and 2 h forecasting horizons. Results show that most PEMs improve prediction performance compared with their corresponding OFMs, with more pronounced gains at the 2 h horizon. Bootstrap analysis and RMSE-based error amplification factor further indicate comparable or lower R² variability and reduced recursive error amplification for most PEMs. Interpretability analyses show that rainfall forcing and water-depth persistence remain dominant predictors, whereas PVSs act as auxiliary diagnostic signals. Overall, the proposed framework provides a lightweight, reliable, interpretable, and scalable GeoAI approach for incorporating water balance knowledge into short-term urban waterlogging prediction, supporting climate resilience and smart urban water management. Full article

(This article belongs to the Special Issue GeoAI Application in Urban Land Use and Urban Climate)

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22 pages, 34955 KB

Open AccessArticle

Monitoring Mangrove Deforestation Using Google Earth Engine and Random Forest Machine Learning Algorithm

by Ahmad Fallatah, Abdullah Alattas, Amer Habibullah, Ammar Mandourah, Riyan Sahahiri, Ahmad Baik, Yahya Alshawabkeh and Mohamed Elfleet

Land 2026, 15(6), 901; https://doi.org/10.3390/land15060901 - 23 May 2026

Mangrove ecosystems provide critical coastal protection, biodiversity support, and carbon storage, yet they remain vulnerable to degradation caused by coastal development, pollution, and climate-related pressures. This study monitors mangrove dynamics in Al-Birk, Asir Region, Saudi Arabia, using Google Earth Engine (GEE), multi-temporal Landsat [...] Read more.

Mangrove ecosystems provide critical coastal protection, biodiversity support, and carbon storage, yet they remain vulnerable to degradation caused by coastal development, pollution, and climate-related pressures. This study monitors mangrove dynamics in Al-Birk, Asir Region, Saudi Arabia, using Google Earth Engine (GEE), multi-temporal Landsat imagery, spectral indices, and Random Forest (RF) classification. Landsat imagery from 2016 to 2021 was processed to derive NDVI, MSAVI2, EVI, and NDWI, and supervised RF classification was applied to map annual mangrove extent and associated land-cover classes. The RF classifier achieved an overall accuracy of 92.5% and a Kappa coefficient of 0.89. Results indicate that classified mangrove extent increased from approximately 1069 ha in 2016 to 1540 ha in 2021, representing a net gain of 471 ha and a 44% increase over the study period. A localized decline was detected between 2020 and 2021, indicating spatially uneven vegetation dynamics. The findings provide a spatial baseline for monitoring mangrove change and supporting coastal conservation planning in Saudi Arabia. While the detected expansion is temporally consistent with ongoing restoration initiatives, the study does not establish direct causality between policy interventions and observed spatial changes. Full article

(This article belongs to the Special Issue Urban Green Infrastructure: Enhancing Resilience and Well-Being in the Face of Climate Change and Urbanization (Second Edition))

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28 pages, 16060 KB

Open AccessArticle

An XGBoost–SHAP Explainable Machine Learning Approach Linking Urban Park Cooling Effects in a Megacity Core to Landscape Features Inside and Outside the Parks

by Yige Guan, Xintong Du and Haiyue Zhao

Land 2026, 15(6), 900; https://doi.org/10.3390/land15060900 - 23 May 2026

Urban parks, as essential components of green infrastructure, play a critical role in mitigating the urban heat island effect and improving thermal comfort. This study evaluated the cooling performance of 170 parks in the urban center region of Beijing using seven cooling effect [...] Read more.

Urban parks, as essential components of green infrastructure, play a critical role in mitigating the urban heat island effect and improving thermal comfort. This study evaluated the cooling performance of 170 parks in the urban center region of Beijing using seven cooling effect indicators. An integrated framework combining XGBoost, SHAP, and Ordinary Least Squares was proposed to examine the nonlinear relationships and threshold effects between cooling effect indicators and landscape features. Moreover, the Elbow method and K-means clustering were applied to classify parks based on their cooling performance. The results showed that both internal and external landscape features are closely associated with park cooling effects. Eight features were identified as key landscape features, possessing higher relative importance. Pronounced nonlinear relationships and threshold effects were identified. For example, the optimal park area is approximately 25 hm², while more regular shapes enhance cooling performance, with an optimal ratio of perimeter and area of about 0.05 m⁻¹. Furthermore, four distinct park types with significantly different cooling performance were identified, reflecting different capacities for regulating urban thermal environments. These findings improved the understanding of park cooling effects and provided guidance for optimizing park design in megacity cores. Full article

(This article belongs to the Section Land Planning and Landscape Architecture)

28 pages, 12278 KB

Open AccessArticle

Heritage Conservation as Degrowth Practice: Multi-Scalar Analysis of Gasholder Adaptive Reuse in London and Edinburgh

by Yihang Sui, Jiayi Jin and Ayse Ozbil Torun

Land 2026, 15(6), 899; https://doi.org/10.3390/land15060899 - 23 May 2026

Industrial heritage adaptive reuse occupies a structurally privileged position for degrowth: heritage listing already institutionalises material sufficiency as a regulatory obligation, mandating low intervention and resisting the demolish-and-replace logic of resource-intensive development. Yet this regulatory floor imposes no ceiling on how protected structures [...] Read more.

Industrial heritage adaptive reuse occupies a structurally privileged position for degrowth: heritage listing already institutionalises material sufficiency as a regulatory obligation, mandating low intervention and resisting the demolish-and-replace logic of resource-intensive development. Yet this regulatory floor imposes no ceiling on how protected structures are programmed or who benefits; the same statutory instrument can produce different schemes depending entirely on governance. This paper demonstrates that gap through two contrasting UK gasholder adaptive reuse projects: King’s Cross Gasholders in London (private-led, luxury residential) and Granton Gasholder in Edinburgh (council-led community park). Applying De Castro Mazarro et al.’s multi-scalar degrowth framework across building, neighbourhood, and city scales through document analysis and site observations, we identify structural mechanisms explaining why building-scale alignment fails to propagate upward. The findings indicate three governance conditions are necessary to convert the structural degrowth potential of industrial heritage into substantive outcomes: public control over development decisions, community participation extended to strategic priorities rather than design preferences, and explicit integration of degrowth values into upstream planning frameworks. Industrial heritage adaptive reuse is not inherently a degrowth practice, but it is one of the few urban development contexts where the regulatory preconditions for degrowth alignment are already in place. Realising that potential requires governance structures that treat sufficiency and collective wellbeing as binding objectives, not rhetorical claims. Full article

(This article belongs to the Special Issue Urban Transitions and Dynamics: Cultural, Ecological, Digital and Degrowth (Second Edition))

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17 pages, 7244 KB

Open AccessArticle

Remnants of Semi-Natural Habitats Sustain Nocturnal Lepidoptera Diversity Within a Mediterranean Vineyard System

by Giada Zucco, Sara La Cava, Marco Infusino and Stefano Scalercio

Land 2026, 15(6), 898; https://doi.org/10.3390/land15060898 - 22 May 2026

Agricultural intensification has led to landscape homogenization and the widespread loss of semi-natural habitats, contributing to biodiversity decline in agroecosystems. Semi-natural areas embedded within croplands may mitigate these effects by acting as reservoirs and steppingstones for species providing ecosystem services such as pollination. [...] Read more.

Agricultural intensification has led to landscape homogenization and the widespread loss of semi-natural habitats, contributing to biodiversity decline in agroecosystems. Semi-natural areas embedded within croplands may mitigate these effects by acting as reservoirs and steppingstones for species providing ecosystem services such as pollination. We assessed the role of remnants of semi-natural habitats in sustaining the diversity and abundance of nocturnal Lepidoptera within a Mediterranean vineyard landscape (southern Italy) using monthly light trap sampling over almost one year. Assemblages were compared between vineyards and adjacent semi-natural patches. Multivariate analyses revealed marked differences in community composition between semi-natural habitat types. Species richness was consistently higher in semi-natural habitats, even when represented by small residual patches. Vineyard assemblages were characterized by reduced richness and a predominance of generalist species with high dispersal ability, indicating a simplified community structure. Nevertheless, some taxa of biogeographical interest were recorded. These findings demonstrate the importance of semi-natural habitats in maintaining nocturnal Lepidoptera diversity in vineyard-dominated landscapes and support their integration into sustainable agricultural management to enhance biodiversity conservation and the provision of ecosystem services. Full article

(This article belongs to the Section Landscape Ecology)

19 pages, 1140 KB

Open AccessArticle

Investigating Coupling Coordination Between Urban Development and Ecological Efficiency: Evidence from the Yangtze River Delta

by Zhenzhen He and Chin-Hong Puah

Land 2026, 15(6), 897; https://doi.org/10.3390/land15060897 - 22 May 2026

This paper investigates the evolution and driving mechanisms of the Coupling Coordination Degree (CCD) between urban development (UD) and ecological efficiency (EE) in the Yangtze River Delta (YRD) urban agglomeration. Using panel data for 27 cities from 2013 to 2023, a comprehensive evaluation [...] Read more.

This paper investigates the evolution and driving mechanisms of the Coupling Coordination Degree (CCD) between urban development (UD) and ecological efficiency (EE) in the Yangtze River Delta (YRD) urban agglomeration. Using panel data for 27 cities from 2013 to 2023, a comprehensive evaluation model and the CCD model are used to measure the level of coordination across cities. A fixed-effects panel regression model is constructed to systematically examine the effects of economic development and education expenditure on CCD, focusing on the moderating role of education expenditure. The empirical results indicate that: (1) CCD in the YRD shows a clear upward trend, gradually shifting from disorder to coordinated development; (2) inter-city disparities remain evident, reflecting differences in development foundations, industrial structures, and governance capacities; (3) economic development significantly promotes CCD by providing material and institutional support for urban–ecological coordination; and (4) education expenditure strengthens this positive relationship by enhancing human capital accumulation and knowledge spillovers. The findings highlight the importance of integrating economic growth with human capital investment to promote green and high-quality urban development. Full article

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