Land | October 2025 - Browse Articles

28 pages, 12698 KB

Open AccessArticle

Innovative Multi-Type Identification System for Cropland Abandonment on the Loess Plateau: Spatiotemporal Dynamics, Driver Shifts (2000–2023) and Implications for Food Security

by Wei Song

Land 2025, 14(10), 2062; https://doi.org/10.3390/land14102062 (registering DOI) - 15 Oct 2025

Abstract

As a critical ecological barrier and key dryland agricultural zone in China, the Loess Plateau is faced with acute tensions between food security risks arising from cropland abandonment (CA) and the imperatives of ecological conservation. Yet, existing research has failed to adequately capture [...] Read more.

As a critical ecological barrier and key dryland agricultural zone in China, the Loess Plateau is faced with acute tensions between food security risks arising from cropland abandonment (CA) and the imperatives of ecological conservation. Yet, existing research has failed to adequately capture the long-term, high-spatiotemporal-resolution dynamics of abandonment in this region or to quantitatively couple its driving mechanisms with implications for food security. To address these gaps, this study establishes a high-precision identification system for CA tailored to the Plateau’s complex topographic conditions, distinguishing among interannual abandonment, multiyear abandonment, conversion to forest/grassland, and reclamation. Leveraging long-term data from 2000 to 2023 and integrating the Mann–Kendall test with the random forest algorithm, we examine the spatiotemporal trajectories, driving forces, and food security consequences of CA. Guided by a “type differentiation–grade classification–temporal tracking” framework, the analysis reveals a marked transition in dominant drivers from “socioeconomic factors” to “topographic–climatic factors.” It further identifies an “increasing loss–slowing growth” effect of abandonment on grain production, alongside a “pressure alleviation” trend in per capita carrying capacity. The results showed that: (1) Between 2000 and 2023, the area of CA on the Loess Plateau expanded from 2.72 million ha to 6.96 million ha, with high-grade abandonment (≥8 years) accounting for 58.9% of the total and being spatially concentrated in the hilly–gully regions of northern Shaanxi and eastern Gansu; (2) The Grain for Green Project (GFGP) peaked at approximately 340,000 hectares in 2018, followed by a slight decline, but has generally remained at around 300,000 hectares since then; (3) The reclamation rate of CA remained between 5% and 12% during 2003–2015, with minimal overall fluctuations, but after 2016, it gradually increased and peaked at 23.4% in 2022; (4) In terms of driving forces, population density (14.99%) was the primary determinant in 2005, whereas by 2020, slope (15.43%) and mean annual precipitation (15.63%) emerged as core factors; and (5) Grain yield losses attributable to abandonment increased from less than 100 t to nearly 450 t, though the growth rate slowed after 2016, accompanied by gradual alleviation of pressure on per capita carrying capacity. Overall, the study offers robust empirical evidence to inform cropland protection, food security strategies, and sustainable agricultural development policies on the Loess Plateau. Full article

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31 pages, 11923 KB

Open AccessArticle

Spatiotemporal Evolution and Driving Mechanisms of Ecosystem Service Value–Urbanization Coupling Coordination in the Yangtze River Delta

by Xiaoyao Gao and Chunshan Zhou

Land 2025, 14(10), 2061; https://doi.org/10.3390/land14102061 (registering DOI) - 15 Oct 2025

Abstract

The interactive coupling mechanism between ecosystem service value (ESV) and urbanization has emerged as a critical research focus in ecological security and sustainable development. This study quantifies the ESV of prefecture-level cities by leveraging remote sensing data and socioeconomic statistics from the Yangtze [...] Read more.

The interactive coupling mechanism between ecosystem service value (ESV) and urbanization has emerged as a critical research focus in ecological security and sustainable development. This study quantifies the ESV of prefecture-level cities by leveraging remote sensing data and socioeconomic statistics from the Yangtze River Delta (YRD) region spanning 2006—2020. It constructs a multidimensional evaluation index system for urbanization. We systematically assess both systems’ spatiotemporal evolution and interactions by employing entropy weighting, comprehensive indexing, and coupling coordination models. Furthermore, Geo-detectors and Geographical and Temporal Weighted Regression (GTWR) models are applied to identify driving factors influencing their coordinated development. Key findings include (1) the total amount of ESV in the YRD exhibits a fluctuating decline, primarily due to a steady increase in urbanization levels; (2) the coordination degree between ESV and urbanization demonstrates phased growth, transitioning to a “basic coordination” stage post-2009; (3) spatially, coordination patterns follow a “core–periphery” hierarchy, marked by radial diffusion and gradient disparities, with most cities being of the ESV-guidance type; (4) GTWR analysis reveals spatiotemporal heterogeneity in driving factors, ranked by intensity as Normalized Difference Vegetation Index (NDVI) > Economic density (ECON) > Degree of openness (OPEN) > Scientific and technological level (TECH) > Industrial structure upgrading index (ISUI) > Government investment efforts (GOV). This study advances methodological frameworks for analyzing ecosystem–urbanization interactions in metropolitan regions, while offering empirical support for ecological planning, dynamic redline adjustments, and territorial spatial optimization in the YRD, particularly within the Ecological Green Integrated Development Demonstration Zone. Full article

(This article belongs to the Topic Ecosystem-Based Adaptation: A Holistic Approach to Pursue Multiple Benefits)

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39 pages, 5033 KB

Open AccessArticle

Territorial Functional Pattern Reconstruction Integrating Set-Theoretic and Functional Mappings with Game-Theoretic Analysis to Reconcile Development and Conservation in China

by Dinghua Ou, Xiaofan Cheng, Zijia Yan, Kun Ruan, Qingyan Huang, Zhi Zhao, Ziheng Yang, Jing Qin and Jianguo Xia

Land 2025, 14(10), 2060; https://doi.org/10.3390/land14102060 (registering DOI) - 15 Oct 2025

Abstract

The contradiction between economic development and ecological protection has become a common challenge for territorial governance in developing countries around the world. However, extant studies have neglected the coupling and symbiotic relationship between humans and nature, resulting in significant functional conflicts, insufficient stability, [...] Read more.

The contradiction between economic development and ecological protection has become a common challenge for territorial governance in developing countries around the world. However, extant studies have neglected the coupling and symbiotic relationship between humans and nature, resulting in significant functional conflicts, insufficient stability, and imbalances in ecological and economic benefits in the reconstruction of territorial spatial functional pattern (TSFP), making it difficult to achieve synergies between development and protection. The question that arises is how the TSFP can be reconstructed in order to achieve harmonious coexistence between humans and nature. This remains a challenging problem in the context of the synergizing development and protection of the TSFP. This study innovatively integrates set-theoretic principles and functional mappings with game-theoretic analysis to develop Territorial Spatial Functional Pattern Reconstruction (TSFPR) model designed to foster harmonious human–nature coexistence, and validates the model using geospatial data from Qionglai City, China. Empirical evidence demonstrates that, in comparison with conventional methods, TSFPR model significantly mitigates the territorial spatial functional conflicts (TSFCs), enhances stability and ecological and economic benefits, and achieves the expected harmonious coexistence between humans and nature. The analysis confirms that the territorial spatial functional conflict (TSFC) coordination index established in this study provides a reliable criterion for identifying superior territorial spatial functions (TSFs). The proposed TSFPR model is an expansion of the theory of spatial optimization modelling, and it provides a tool for reconstructing the TSFP for the harmonious coexistence between humans and nature. In summary, the utilization of the TSFPR model to reconstruct the TSFP for harmonious coexistence between humans and nature provides a novel solution for coordinating the development and protection of territorial space governance. Full article

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28 pages, 5860 KB

Open AccessArticle

Improving Landslide Susceptibility Assessment Through Non-Landslide Sampling Strategies

by Liping Tu, Meiqiu Chen, Peng Leng, Shengwei Liu, Mei’e Liu, Wang Luo and Yaqin Mao

Land 2025, 14(10), 2059; https://doi.org/10.3390/land14102059 - 15 Oct 2025

Abstract

Landslides are a prevalent geological hazard in China, posing significant threats to life and property. Landslide susceptibility assessment is essential for disaster prevention, and the quality of non-landslide samples critically affects model accuracy. This study takes Yongxin County, Jiangxi Province, as a case, [...] Read more.

Landslides are a prevalent geological hazard in China, posing significant threats to life and property. Landslide susceptibility assessment is essential for disaster prevention, and the quality of non-landslide samples critically affects model accuracy. This study takes Yongxin County, Jiangxi Province, as a case, selecting ten susceptibility factors and applying the Random Forest (RF) model with six non-landslide sampling methods for comparison. Results indicate that non-landslide sample selection substantially influences model performance, with the RF model using the IV method achieving the highest accuracy (AUC = 0.9878). SHAP analysis identifies NDVI, slope, lithology, land cover, and elevation as the primary contributing factors. Statistical results show that RF_IV non-landslide sample predictions are lowest, mainly below 0.18, with a median of 0.18, confirming that the IV method effectively excludes landslide-prone areas and accurately represents non-landslide regions. These findings provide practical guidance for landslide risk managers, local authorities, and policymakers, and offer methodological insights for researchers in geological hazard modeling. Full article

(This article belongs to the Topic Disaster and Environment Monitoring Based on Multisource Remote Sensing Images)

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4 pages, 132 KB

Open AccessEditorial

GeoAI for Land Use Observations, Analysis, and Forecasting

by Wenfeng Zheng, Kenan Li and Xuan Liu

Land 2025, 14(10), 2058; https://doi.org/10.3390/land14102058 - 15 Oct 2025

Abstract

Geographic artificial intelligence (GeoAI) is reshaping how we observe, understand, and govern land systems [...] Full article

(This article belongs to the Special Issue GeoAI for Land Use Observations, Analysis and Forecasting)

20 pages, 2132 KB

Open AccessArticle

Research on the Influencing Factors of the Cropland Abandonment Behavior of Different Typical Types of Farming Households: Based on a Survey in Mountainous Areas

by Yingbin Feng, Jingjing Li and Dedong Feng

Land 2025, 14(10), 2057; https://doi.org/10.3390/land14102057 - 15 Oct 2025

Abstract

Cropland abandonment (CA) is a critical environmental issue globally, with balancing food security and ecological protection vital for sustainable development. This study explores CA behavior differences and drivers between out-of-poverty farming households (OPFHs) and non-poverty farming households (NPFHs) in China′s mountainous areas, using [...] Read more.

Cropland abandonment (CA) is a critical environmental issue globally, with balancing food security and ecological protection vital for sustainable development. This study explores CA behavior differences and drivers between out-of-poverty farming households (OPFHs) and non-poverty farming households (NPFHs) in China′s mountainous areas, using stepwise regression on survey data from 321 households in Liping County, Guizhou. The results show that: (1) The differences in CA behaviors between the two types of farming households are mainly reflected at the farmer level and the plot level. Plot integrity is a common influencing factor of CA areas for both types of farming households. (2) The driving factors affecting the area of CA by OPFHs also include the average age of the labor force, the proportion of the resident population in the total household registration population, and plot type, while the drivers affecting the area of CA by NPFHs include per capita income, non-agricultural income, per capita cropland area, and commuting time. (3) The differences in CA behavior and its driving factors between OPFHs and NPFHs in mountainous areas are characterized by diversity and interaction. Based on the results of the study, we propose the management of farming households and cropland, which can contribute to rural revitalization in China and the world, to a certain extent. Full article

(This article belongs to the Topic Global Farmland Protection, Food Security and Land Use Planning)

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19 pages, 3248 KB

Open AccessArticle

Effects of Riparian Zone Width and Soil Depth: Soil Environmental Factors Drive Changes in Soil Enzyme Activity

by Zixuan Yan, Peng Li, Chaohong Feng, Yongxiang Cao, Kunming Lu, Chenxu Zhao and Zhanbin Li

Land 2025, 14(10), 2056; https://doi.org/10.3390/land14102056 - 15 Oct 2025

Abstract

Functioning as a critical ecotone between terrestrial and aquatic ecosystems, riparian zones exhibit soil enzyme activities that serve as key biomarkers of their nutrient cycling processes. However, despite considerable focus on riparian soil properties, the dynamics and underlying drivers of these enzymatic activities [...] Read more.

Functioning as a critical ecotone between terrestrial and aquatic ecosystems, riparian zones exhibit soil enzyme activities that serve as key biomarkers of their nutrient cycling processes. However, despite considerable focus on riparian soil properties, the dynamics and underlying drivers of these enzymatic activities are not yet fully characterized. To this end, soils were systematically sampled across varying widths and depths from three representative riparian zones to quantify the driving forces of physicochemical properties on enzyme activity dynamics. The results showed that the soil enzyme activity was highest in the forest riparian zone and lowest in the farmland riparian zone, with average enzyme activities of 37.95 (μmol·g⁻¹·h⁻¹) and 26.85 (μmol·g⁻¹·h⁻¹), respectively. The width of the riparian zone changes the spatial distribution of soil enzyme activity. The soil enzyme activity is higher in the land edge area far from the river (profile-1) and lower in the water edge area near the river (profile-4), with average enzyme activities of 47.4384 (μmol·g⁻¹·h⁻¹) and 17.0017 (μmol·g⁻¹·h⁻¹), respectively. Moreover, soil water content (SWC) has a strong impact on enzyme activity changes. The increase in soil depth reduces soil enzyme activity, with enzyme activity in the 0–20 cm soil layer being 1.5 times higher than in the 20–50 cm soil layer. Meanwhile, the primary factors influencing changes in soil enzyme activity have gradually shifted from total nitrogen (TN), nitrate nitrogen (NO₃-N), and soil organic carbon (SOC) to the sole control of SOC. Research has shown that human influence strongly interferes with soil enzyme activity in riparian zones. The width of the riparian zone and soil depth serve as key drivers of the spatial distribution of soil enzyme activity by modulating soil environmental factors. The patterns revealed in this study indicate that maintaining appropriate riparian zone width and reducing anthropogenic disturbances can enhance nutrient cycling dynamics at the micro-scale by increasing soil enzyme activity. This process is crucial for strengthening the riparian zone’s macro-level ecosystem services, particularly by effectively enhancing its capacity to sequester and transform nutrients like nitrogen and phosphorus from agricultural nonpoint sources, thereby safeguarding downstream water quality. Consequently, soil enzyme activity serves as a key indicator, providing essential scientific basis for assessing riparian health and guiding ecological restoration efforts. Full article

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28 pages, 22364 KB

Open AccessArticle

Assessment and Layout Optimization of Urban Parks Based on Accessibility and Green Space Justice: A Case Study of Zhengzhou City, China

by Shengnan Zhao, Xirui Wen, Yuhang Ge, Xuning Qiao, Yu Wang, Jing Zhang and Wenfei Luan

Land 2025, 14(10), 2055; https://doi.org/10.3390/land14102055 - 15 Oct 2025

Abstract

Addressing the imbalance between supply and demand for urban parks necessitates an assessment of their service accessibility and spatial equity. This study integrates multi-source geographic data, uses multiple data sources to generate a population distribution with high spatial resolution, and constructs park service [...] Read more.

Addressing the imbalance between supply and demand for urban parks necessitates an assessment of their service accessibility and spatial equity. This study integrates multi-source geographic data, uses multiple data sources to generate a population distribution with high spatial resolution, and constructs park service areas with multiple time thresholds based on travel preference surveys. The network analysis method is used to evaluate the supply–demand ratio and spatial equity by using location entropy, Lorenz curves, and the Gini coefficient to identify the optimal location. The results reveal a significant difference in the supply–demand ratio of parks. Within the 5 min time threshold, only 14.68% of the pixels in the park supply area meet the needs of residents, while the proportions for the 15 min and 30 min time service area expands to 71.74% and 86.34%, respectively. The distribution of parks exhibits apparent spatial inequity. Equity is highest for the 15 min service area (Gini coefficient = 0.25), followed by the 30 min area (Gini coefficient = 0.27) and 5 min areas (Gini coefficient = 0.37). Among the 80 streets in the study area, the per capita green space location entropy of 11 streets is zero. A targeted site selection analysis for areas with park supply deficiencies led to the proposed addition of 11 new parks. After this optimization, the proportion of regions achieving supply–demand balance or better reached 80.38%, significantly alleviating the supply–demand conflict. This study reveals the characteristics of park supply–demand imbalance and spatial equity under different travel modes and time thresholds, providing a scientific basis for the precise planning and equity enhancement of parks in high-density cities. Full article

(This article belongs to the Special Issue Green Spaces and Urban Morphology: Building Sustainable Cities)

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23 pages, 2397 KB

Open AccessArticle

Research on Social-Ecological Resilience Assessment of Rural Settlements in Typical Mountainous Areas of Southwest China Based on the Coordination of Kernel and Peripheral Systems

by Wei Cao, Qingyuan Yang, Yan Liu, Xiaoyu Liu, Huiyu He, Jinrong Yang, Qiao Deng and Yahui Wang

Land 2025, 14(10), 2054; https://doi.org/10.3390/land14102054 - 15 Oct 2025

Abstract

The social-ecological resilience of rural settlements refers to their ability to resist and mitigate the risks posed by internal and external disturbances, and to utilize the external environment to achieve a new equilibrium state. Amid rapid urbanization, it is of great significance for [...] Read more.

The social-ecological resilience of rural settlements refers to their ability to resist and mitigate the risks posed by internal and external disturbances, and to utilize the external environment to achieve a new equilibrium state. Amid rapid urbanization, it is of great significance for mountainous settlements to improve their risk resistance and development ability. Taking Dong’an Town in Chengkou County, located in the eastern part of Qinling–Bashan Mountains in southwestern China, as the research object, this study constructs an evaluation index system for rural residential resilience based on social-ecological resilience theory. It explores the resilience level of rural residences in mountainous areas from the dimensions of internal resilience and external environmental resilience and scientifically proposes an optimization path for the spatial layout of rural residences. This study provides a reference for optimizing the rural living environment, promoting spatial equity, and improving people’s livelihood according to local conditions. The results showed that: (1) The overall level of security resilience of rural settlements in Dong’an Town was relatively high, with 221 patches above the security level, accounting for 19.53% of the total area of the town. (2) The rural residents in Dong’an Town can be categorized into three types: core structure optimization, peripheral system upgrading, and relocation and withdrawal. Different types of rural settlements adapt to internal and external resource conditions and select optimal spatial layout paths according to local conditions. Full article

(This article belongs to the Topic Global Farmland Protection, Food Security and Land Use Planning)

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28 pages, 2350 KB

Open AccessArticle

Evolving Green Premiums: The Impact of Energy Efficiency on London Housing Prices over Time

by Jiabin Wei and Richard Peiser

Land 2025, 14(10), 2053; https://doi.org/10.3390/land14102053 - 14 Oct 2025

Abstract

As climate policy and energy costs increasingly influence housing markets, understanding how energy efficiency is capitalized into home prices has become a critical question for both researchers and policymakers. While prior studies confirm the existence of a green premium—the price advantage of more [...] Read more.

As climate policy and energy costs increasingly influence housing markets, understanding how energy efficiency is capitalized into home prices has become a critical question for both researchers and policymakers. While prior studies confirm the existence of a green premium—the price advantage of more energy-efficient homes—less is known about how this premium evolves over time in response to shifting regulations, awareness, and market conditions. This study provides new empirical evidence on the dynamic valuation of energy efficiency in the London housing market between 2013 and 2021. Using a repeat-sales framework, we isolate within-property price changes and examine how energy performance is capitalized over time. We find that the green premium associated with higher current energy efficiency strengthened steadily, rising from statistically insignificant levels in 2013 to approximately 0.47% per Energy Performance Certificate (EPC) point by 2021. Meanwhile, the price penalty for a large efficiency gap, reflecting unrealized upgrade potential, narrowed substantially in 2020 and 2021, indicating a marked reduction in buyers’ aversion to less efficient homes. This study adds a new dimension to the green premium literature. It provides empirical evidence that the relationship between energy efficiency and housing value is not static, but responsive to regulatory, economic, and social changes. By tracking year-by-year changes in London, our analysis offers insight into how quickly market preferences adjust and how interventions like minimum efficiency standards translate into property values. This enriched understanding moves the field beyond the question of whether a green premium exists, to how and why it evolves. Full article

(This article belongs to the Special Issue Urban and Rural Development Planning for Resilient Human Environments (Second Edition))

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16 pages, 2042 KB

Open AccessArticle

Suitability Assessment of Pastoral Human Settlements in Xilingol League Based on an Optimized MaxEnt Model

by Sen Mu, Jianghong Zhen, Chun Xi and Lei Wang

Land 2025, 14(10), 2052; https://doi.org/10.3390/land14102052 - 14 Oct 2025

Abstract

Assessing the suitability of human settlements is of great significance for promoting pastoral development, improving herders’ livelihoods, and advancing the construction of beautiful villages in agro-pastoral regions. Focusing on ten pastoral banners within Xilingol League, a representative pastoral region in northern China, this [...] Read more.

Assessing the suitability of human settlements is of great significance for promoting pastoral development, improving herders’ livelihoods, and advancing the construction of beautiful villages in agro-pastoral regions. Focusing on ten pastoral banners within Xilingol League, a representative pastoral region in northern China, this study employed the Google Earth Engine (GEE) platform combined with statistical datasets to evaluate settlement suitability using an optimized MaxEnt model. Fourteen key influencing factors were identified, and the spatiotemporal dynamics of settlement suitability in 2017 and 2024 were analyzed, together with predictions of suitable area distribution. The results showed that the model achieved the highest accuracy when using a linear combination of linear, quadratic, hinge, product, and threshold features with a regularization multiplier of 5.0. Suitable areas were mainly located in the southern part of the League, characterized by higher elevation, moderate temperatures, sufficient water resources, and relatively developed economies, while unsuitable areas were concentrated along the northwestern and northeastern borders with Mongolia. Spatially, settlement suitability exhibited a decreasing gradient from the southwest to the northeast. Furthermore, the dominant driving factors have gradually shifted from ecological conditions to socio-economic conditions. Overall, the suitability of pastoral human settlements in Xilingol League has continued to improve, providing new insights for suitability evaluation and spatial restructuring in pastoral regions. Full article

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

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31 pages, 6827 KB

Open AccessArticle

Human–Nature Interaction Pattern Design in Landscape Architecture

by Hongfei Li and Peter H. Kahn, Jr.

Land 2025, 14(10), 2051; https://doi.org/10.3390/land14102051 - 14 Oct 2025

Abstract

Landscape architecture has long engaged esthetics, ecological process, and cultural meaning, and contemporary practice increasingly embraces systemic and process-based approaches. Yet even within this richness, designers often lack systematic tools for addressing how embodied interaction shapes human–nature relationships. Granted, frameworks such as biophilic [...] Read more.

Landscape architecture has long engaged esthetics, ecological process, and cultural meaning, and contemporary practice increasingly embraces systemic and process-based approaches. Yet even within this richness, designers often lack systematic tools for addressing how embodied interaction shapes human–nature relationships. Granted, frameworks such as biophilic design and restorative environments emphasize the importance of contact with nature. Yet they often stop short of specifying the sensory and movement-based interactions through which agency, well-being, and meaning are cultivated. To address this gap, this paper introduces Interaction Pattern Design (IPD) as a theory-grounded and practice-oriented framework for landscape architecture. The first part of the paper outlines what interaction patterns are, how they scale along the continuum from highly domestic to relatively wild environments, and the empirical evidence that establishes their significance. The second half of this paper speaks to designers specifically and applies this IP approach to the design process. Two design tools are introduced. One is Quadrant Mapping, which visualizes intersections of environmental and behavioral wildness within a site. The second is Structuring Interaction Patterns, which organizes design elements through scale, sequence, and co-occurrence. Drawing from case studies, the paper demonstrates how these tools enrich process- and ecology-focused design methods, supporting deeper and more enduring forms of engagement with nature. Full article

(This article belongs to the Special Issue Feature Papers for Land Planning and Landscape Architecture Section, Second Edition)

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23 pages, 4665 KB

Open AccessArticle

Objective Parameterization of InVEST Habitat Quality Model Using Integrated PCA-SEM-Spatial Analysis: A Biotope Map-Based Framework

by Dong Uk Kim and Hye Yeon Yoon

Land 2025, 14(10), 2050; https://doi.org/10.3390/land14102050 - 14 Oct 2025

Abstract

Current InVEST habitat quality assessments rely heavily on subjective expert judgment for parameter specification, introducing substantial uncertainty and limiting their regional applicability. To address this gap, we developed an objective, statistically rigorous framework for parameter derivation by integrating Principal Component Analysis (PCA), Structural [...] Read more.

Current InVEST habitat quality assessments rely heavily on subjective expert judgment for parameter specification, introducing substantial uncertainty and limiting their regional applicability. To address this gap, we developed an objective, statistically rigorous framework for parameter derivation by integrating Principal Component Analysis (PCA), Structural Equation Modeling (SEM), and spatial analysis, supported by high-resolution biotope mapping. The methodology was applied to Gochang-gun, South Korea, where nine threat factors were analyzed using empirical data from 6633 sampling points. PCA identified threat groupings, SEM quantified habitat–threat relationships for sensitivity derivation, and variogram analysis determined maximum influence distances, while 1:5000 scale biotope maps incorporating 14 ecological indicators replaced conventional land cover classifications. These empirically derived parameters were directly incorporated into the InVEST Habitat Quality model, replacing default or expert-based values. As a result, the biotope-based InVEST HQ implementation achieved exceptional performance (R² = 0.892) with crops emerging as the dominant threat factor (sensitivity = 1.000, weight = 34.1%). Compared to the land use/land cover (LULC)-based approach using conventional parameterization, the biotope–PCA–SEM model demonstrated higher predictive accuracy (AUC = 0.805 vs. 0.755), stronger correlations with independent conservation indicators (protected area correlation: 0.457 vs. 0.201), and clearer ecological gradients across UNESCO Biosphere Reserve zones. This framework eliminates subjective bias while maintaining regional specificity, establishing a transferable foundation for evidence-based conservation planning. By demonstrating substantial improvements over conventional parameterization, the study highlights the inadequacy of transferred parameters and provides an objective standard for advancing InVEST applications worldwide. Full article

(This article belongs to the Special Issue Advancements in Geospatial Techniques for Land Change Analysis and Management)

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22 pages, 7988 KB

Open AccessArticle

Urbanization, Rural E-Commerce Villages, and Regional Solutions for Urban–Rural Coordinated Development in China

by Zhikun Yue, Xungang Zheng, Linling Zhong and Wang Zhang

Land 2025, 14(10), 2049; https://doi.org/10.3390/land14102049 - 14 Oct 2025

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Abstract

With the rapid development of e-commerce, Taobao Villages have emerged as a representative form of rural e-commerce in China, exerting a profound influence on rural economic transformation and urban–rural integration. However, their spatiotemporal distribution is uneven and exhibits a complex interaction with urbanization. [...] Read more.

With the rapid development of e-commerce, Taobao Villages have emerged as a representative form of rural e-commerce in China, exerting a profound influence on rural economic transformation and urban–rural integration. However, their spatiotemporal distribution is uneven and exhibits a complex interaction with urbanization. Drawing on data from 178 cities between 2017 and 2022, this study employs the Spatial Autoregressive Model (SAR), Spatial Error Model (SEM), and Spatial Durbin Model (SDM) to examine both the direct and spillover effects of urbanization on Taobao Villages. The results indicate that Taobao Villages display significant spatial clustering across China. While urbanization exerts a positive short-term effect on the number of local Taobao Villages, this effect weakens in the long term and under spatial interaction, and higher levels of urbanization in one region impose significant negative spillover effects on neighboring areas. These findings highlight the dual nature of urbanization in simultaneously promoting and constraining rural e-commerce development. Accordingly, policy efforts should focus on rational administrative spatial adjustment and boundary reorganization, optimizing the urban–rural spatial structure, supporting the development of peripheral and disadvantaged regions, enhancing the balanced and efficient flow of factors across regions, and fostering differentiated development pathways to strengthen the resilience of Taobao Villages and promote healthy and sustainable urban–rural integration. Full article

(This article belongs to the Special Issue Regional Solutions to Urban-Rural Coordinated Development in the Megacity Regions (3rd Edition))

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17 pages, 1568 KB

Open AccessPerspective

Restoring Waterways, But for Whom? Environmental Justice, Human Rights, and the Unhoused

by Sharon Moran and Richard Smardon

Land 2025, 14(10), 2048; https://doi.org/10.3390/land14102048 - 14 Oct 2025

Viewed by 14

Abstract

The restoration of waterways is increasingly understood as an endeavor that could (and should) be beneficial for both ecosystems and people. Researchers have already explored several ways that restoration can mediate in favor of environmental justice goals, while simultaneously acknowledging the dangers of [...] Read more.

The restoration of waterways is increasingly understood as an endeavor that could (and should) be beneficial for both ecosystems and people. Researchers have already explored several ways that restoration can mediate in favor of environmental justice goals, while simultaneously acknowledging the dangers of green gentrification. This paper extends the inquiries about waterway restoration and environmental justice to include a focus on one of society’s most frequently marginalized groups, unhoused people. Working inductively, we conduct a scoping study that examines published studies, news stories, and examples from the field that explore the intersection among waterway restoration and environmental justice, in the context of the interests of unhoused people. We argue that further work on the topic is necessary, and it should include both systematic investigations as well as design guidance material; this exploration represents the first step in outlining the direction of that work. Follow-on studies will center on clarifying the social dynamics in play, including identifying contested policy narratives, describing the regulatory context of the existing cases, definition(s) of what constitutes unhoused/homeless, and what impacts they have on decision-making. The future research we anticipate will develop information and propose strategies that can be used by practitioners including planners and landscape architects, in the process of organizing project work, to help advance environmental justice and human rights goals. Full article

(This article belongs to the Special Issue Healing Place and Planet: Conference on Landscape and Greenway Planning)

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1 pages, 118 KB

Open AccessCorrection

Correction: Yang, Z.; Tian, L. Ecological Waves at Tourist Attractions on the Qinghai-Tibet Plateau Promote Greenness of Surrounding Vegetation. Land 2025, 14, 159

by Zitao Yang and Li Tian

Land 2025, 14(10), 2047; https://doi.org/10.3390/land14102047 - 14 Oct 2025

Viewed by 41

Abstract

In the published publication [...] Full article

(This article belongs to the Special Issue The Mechanism of Land-Water Interaction and Management Strategies: Recent Discoveries and the Way Forward)

21 pages, 3555 KB

Open AccessArticle

Spatio-Temporal Evolution and Zonal Control of Non-Grain Cultivated Land in Major Grain Producing Areas: A Case Study of Henan Province

by Aman Fang, Ziyi Xing, Weiqiang Chen, Yuanqing Shi, Lingfei Shi, Xinwei Feng and Yuehong Ma

Land 2025, 14(10), 2046; https://doi.org/10.3390/land14102046 - 13 Oct 2025

Viewed by 142

Abstract

Ensuring food security amidst increasing non-grain utilization of cultivated land is a critical challenge in major grain-producing regions. This study analyzes the spatio-temporal evolution and driving mechanisms of non-grain cultivated land in Henan Province, China, from 2012 to 2023, using spatial autocorrelation, multiple [...] Read more.

Ensuring food security amidst increasing non-grain utilization of cultivated land is a critical challenge in major grain-producing regions. This study analyzes the spatio-temporal evolution and driving mechanisms of non-grain cultivated land in Henan Province, China, from 2012 to 2023, using spatial autocorrelation, multiple linear regression, geographically and temporally weighted regression model, and cluster analysis. Results show that the non-grain ratio exhibited a fluctuating yet overall increasing trend, from 27.47% in 2012 to 25.91% in 2017 and reaching 30.28% in 2023, with higher values in the northern and southwestern counties of the province. Spatial clustering patterns remained relatively stable, characterized by a “high–high clustering in the southwest and low–low clustering in the north,” which was further substantiated by significant Global Moran’s I values (0.362 in 2012 and 0.307 in 2023). Key drivers included per capita level of agricultural mechanization, labor force per unit of cultivated land area, output value per unit of cultivated land area, and per capita disposable income of rural residents. PCA and K-means clustering identified three zonal types: agricultural production support (45.10% of counties), agricultural production weakening (35.29% of counties), and economically location-guided (19.61% of counties). The findings underscore the need for differentiated policies—such as precision subsidies, land consolidation, and ecological farming practices. This study provides a scientific basis for zonal governance of non-grain cultivated land in grain-producing areas. Full article

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

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32 pages, 6336 KB

Open AccessArticle

A Spatiotemporal Analysis of Potential Demand for Urban Parks Using Long-Term Population Projections

by Daeho Kim, Yoonji Kim, Hyun Chan Sung and Seongwoo Jeon

Land 2025, 14(10), 2045; https://doi.org/10.3390/land14102045 - 13 Oct 2025

Viewed by 151

Abstract

In the Republic of Korea, the problems of low birth rate and population aging are accelerating population decline at the regional level, leading to the phenomena of local extinction and urban shrinkage. These phenomena, coupled with the projected nationwide population decline, pose a [...] Read more.

In the Republic of Korea, the problems of low birth rate and population aging are accelerating population decline at the regional level, leading to the phenomena of local extinction and urban shrinkage. These phenomena, coupled with the projected nationwide population decline, pose a fundamental threat to the sustainability of essential infrastructure such as urban parks. The conventional growth-oriented paradigm of urban planning has shown clear limitations in quantitatively forecasting future demand, constraining proactive management strategies for the era of population decline. To address this gap, this study develops a policy-decision-support framework that integrates long-term population projections, grid-based population data, the DEGURBA urban classification system—a global standard for delineating urban and rural areas— and network-based accessibility analysis. For the entire Republic of Korea, we (1) constructed a 1 km resolution time-series population dataset for 2022–2072; (2) applied DEGURBA to quantify transitions among urban, semi-urban, and rural types; and (3) assessed changes in potential user populations within the defined service catchments. The results indicate that while population concentration in the Seoul Capital Area persists, under the low-variant scenario, a projected average decline of 40% in potential user populations by 2072 will lead to significant functional changes, with 53.6% of municipalities nationwide transitioning to “semi-urban” or “rural” areas. This spatial shift is projected to decrease the proportion of urban parks located in “urban” areas from 83.3% to 75.0%, while the total potential user population is expected to plummet from approximately 44.4 million to 25.8 million, a 42.0% reduction. This study underscores the need for urban park policy to move beyond quantitative expansion and toward quality-oriented management based on selection and concentration. By uniquely integrating long-term demographic scenarios, the Degree of Urbanization (DEGURBA), and spatial accessibility analysis, this study provides a foundational scientific basis for forecasting future demand and supports the formulation of sustainable, data-driven strategies for urban park restructuring under conditions of demographic change. Full article

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

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13 pages, 1722 KB

Open AccessArticle

Interactions Between Soil Texture and Cover Crop Diversity Shape Carbon Dynamics and Aggregate Stability

by Vladimír Šimanský and Martin Lukac

Land 2025, 14(10), 2044; https://doi.org/10.3390/land14102044 - 13 Oct 2025

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Abstract

Increasing attention is being paid to the use of cover crops as a means of improving soil quality, particularly in relation to soil organic matter (SOM) accumulation and aggregate stability. This study evaluated the effects of soil texture, soil depth, and cover crop [...] Read more.

Increasing attention is being paid to the use of cover crops as a means of improving soil quality, particularly in relation to soil organic matter (SOM) accumulation and aggregate stability. This study evaluated the effects of soil texture, soil depth, and cover crop type on soil organic carbon (Corg), labile carbon (C_L), and soil structure under field conditions in western Slovakia. A field experiment compared two texturally distinct Phaeozem soils—silty clay loam and sandy loam —and two cover cropping strategies: pea (Pisum sativum L.) monoculture and a four-species mixture of flax (Linum usitatissimum L.), camelina (Camelina sativa L.), white mustard (Sinapis alba L.), and Italian millet (Setaria italica L.). Fine-textured soil accumulated up to 50% more Corg and 1.5 times more C_L than sandy soil, while aggregate stability was up to 90% higher. The surface layer (0–10 cm) contained more SOM, but the deeper layer (10–20 cm) showed greater aggregate stability. Pea cultivation increased total organic carbon, whereas the diverse mixture enhanced labile carbon content and promoted the formation of smaller yet more stable aggregates. Strong correlations between C_L and aggregate stability confirmed the key role of labile organic matter fractions in soil structural stabilisation. Overall, the results demonstrate that the interaction between soil texture and cover crop diversity critically shapes SOM dynamics and soil structure. Combining diverse cover crops with fine-textured soils provides an effective strategy to enhance soil quality, carbon sequestration, and long-term agricultural sustainability. Full article

(This article belongs to the Section Land, Soil and Water)

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22 pages, 2661 KB

Open AccessArticle

Population–Land–Industry–Facility System Coupling Coordination and Influencing Factors in Hebei Province

by Yichun Niu, Li Zhao, Jiaxi Xie, Haoyu Zhou, Junjie Zang and Chunxiu Zhao

Land 2025, 14(10), 2043; https://doi.org/10.3390/land14102043 - 13 Oct 2025

Viewed by 155

Abstract

Exploring the interactions and coupling effects in the Population–Land–Industry–Facility (PLIF) system can help maximize resource allocation and promote the synergistic development of systems. This study constructs an index system for the PLIF system in Hebei Province, employing coupling coordination degree and spatial autocorrelation [...] Read more.

Exploring the interactions and coupling effects in the Population–Land–Industry–Facility (PLIF) system can help maximize resource allocation and promote the synergistic development of systems. This study constructs an index system for the PLIF system in Hebei Province, employing coupling coordination degree and spatial autocorrelation methods to investigate the spatio-temporal evolution of the system’s coordination. Furthermore, grey relational analysis is employed to examine the key factors influencing the coordination degree of the system. The results show the following: (1) The development levels of each subsystem and the overall development level of the PLIF system in Hebei Province have generally increased, but the overall level remains relatively low. (2) The PLIF system in Hebei Province exhibits a pattern of “low in the north and high in the south, high in the east and low in the west”, with most counties in a barely coordinated state and a generally high degree of coupling. (3) The main factors affecting the coordinated development of the PLIF system include population density, the proportion of the tertiary industry, and the degree of non-agriculturalization of rural labor force. The research results of this paper provide a reference for promoting the coordinated development of population, land, industry, and facilities in Hebei Province and facilitating the sustainable development of the region. Full article

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38 pages, 14720 KB

Open AccessArticle

Ecological Comprehensive Efficiency and Driving Mechanisms of China’s Water–Energy–Food System and Climate Change System Based on the Carbon Nexus: Insights from the Integration of Network DEA and the Geographic Detector

by Fang-Rong Ren, Fang-Yi Sun, Xiao-Yan Liu and Hui-Lin Liu

Land 2025, 14(10), 2042; https://doi.org/10.3390/land14102042 - 13 Oct 2025

Viewed by 85

Abstract

As a major energy producer and consumer, China has witnessed rapid growth in carbon emissions, which are closely linked to changes in regional climate and the environment. Water, energy, and food (W-E-F) are the three most critical components of human production and daily [...] Read more.

As a major energy producer and consumer, China has witnessed rapid growth in carbon emissions, which are closely linked to changes in regional climate and the environment. Water, energy, and food (W-E-F) are the three most critical components of human production and daily life, and achieving the coordinated development of these three resources and connecting them with climate change through the carbon emissions generated during their utilization processes has become a key issue for realizing regional ecological sustainable development. This study constructs a dynamic two-stage network slack-based measure-data envelopment analysis (SBM-DEA) model, which integrates the water–energy–food (W-E-F) system with the climate change process to evaluate China’s comprehensive ecological efficiency from 2011 to 2022, and adopts the Dagum Gini coefficient decomposition, kernel density estimation, hierarchical clustering, and geographical detector model to analyze provincial panel data, thereby assessing efficiency patterns, regional differences, and driving mechanisms. The novelty and contributions of this study can be summarized in three aspects. First, it establishes a unified framework that incorporates the W-E-F nexus and climate change into a dynamic network SBM-DEA model, enabling a more systematic assessment of ecological efficiency. Second, it uncovers that interregional overlap effects and policy-driven factors are the dominant sources of spatial and temporal disparities in ecological efficiency. Third, it further quantifies the interactive effects among key driving factors using Geodetector, thus offering practical insights for regional coordination and policy design. The results show that China’s national ecological efficiency is at a medium level. Southern China has consistently maintained a leading position, while provinces in northwest and southwest China have remained relatively backward; the efficiency of the water–energy–food integration stage is relatively high, whereas the efficiency of the climate change stage is medium and exhibits significant temporal fluctuations. Interregional differences are the main source of efficiency gaps; ecological quality, environmental protection efforts, and population size are identified as the primary driving factors, and their interaction effects have intensified spatial heterogeneity. In addition, sub-indicator analysis reveals that the efficiency related to total wastewater, air pollutant emissions, and agricultural pollution shows good synergy, while the efficiency associated with sudden environmental change events is highly volatile and has weak correlations with other undesirable outputs. These findings deepen the understanding of the water–energy–food-climate system and provide policy implications for strengthening ecological governance and regional coordination. Full article

33 pages, 6537 KB

Open AccessArticle

Policy-Driven Urban Expansion and Land Use/Land Cover Change in Ewa, Honolulu (2002–2022): Remote Sensing and Machine Learning Analysis of Transit-Oriented Development Impacts

by Padmendra Prasad Shrestha, Asheshwor Man Shrestha and Chang-Yu Hong

Land 2025, 14(10), 2041; https://doi.org/10.3390/land14102041 - 13 Oct 2025

Viewed by 181

Abstract

While prior studies on LULC change in the Ewa region of O’ahu Hawai’i have explored the policy implications and the rapid infrastructure changes on land use, very few studies have attempted to fully integrate both of these changes in a comprehensive, long-term study [...] Read more.

While prior studies on LULC change in the Ewa region of O’ahu Hawai’i have explored the policy implications and the rapid infrastructure changes on land use, very few studies have attempted to fully integrate both of these changes in a comprehensive, long-term study of island geographies. Most of the past work has focused on general trends or short-term fluctuations, without considering the play of nuanced interactions between urbanization policies, transit-oriented development, and constraints of Hawai’i’s finite land resources. To fill these gaps, this study examines LULC changes in Ewa, Honolulu between 2002 and 2022, which emphasizes the impacts of strategic urban policies and infrastructure development, such as the Honolulu Skyline Rail Transit System. Using Landsat 7 satellite imagery and random forest machine learning classifier, in Google Earth Engine, LULC is classified into urban, forest, vegetation, barren, and water with classification accuracy of over 85%. The results highlight trends of significant urban growth especially after 2010, and highlight key issues of tension between housing demands and environmental sustainability in O’ahu. This study highlights the potential of integrated remote sensing and policy analysis for informing sustainable development in land-constrained island settings, and advocates for planning frameworks that more effectively balance growth, ecosystem stewardship, and community welfare. Full article

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26 pages, 16189 KB

Open AccessArticle

With Cats’ Eyes: Cartographic Methodology for an Analysis of Urban Security in the Central District of Madrid

by Alejandro García García, Elena Agudo Sierra, Juan Diego López Arquillo, Paula Aragón de Francisco, María Clara García Carrillo, Diego Naya Suárez and Telmo Zubiaurre Arrizabalaga

Land 2025, 14(10), 2040; https://doi.org/10.3390/land14102040 - 13 Oct 2025

Viewed by 159

Abstract

In the contemporary urban context, safety in public space presents profound inequalities linked to gender, especially in the night period. This research explores how the subjective perception of security in the central district of Madrid affects women’s mobility patterns and use of public [...] Read more.

In the contemporary urban context, safety in public space presents profound inequalities linked to gender, especially in the night period. This research explores how the subjective perception of security in the central district of Madrid affects women’s mobility patterns and use of public space. Through a mixed methodology, which combines spatial analysis with sensitive cartographies and collective mapping, it seeks to make visible the conditions of (in)security experienced in the city. The approach adopts a feminist and multi-scalar perspective, ranging from the object to the district scale. The analysis is structured around four layers: mobility, urban environment, green areas and night-time uses. Tools such as Geographic Information Systems were used for the treatment of objective data and qualitative techniques such as interviews and tours accompanied by a set of subjective perceptions. The results show the existence of multiple barriers that condition women’s access to and enjoyment of public space, revealing a discrepancy between what is planned and what is lived. The final considerations anticipate the possibility of replicating the methodology applied in urban planning, proposing future strategies to build safer, more inclusive and sensitive environments to the diversity of their inhabitants. Full article

(This article belongs to the Special Issue Advancing Sustainable Urban Development Through Spatial Analysis: Leveraging Digital Technologies and Geographic Data for Smart, Inclusive, and Resilient Cities)

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21 pages, 12783 KB

Open AccessArticle

Exploring the Multidimensional Visual Perception of Urban Riverfront Street Environments: A Framework Using Street View Images, Deep Learning and Eye-Tracking

by Xing Xiong, Yifan Wu, Miaomiao Ma, Shanrui Yang, Junxiang Zhang, Qinghai Zhang, Haiyue Ye and Yuanke Hu

Land 2025, 14(10), 2039; https://doi.org/10.3390/land14102039 - 13 Oct 2025

Viewed by 181

Abstract

Urban waterfront areas (UWAs), which are essential natural resources and highly perceived public areas in cities, play a crucial role in improving the quality of the urban environment. While numerous studies have delved into the visual perception of urban environments, little attention has [...] Read more.

Urban waterfront areas (UWAs), which are essential natural resources and highly perceived public areas in cities, play a crucial role in improving the quality of the urban environment. While numerous studies have delved into the visual perception of urban environments, little attention has been paid to understanding how the visual perception of urban riverfront streets (URSs) differs with various aspects within their unique spatial environment. This study took the Gusu District in Suzhou, China, as a case study, applying deep learning to street-view images to identify urban riverside landscape elements and evaluate their visual attention, aesthetic preference, and distinctiveness through eye-tracking technology and questionnaires. Subsequently, a multidimensional assessment was conducted to analyze how landscape elements influence visual perception in the urban riverfront street. This study concludes that (1) riverfront streets in the Gusu District present balanced visual attention, with high aesthetic preference but limited distinctiveness, and only a few roads in the ancient city score highly for distinctiveness. (2) Greenery, traditional-style buildings, water, and riverfronts positively impact visual perception, while buildings have a negative impact, and backgrounds such as the sky and roads exhibit minimal influence. This study validated the scientific accuracy, appropriateness, and precision of assessments of visual attention, aesthetics, and distinctiveness to quantitatively evaluate the multidimensional human perception of URSs. Full article

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27 pages, 6909 KB

Open AccessArticle

Comparative Analysis of Deep Learning and Traditional Methods for High-Resolution Cropland Extraction with Different Training Data Characteristics

by Dujuan Zhang, Xiufang Zhu, Yaozhong Pan, Hengliang Guo, Qiannan Li and Haitao Wei

Land 2025, 14(10), 2038; https://doi.org/10.3390/land14102038 - 13 Oct 2025

Viewed by 182

Abstract

High-resolution remote sensing (HRRS) imagery enables the extraction of cropland information with high levels of detail, especially when combined with the impressive performance of deep convolutional neural networks (DCNNs) in understanding these images. Comprehending the factors influencing DCNNs’ performance in HRRS cropland extraction [...] Read more.

High-resolution remote sensing (HRRS) imagery enables the extraction of cropland information with high levels of detail, especially when combined with the impressive performance of deep convolutional neural networks (DCNNs) in understanding these images. Comprehending the factors influencing DCNNs’ performance in HRRS cropland extraction is of considerable importance for practical agricultural monitoring applications. This study investigates the impact of classifier selection and different training data characteristics on the HRRS cropland classification outcomes. Specifically, Gaofen-1 composite images with 2 m spatial resolution are employed for HRRS cropland extraction, and two county-wide regions with distinct agricultural landscapes in Shandong Province, China, are selected as the study areas. The performance of two deep learning (DL) algorithms (UNet and DeepLabv3+) and a traditional classification algorithm, Object-Based Image Analysis with Random Forest (OBIA-RF), is compared. Additionally, the effects of different band combinations, crop growth stages, and class mislabeling on the classification accuracy are evaluated. The results demonstrated that the UNet and DeepLabv3+ models outperformed OBIA-RF in both simple and complex agricultural landscapes, and were insensitive to the changes in band combinations, indicating their ability to learn abstract features and contextual semantic information for HRRS cropland extraction. Moreover, compared with the DL models, OBIA-RF was more sensitive to changes in the temporal characteristics. The performance of all three models was unaffected when the mislabeling error ratio remained below 5%. Beyond this threshold, the performance of all models decreased, with UNet and DeepLabv3+ showing similar performance decline trends and OBIA-RF suffering a more drastic reduction. Furthermore, the DL models exhibited relatively low sensitivity to the patch size of sample blocks and data augmentation. These findings can facilitate the design of operational implementations for practical applications. Full article

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8 pages, 163 KB

Open AccessEditorial

Integrating Spatial Analysis and Regional Science to Guide Urban Planning (Editorial for Special Issue Reprint)

by Apostolos Lagarias, Poulicos Prastacos, Despoina Dimelli and Alexandra Delgado-Jiménez

Land 2025, 14(10), 2037; https://doi.org/10.3390/land14102037 - 13 Oct 2025

Viewed by 186

Abstract

Spatial analysis is a research paradigm that employs specialized techniques and models to analyze and model spatial data, focusing on the variation over space and helping to reveal hidden patterns and model relationships [...] Full article

(This article belongs to the Special Issue Integrating Spatial Analysis and Regional Science to Guide Urban Planning)

17 pages, 2045 KB

Open AccessFeature PaperArticle

Effects of Biochar-Based Fertilizer on Root Zeta Potential, Nutrient Leaching and Yield in an Intensive Protected Cropping System

by Kane Trubenbacher, Shahla Hosseini Bai, Lakmini Dissanayake, Negar Omidvar, Stephen Joseph and Michael B. Farrar

Land 2025, 14(10), 2036; https://doi.org/10.3390/land14102036 - 13 Oct 2025

Viewed by 283

Abstract

Rising global demand for food and fibre requires more efficient and sustainable fertilizer strategies. Biochar mineral complexes (BMC) are being developed for use as an organic alternative to conventional synthetic fertilizers, or to supplement conventional fertilizers applied at lower rates. Biochar can change [...] Read more.

Rising global demand for food and fibre requires more efficient and sustainable fertilizer strategies. Biochar mineral complexes (BMC) are being developed for use as an organic alternative to conventional synthetic fertilizers, or to supplement conventional fertilizers applied at lower rates. Biochar can change electrochemical properties such as zeta potential (ZP) that influence nutrient use efficiency. However, the impact of BMCs on the ZP of plant roots remains unknown. This study investigated the effects of BMC on root zeta potential, nutrient leaching, and yield in an intensive protected cropping system. A novel BMC was developed and tested in four treatments: synthetic fertilizer, organic fertilizer, BMC with half-rate organic fertilizer, and BMC alone. Organic fertilizer significantly increased negative root ZP compared with other treatments, largely due to higher concentrations of –COOH and –OH functional groups on the potting media. Treatments containing organic fertilizer also increased pH and cation exchange capacity (CEC), enhancing nutrient availability and retention relative to synthetic fertilizer. Yield was greatest with synthetic fertilizer; however, BMC combined with half-rate organic fertilizer achieved similar yields to full-rate organic fertilizer. This indicates that BMC co-applied with half-rate organic fertilizer should be considered by farmers to be a viable alternative to full-rate organic fertilizer regimes to reduce net inputs and risk of negative environmental impacts from over-fertilization. Full article

(This article belongs to the Topic Environmental Pollution in Modern Agriculture: Causes, Effect, and Control)

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32 pages, 8244 KB

Open AccessArticle

Towards Well-Being in Old Residential Areas: How Health-Promoting Environments Influence Resident Sentiment Within the 15-Minute Living Circle

by Jiaying Zhao, Yang Chen, Jiaping Liu and Pierluigi Salvadeo

Land 2025, 14(10), 2035; https://doi.org/10.3390/land14102035 - 12 Oct 2025

Viewed by 373

Abstract

Building healthy communities is crucial for creating healthy cities and improving residents’ well-being. Old residential areas, with their substantial stock and elevated health risks, require urgent environmental upgrades. However, the relationship between community health promotion factors and resident sentiment, a crucial indicator of [...] Read more.

Building healthy communities is crucial for creating healthy cities and improving residents’ well-being. Old residential areas, with their substantial stock and elevated health risks, require urgent environmental upgrades. However, the relationship between community health promotion factors and resident sentiment, a crucial indicator of subjective well-being, in old residential areas remains poorly understood. By integrating big data-based community health promotion factors and Weibo data within the 15-min living circle of old residential areas in Xi’an, we developed an XGBoost model and employed SHAP analyses to interpret predictive outcomes. Results show that healthy facilities were dominant influencing factors in old residential areas. Densities of parking, supermarkets, education, package stations, and scenic spots exhibit nonlinear relationships with positive sentiment, indicating clear threshold effects and saturation effects. Two dominant patterns were observed in interactions between dominant factors and their strongest interacting factors. Four environment–sentiment patterns were identified for targeted planning interventions. It is recommended that planners and policymakers account for density phases and synergistic combinations of the dominant factors to optimize community health within old residential areas. The findings offer empirical support and planning insights for fostering healthy, sentiment-sensitive retrofit in old residential areas within the 15-min living circle. Full article

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

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24 pages, 3187 KB

Open AccessArticle

Digital Transformation in Rural Hungary: Infrastructure, Skills and Uptake Across Regions

by Dániel Fróna and Dorina Fróna-Hadas

Land 2025, 14(10), 2034; https://doi.org/10.3390/land14102034 - 12 Oct 2025

Viewed by 145

Abstract

Rural digitalization in Hungary from 2010 to 2024 is examined, focusing on infrastructure, digital skills, and sectoral uptake. Using secondary data, an interrupted time-series model determines national household internet access, and a regional panel includes post-2020 slope terms. Nationally, uptake continued and accelerated [...] Read more.

Rural digitalization in Hungary from 2010 to 2024 is examined, focusing on infrastructure, digital skills, and sectoral uptake. Using secondary data, an interrupted time-series model determines national household internet access, and a regional panel includes post-2020 slope terms. Nationally, uptake continued and accelerated after 2020, while regional trajectories remained broadly parallel, indicating persistent yet narrowing territorial differences. Market indicators point to a capacity-heavy fixed network with county-level disparities, suggesting that affordability and competencies shape the remaining rural gaps. There is a need for place-based policies that jointly target last-mile infrastructure, affordability, and skills to convert access into practical use in rural economies. Full article

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

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15 pages, 4945 KB

Open AccessArticle

Divergent Urban Canopy Heat Island Responses to Heatwave Type over the Tibetan Plateau: A Case Study of Xining

by Guoxin Chen, Xiaofan Lu, Qiong Li, Siqi Zhang and Suonam Kealdrup Tysa

Land 2025, 14(10), 2033; https://doi.org/10.3390/land14102033 - 12 Oct 2025

Viewed by 246

Abstract

The escalating heatwave risks over the Tibetan Plateau (TP) highlight unresolved gaps in understanding multitype mechanisms and diurnal urban canopy heat island (UCHI) responses. Using Xining’s high-density observational network (2018–2023) and by employing comparative analysis (urban–rural, heatwave versus non-heatwave days) and composite analysis, [...] Read more.

The escalating heatwave risks over the Tibetan Plateau (TP) highlight unresolved gaps in understanding multitype mechanisms and diurnal urban canopy heat island (UCHI) responses. Using Xining’s high-density observational network (2018–2023) and by employing comparative analysis (urban–rural, heatwave versus non-heatwave days) and composite analysis, we found: During the record-breaking July 2022 heatwave across the TP, Xining reached an extreme UCHI peak (z-score: 3.0). Critically asymmetric UCHI responses as daytime heatwaves amplify mean intensity by 0.35 °C via extreme value shifts, whereas nighttime events suppress it by 0.31 °C. Crucially, heatwaves induce negligible daytime UCHI modulation but drive comparable magnitude nighttime UCHI intensification (during daytime events) and reduction (during nighttime events), demonstrating type-dependent and diurnally asymmetric urban thermal sensitivities. Heatwaves driven by distinct synoptic patterns; daytime events are controlled by an anomaly anticyclone (cloudless, dry conditions), while nighttime events occur under plateau-north anticyclones (cloudy, humid conditions). These patterns fundamentally reshape heatwave–UCHI interactions through divergent mechanisms: Daytime/nighttime heatwaves amplify/suppress nocturnal UCHI through enhanced/reduced urban heat storage and accelerated/inhibited rural radiative cooling. Our case study demonstrates that although heatwaves generally amplify nocturnal UCHI, in dry regions, their synoptic drivers significantly modify this nighttime synergy. The nocturnal UCHI during heatwave is not only driven by humidity effects but also modulated by cloud cover-regulated rural radiative cooling and urban thermal storage. These findings establish a mechanistic framework for heatwaves–UCHI interactions and provide actionable insights for heat-resilient planning in high-altitude arid cities. Full article

(This article belongs to the Special Issue Influence of Urbanization-Related Radical Land Modification on Urban Extreme Climate: 2nd Edition)

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