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29 pages, 24813 KB

Open AccessArticle

Prioritizing Ecological Restoration and Reuse Zoning for Mining Brownfields at a Whole-Area Spatial Scale Within a “One Health” Framework: A Case Study of Longhu Town, Jinjiang City

by Qiuyang Cai, Yu Zheng, Siren Lan, Qunyue Liu, Ruiyu Xia and Ruiming Zheng

Land 2026, 15(7), 1323; https://doi.org/10.3390/land15071323 - 22 Jul 2026

Viewed by 475

Abstract

As an important part of territorial ecological restoration, existing research on mine ecological restoration largely focuses on individual mine restoration projects from an engineering perspective or the identification of restoration priorities from a purely ecological viewpoint. There is little consideration of integrated decision-making [...] Read more.

As an important part of territorial ecological restoration, existing research on mine ecological restoration largely focuses on individual mine restoration projects from an engineering perspective or the identification of restoration priorities from a purely ecological viewpoint. There is little consideration of integrated decision-making for mine ecological restoration at a whole-area spatial scale, and a spatial prioritization framework that simultaneously integrates ecological, habitat, and health-support dimensions remains absent. This study introduces a One Health framework, taking 169 mining brownfields in Longhu Town, Jinjiang City, Fujian Province as the study objects. Based on a whole-area spatial scale, ArcGIS (10.8) spatial analysis was conducted to construct a three-dimensional evaluation framework of environment, species, and health support from the three dimensions of ecological sensitivity and landscape visual sensitivity, bird habitat suitability, and the spatial provision of health facilities. The Analytic Hierarchy Process (AHP) was then combined to identify ecological restoration priorities and reuse zones, further exploring strategic guidance for the ecological restoration and reuse of mining brownfields oriented toward a One Health framework at the whole-area spatial scale. The results show that the 169 mine brownfields are concentrated around stone processing areas. Among them, 21 sites are prioritized for environmental restoration, 67 for bird habitat suitability improvement, and 93 for enhancing health facility provision; these are ultimately classified into three comprehensive restoration zones. This study can provide decision support for the differentiated restoration, reuse zoning, and spatial governance of mine brownfields within a whole-area spatial planning system. Full article

(This article belongs to the Topic Biophilic Cities and Communities: Human-Environment Interaction and Sustainable Governance)

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31 pages, 4768 KB

Open AccessFeature PaperArticle

Contested Frontiers Within the Cocoa Socio-Biodiversity Economy: A Gradient Approach to LULC Transitions and Land Use Practices in the Brazilian Amazon

by Vincenzo Carbone, Pablo L. Cavanagh, Anna C. Zoeters, Majoi de Novaes Nascimento, Fabio de Castro and Arie C. Seijmonsbergen

Land 2026, 15(7), 1322; https://doi.org/10.3390/land15071322 - 22 Jul 2026

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Abstract

The Brazilian Amazon is a contested frontier, shaped by destructive and conservationist forces. Most forest clearing is driven by agro-extractivism, an agrarian pathway based on raw commodity production. The socio-biodiversity economy (SBE) has emerged in response, widely regarded as a transformative agrarian pathway [...] Read more.

The Brazilian Amazon is a contested frontier, shaped by destructive and conservationist forces. Most forest clearing is driven by agro-extractivism, an agrarian pathway based on raw commodity production. The socio-biodiversity economy (SBE) has emerged in response, widely regarded as a transformative agrarian pathway capable of reconciling environmental conservation and rural livelihoods. However, recent research suggests that, as socio-biodiversity products scale up, agro-extractivist dynamics can be reproduced within the SBE. We examine this tension in the cocoa frontier of the Transamazon, where cocoa is institutionally promoted as an SBE alternative. We conduct an exploratory, mixed-methods study combining a geospatial analysis of land use and land cover (LULC) change (2020–2025, random forest classification) with a qualitative analysis drawing on participatory mapping and 87 semi-structured interviews with farmers, cooperatives, buyers, and institutional actors. Using a gradient framework, we read LULC transitions and farmers’ land use practices along an agro-extractivism–SBE continuum. The cocoa frontier emerges as a hybrid geography. The landscape is predominantly stable but internally reorganizing: anthropogenic forest declines while full-sun monoculture expands over pasture, with intensification concentrated in peri-urban areas and restoration in remote ones. Land use practices form five recurring configurations, two firmly anchored at the socio-biodiversity or agro-extractivist poles and three whose alignment with the SBE depends on access to markets, knowledge, and institutions. We argue that the frontier contestation unfolds not only between distinct economies but within the cocoa economy itself, and we identify the policy areas relevant to sustaining SBE-oriented practices in the Transamazon. More broadly, this study suggests that the classification of Amazonian forest-based economies as inherent alternatives to agro-extractivism should be treated as an empirical question rather than an assumption. Full article

(This article belongs to the Special Issue Opportunities and Risks for Agriculture and the Environment at Landscape Scales)

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26 pages, 18167 KB

Open AccessArticle

Quantifying the Drivers of Vegetation Resilience Gradient Effects Across Hierarchical Administrative Borders: A Case Study of the Beijing–Tianjin–Hebei Region

by Lifu Zheng, Yunlu Zhang, Ruojing Li, Kaiping Wang, Siqi Wu, Tieyue Qiang and Luxuan Lei

Land 2026, 15(7), 1321; https://doi.org/10.3390/land15071321 - 22 Jul 2026

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Abstract

Understanding vegetation resilience gradient effects across hierarchical administrative borders is critical for cross-jurisdictional land management yet remains underexplored. This study integrates an AR(1) model with XGBoost-SHAP analysis to assess resilience and its drivers across provincial, municipal, and county borders in the Beijing–Tianjin–Hebei (BTH) [...] Read more.

Understanding vegetation resilience gradient effects across hierarchical administrative borders is critical for cross-jurisdictional land management yet remains underexplored. This study integrates an AR(1) model with XGBoost-SHAP analysis to assess resilience and its drivers across provincial, municipal, and county borders in the Beijing–Tianjin–Hebei (BTH) region using NDVI data (2000–2025). The results show that (1) vegetation resilience across hierarchical border belts experienced an initial decline followed by recovery. A notable shift in resilience optimality was observed from city borders in 2005 to provincial borders by 2020. Gradient effects were stronger in northern city borders. The stable-fluctuating type dominated, followed by peak and valley types. (2) Precipitation, tree age, and altitude suppress gradient formation. Conversely, cross-boundary economic disparity, nighttime light differences, and land use composition tend to be associated with amplified gradient effects in a hierarchical manner: cropland and built-up expansion intensify gradients at provincial borders but reduce them at city borders, suggesting a potential role of governance coordination. (3) Based on these findings, a tiered governance framework is suggested—northern high-gradient provincial and city borders are proposed as priority areas for intensive interventions, while county borders (where gradient effects are weakest) may benefit from moderate, low-intensity interventions focused on maintaining land use continuity. At the provincial level, stronger inter-provincial coordination—through cross-boundary ecological compensation and harmonized environmental standards—may help mitigate gradient effects. Collectively, this study provides insights for cross-jurisdictional land governance in the BTH region and other analogous urban agglomerations. Full article

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

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28 pages, 36054 KB

Open AccessArticle

A Methodological Triangulation of the Environmentally Sustainable Human Development Index (ESHDI) of the Tropical Montane Cloud Forest Area, Puebla, Mexico

by Carlos Rosano-Peña, Mario del Roble Pensado-Leglise, Patricia Guarnieri, Aurelio A. Bernal-Campos and Thiago Victorino

Land 2026, 15(7), 1320; https://doi.org/10.3390/land15071320 - 22 Jul 2026

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Abstract

This study analyses the Environmentally Sustainable Human Development Index (ESHDI) across 42 municipalities in Puebla, Mexico, which share the same predominant biome, in 2010 and 2020. The objective was to compare four methods for constructing synthetic indices—Geometric Mean (GM), Principal Component Analysis (PCA), [...] Read more.

This study analyses the Environmentally Sustainable Human Development Index (ESHDI) across 42 municipalities in Puebla, Mexico, which share the same predominant biome, in 2010 and 2020. The objective was to compare four methods for constructing synthetic indices—Geometric Mean (GM), Principal Component Analysis (PCA), and two variants of Data Envelopment Analysis (DEA-CCR and DEA-SBM)—to identify the approaches most consistent with the ESHDI’s multidimensional nature. Considering the dimensions of Health, Education, Income, and per capita CO₂ emissions, the robustness of the classifications was evaluated using Kendall’s W, Spearman’s rho, and Kendall’s tau coefficients. The results reveal statistical convergence among the methods, as well as relevant structural differences in the weighting schemes and the generated rankings. While MG, ACP, and DEA-SBM assigned relatively balanced weights to the dimensions and produced similar rankings, DEA-CCR concentrated weights on the best-performing dimensions of each municipality, allowing a single dimension to exert a disproportionate influence on the aggregate index and compromise its multidimensional balance. Among the methods evaluated, DEA-SBM stood out for its ability to combine conceptual consistency with benchmarking capacity. In addition to measuring environmentally sustainable human development, the method enables the identification of reference municipalities, the establishment of realistic performance targets, and the diagnosis of specific inefficiencies in each dimension, thereby supporting the formulation of more effective and territorially contextualised public policies. The evidence reinforces the theoretical and empirical relevance of incorporating environmental sustainability into human development metrics and demonstrates that methodological choices in aggregation significantly influence the evaluation of territorial performance. Full article

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

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30 pages, 443 KB

Open AccessArticle

Spatial Governance and Everyday Agency in Brazil’s Rural–Urban Transition: The Case of Piracicaba’s Open-Air Markets

by Luciano Mendes, Isabela Baldin and Carolina Abdalla

Land 2026, 15(7), 1319; https://doi.org/10.3390/land15071319 - 22 Jul 2026

Viewed by 523

Abstract

This study investigates how smallholder farmers and vendors in Piracicaba, Brazil, navigate the tensions between standardized spatial governance and heterogeneous livelihood strategies in the rural–urban transition. Based on 25 semi-structured interviews with participants in municipal open-air markets (varejões), we analyze how policies implemented [...] Read more.

This study investigates how smallholder farmers and vendors in Piracicaba, Brazil, navigate the tensions between standardized spatial governance and heterogeneous livelihood strategies in the rural–urban transition. Based on 25 semi-structured interviews with participants in municipal open-air markets (varejões), we analyze how policies implemented by the Municipal Secretariat of Agriculture and Food Supply (SEMA), including rigid price controls, mandatory MEI registration, and inflexible infrastructure rules, clash with the realities of organic, family-based, and mixed production systems. The findings reveal that SEMA’s one-size-fits-all approach fails to account for real production costs, quality differentiation, and informal cooperation, thereby penalizing innovation and marginalizing vulnerable producers. Rather than passive recipients, vendors actively resist and reshape governance through income diversification, informal cooperatives, direct sales, and ethical redefinitions of agricultural work. We argue that effective spatial governance must move beyond technical standardization and instead recognize productive heterogeneity and local agency as central to sustainable rural–urban transitions. This Brazilian case offers a critical counterpoint to top-down models and underscores the need for flexible, participatory, and context-sensitive policy design. Full article

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

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25 pages, 3547 KB

Open AccessArticle

Modeling Sustainability Trade-Offs in a High-Andean Rural Community: Pine Plantations, Livestock, and Food Systems in Patapallpa Alta (Cusco, Peru)

by Juan José Cadillo-Benalcazar, Pablito Marcelo López Serrano, Amilcar Quispe, María E. Holgado-Rojas, Janet Mamani, Hugo B. Ccopa Huayta, María A. Paucarmayta-Holgado, Richard R. Vargas-Tito and Richard Tito

Land 2026, 15(7), 1318; https://doi.org/10.3390/land15071318 - 22 Jul 2026

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Abstract

Rural development strategies in the Andes face persistent tensions between income generation, food provision, and the conservation of ecological functions. In Patapallpa Alta (Cusco, Peru), the expansion of pine plantations associated with mushroom production has created new economic opportunities but also tensions involving [...] Read more.

Rural development strategies in the Andes face persistent tensions between income generation, food provision, and the conservation of ecological functions. In Patapallpa Alta (Cusco, Peru), the expansion of pine plantations associated with mushroom production has created new economic opportunities but also tensions involving water availability, land-use, and labor organization. This study applies the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) approach to develop a model for evaluating these trade-offs in terms of viability, feasibility, and desirability. The analysis includes territorial, productive, nutritional, and biophysical dimensions to represent interdependencies among dietary needs, food provision, labor, land-use, and biophysical pressures. The results show that the community functions as an open metabolic system where social reproduction depends on both local production and external flows. Although the pine–mushroom subsystem generates income and is socially valued, it also reshapes relationships among land, water, and labor in ecosystems where grasslands perform essential hydrological functions. This model brings the underlying structural tensions that shape sustainability to the surface and provides a useful framework for supporting decision-making in complex rural territories. Full article

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38 pages, 21322 KB

Open AccessArticle

Assessing the Impact of Innovation-Oriented Urban Policy on Urban Ecological Resilience: Empirical Evidence from 271 Cities in China

by Junxi Li, Bei Peng, Xingwei Li, Chenlin Lan and Jie Cheng

Land 2026, 15(7), 1317; https://doi.org/10.3390/land15071317 - 21 Jul 2026

Viewed by 768

Abstract

Against accelerating urban expansion, climate risks, and green transition, fortifying urban ecological resilience (UER) has become central to global urban sustainability. However, there is as yet no systematic evidence to suggest how the National Innovative City Pilot Policy (NICPP) promotes green technology innovation [...] Read more.

Against accelerating urban expansion, climate risks, and green transition, fortifying urban ecological resilience (UER) has become central to global urban sustainability. However, there is as yet no systematic evidence to suggest how the National Innovative City Pilot Policy (NICPP) promotes green technology innovation (GTI) and strengthens UER. To address this gap, this paper builds upon the traditional resistance–adaptability–resilience (RAR) paradigm and its extension, the driving force–resistance–adaptability–resilience (DRAR) framework to formulate a comprehensive driving force–pressure–resistance–adaptability–resilience (DPRAR) assessment system. Moreover, this paper investigates a dataset of 271 cities in China spanning the period from 2006 to 2023. By treating the NICPP as a quasi-natural experiment, this paper integrates an entropy balancing technique into a staggered difference–in–differences (DID) model to identify its effect on UER. The results are outlined below. (1) From 2006 to 2023, UER across Chinese municipalities generally increased, though spatial imbalances persisted. (2) The NICPP enhanced urban UER, with effects characterized by time-lagged and cumulative patterns. (3) Both the quantity and quality structure of urban GTI served as channels through which the NICPP affected UER. (4) The NICPP effects are strongest in the central region, followed by those in the western and eastern regions, as well as in resource-dependent cities and cities with stricter environmental regulation. This research provides novel empirical perspectives linking innovation-driven development, GTI, and UER, with implications for NICPP optimization and UER enhancement in China. Full article

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

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22 pages, 9127 KB

Open AccessArticle

How Climate Shapes Cropland: The Potential Pathways Through Human Activities in Northeast China

by Haoran Xiong, Dandan Ren, Ying Yuan, Qingtao Ma and Sayidjakhon Khasanov

Land 2026, 15(7), 1316; https://doi.org/10.3390/land15071316 - 21 Jul 2026

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Abstract

Climate and human activity shape cropland dynamics, while their cascading interactions remain an intricate black box blocking mechanistic understanding of land system shifts. Taking Jilin Province as a case, we developed an integrated framework combining OPGD (optimal parameter geographic detector), SEM (structural equation [...] Read more.

Climate and human activity shape cropland dynamics, while their cascading interactions remain an intricate black box blocking mechanistic understanding of land system shifts. Taking Jilin Province as a case, we developed an integrated framework combining OPGD (optimal parameter geographic detector), SEM (structural equation modeling) and GWR (geographically weighted regression) to quantify multi-scale cascading mechanisms of 13 environmental factors and cropland. Cropland conversion showed distinct spatial disparities: western plains saw mainly grassland reclamation, central urban plains experienced cropland occupation by construction, and eastern mountain areas had forest-to-cropland expansion. Over 2010–2019, cropland decreased by 1.39% (1257.7 ha) for construction, compensated by conversions from 4.99% grassland (4518.8 ha) and 3.01% forestland (2720.2 ha). Climate dominated cropland variations through indirect human-mediated pathways, with path coefficients of 0.664 for Climate → Human and 0.571 for Human → Cropland; climate exerted direct driving effects on grass–cropland transition in western ecologically fragile plains. Greenhouse gases, evapotranspiration, humidity, temperature and leaf area index controlled overall cropland variations. Central and western croplands were dominated by topography, whereas precipitation, population and GDP determined eastern cropland dynamics. This framework differentiated direct and indirect driving pathways of cropland evolution, guiding policy formulation for regional grain security. Full article

(This article belongs to the Special Issue Feature Papers for "Land–Climate Interactions" Section: Integration of Remote Sensing and GIS)

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26 pages, 3470 KB

Open AccessArticle

Why Do Farmers Leave Land Idle? Unpacking the Role of Farmland Fragmentation and Mechanization Constraints in Farmland Abandonment Behavior

by Peng Cheng, Yuru Wang, Ke Liu, Xuesong Kong, Houtian Tang, Yu Cheng and Jinrun Chen

Land 2026, 15(7), 1315; https://doi.org/10.3390/land15071315 - 21 Jul 2026

Cited by 3 | Viewed by 531

Abstract

Under the dual pressures of increasing fragmentation of farmland and profound changes in the agricultural labor force, the problem of abandoned farmland in rural China has become increasingly prominent, posing a serious threat to food security. Previous studies have mainly focused on the [...] Read more.

Under the dual pressures of increasing fragmentation of farmland and profound changes in the agricultural labor force, the problem of abandoned farmland in rural China has become increasingly prominent, posing a serious threat to food security. Previous studies have mainly focused on the impact of socioeconomic factors on farmland abandonment behavior; however, there remains a lack of systematic investigations into the underlying mechanisms through which farmland fragmentation influences farmers’ land-use decisions. Therefore, this study applies behavioral theory to construct a “fragmentation–mechanization–abandonment” analytical framework to analyze the potential mechanisms of land-use decision-making. Using micro-level household survey data from multiple provinces across China, we conduct empirical tests through Probit models and Karlson Holm and Breen (KHB) mediation effect analysis. Our findings include: (1) Farmland fragmentation significantly increases the probability of farmland abandonment, which remains robust across multiple tests. (2) Farmland fragmentation indirectly influences abandonment behavior through the mediating variable of agricultural mechanization level, but this mechanism plays only a partial mediating role. (3) Heterogeneity tests indicate that the positive effect of farmland fragmentation is significantly stronger among households with low access to finance than among those with high access to finance. This influence is also stronger among households with high farmland accessibility. This study indicates that abandonment governance requires moving beyond a singular focus on land consolidation and shifting toward a synergistic approach that combines differentiated regional strategies with targeted support for smallholders. From a micro-mechanism perspective, this study provides empirical evidence for targeted implementation of land consolidation and livelihood support for smallholders, offering important policy implications for achieving agricultural modernization. Full article

(This article belongs to the Special Issue Agricultural Land Economics: Balancing Production, Conservation, and Sustainability)

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23 pages, 20589 KB

Open AccessArticle

“Jardin de la Rue” the Phenomenon of Urban Green Infrastructure: A Case Study of Street Vegetation in Bordeaux

by Jan Winkler

Land 2026, 15(7), 1314; https://doi.org/10.3390/land15071314 - 21 Jul 2026

Viewed by 416

Abstract

Current approaches to urban greenery often led to a certain uniformity of vegetation. The desire of residents to be able to grow plants according to their own preferences and to co-create the appearance of the surroundings of their houses therefore leads to the [...] Read more.

Current approaches to urban greenery often led to a certain uniformity of vegetation. The desire of residents to be able to grow plants according to their own preferences and to co-create the appearance of the surroundings of their houses therefore leads to the emergence of spontaneous initiatives. One of these phenomena is the narrow strips at the interface between the foundations of houses and the sidewalks of streets in continuous urban development, which are used for growing plants and are referred to as “Jardin de la Rue”. The assessment of street vegetation with “Jardin de la Rue” elements took place in the urban district of Saint-Genès, which is part of the city of Bordeaux in the Nouvelle-Aquitaine region in France. The description of the street vegetation with the “Jardin de la Rue” represents an important first step towards understanding the causes of their creation and the subsequent ecological and social interactions. The creation of these small green spaces is the result of the initiative of residents, and these areas are not part of the planned urban green space. Field surveys in selected streets took place in August–September in 2023, 2024 and 2025. Based on the analysis of the species composition, a total of 107 plant taxa were recorded in the streets. The most frequently recorded ornamental taxa include Lonicera japonica Thunb., Alcea rosea L. and Passiflora caerulea L. The most popular group of cultivated plants consists mainly of lianas, e.g., Akebia quinata (Thunb. ex Houtt.) Decne., Ipomoea purpurea (L.) Roth, Lonicera japonica Thunb., Parthenocissus tricuspidata (Siebold & Zucc.) Planch., Passiflora amethystina J.C.Mikan, Solanum laxum Spreng., Trachelospermum asiaticum (Siebold & Zucc.) Nakai, Trachelospermum jasminoides (Lindl.) Lem. and Wisteria sinensis (Sims) Sweet. The most frequently represented taxa belong mainly to the weed group, e.g., Amaranthus deflexus L., Taraxacum sect. Taraxacum F.H.Wigg., Paspalum dilatatum Poir. The vegetation of the “Jardin de la Rue” elements is a manifestation of the cultural function of plants. The free choice of cultivated taxa allows residents to express their preferences and relationship to the place. Respect for these spontaneous green spaces and their vegetation composition by the city administration is a manifestation of mutual cooperation and at the same time a means of strengthening the ties of residents to their place of residence. These elements may deserve greater consideration within contemporary approaches to construction, architecture and urban planning. Full article

(This article belongs to the Special Issue Sustainable Urbanscapes: The Role of Green Infrastructure on the Resilience of Ecosystem Services (Second Edition))

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21 pages, 11246 KB

Open AccessArticle

Green Exposure and Restorative Quality of Campus Public Spaces: A Nonlinear Multi-Dimensional Visual Analysis Using Computer Vision

by Haiyuan Quan, Xiwei Xu, Huanchun Huang, Zihan Gao, Wei Ding, Ning Qiu and Xinyu Han

Land 2026, 15(7), 1313; https://doi.org/10.3390/land15071313 - 21 Jul 2026

Viewed by 428

Abstract

Green exposure in public spaces plays a critical role in promoting mental health and well-being, especially for populations experiencing elevated psychological pressure in academically demanding environments such as university campuses. However, existing research remains largely limited to coarse-scale assessments, often overlooking the nuanced [...] Read more.

Green exposure in public spaces plays a critical role in promoting mental health and well-being, especially for populations experiencing elevated psychological pressure in academically demanding environments such as university campuses. However, existing research remains largely limited to coarse-scale assessments, often overlooking the nuanced and nonlinear interactions between visual environmental characteristics and restorative quality across diverse spatial typologies. Addressing this gap, this study proposes a fine-scale, data-driven framework that integrates computer vision (CV) with perception-based evaluations using Shandong Jianzhu University as a case study. A semantic segmentation model (Mask2Former) was employed to extract 14 visual environmental elements from 193 campus photographs, while 426 students provided 4260 image-based evaluations of Perceived Restorative Quality (PRQ). Ridge regression optimized through cross-validation was used to identify key environmental correlates of PRQ, K-means clustering was applied to classify Campus Restorative Space (CRS) typologies, and Generalized Propensity Score Matching (GPSM) was employed to examine nonlinear dose–response relationships between sensory dimensions and restorative quality. The results indicate that natural elements, particularly vegetation and water-related features, are generally associated with higher PRQ scores; however, restorative responses do not consistently follow linear patterns. Several sensory dimensions exhibited threshold effects and diminishing marginal returns, suggesting that restorative benefits depend on balanced environmental composition rather than the simple accumulation of green elements. Furthermore, three CRS typologies—Greenery-Dominant Spaces, Open Landscape Spaces, and Courtyard Spaces—demonstrated distinct restorative pathways, indicating that the effects of environmental characteristics vary across spatial contexts. These findings support a context-dependent understanding of restorative environments and highlight the importance of spatial typology, environmental composition, and nonlinear responses in shaping restorative experiences. The study proposes a transferable analytical framework for assessing campus restorative environments and offers practical implications for evidence-based campus planning and design. Full article

(This article belongs to the Special Issue Green Exposure, Public Space Usage, and Travel Behavior: Strategies for Building Inclusive Cities and Supporting Vulnerable Groups)

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18 pages, 10775 KB

Open AccessArticle

Soil Clustering Using Geophysical and Remote Sensing Data: Implications for Water Management Zones

by Lorenzo De Carlo, Antonietta Celeste Turturro and Mert Çetin Ekiz

Land 2026, 15(7), 1312; https://doi.org/10.3390/land15071312 - 21 Jul 2026

Viewed by 460

Abstract

Traditional soil management relies on “whole-field” averages, which leads to resource waste and environmental degradation under anthropogenic pressures. While combining electromagnetic induction (EMI) and remote sensing is known for digital soil mapping, current approaches lack a unified, automated framework to handle complex multi-source [...] Read more.

Traditional soil management relies on “whole-field” averages, which leads to resource waste and environmental degradation under anthropogenic pressures. While combining electromagnetic induction (EMI) and remote sensing is known for digital soil mapping, current approaches lack a unified, automated framework to handle complex multi-source data dependencies for local-scale precision irrigation. To overcome this limitation, this study introduces a novel integrated methodology that couples high-resolution geophysical datasets and remote/proximal sensing through an automated machine learning workflow, capturing dynamic soil–human interaction boundaries more precisely than traditional empirical overlays. The general methodology was tested in a vineyard plot within the Torre Guaceto Natural Reserve (Southern Italy). Spatial datasets from EMI and remote sensing were integrated. Crucially, the K-means clustering algorithm was deployed early in the workflow to optimize the fused datasets and classify the plot into homogeneous zone clusters. The machine learning approach successfully identified two distinct main soil clusters. The spatial boundaries of these zones were rigorously validated using in situ soil moisture data from capacitance sensors, showing a statistically significant variance in volumetric water content between the two zones. This study demonstrates that integrated machine learning workflows can accurately delineate precision agricultural zones without relying on high-cost exhaustive sampling. It is recommended that farmers and managers within sensitive nature reserves adopt this cluster-based Variable Rate Application (VRA) for water and fertilizers to optimize resource efficiency and prevent nutrient leaching into underlying aquifers. Full article

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

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29 pages, 814 KB

Open AccessArticle

Unlocking Urban Ecological Resilience: A Configurational Analysis Through the Lens of Risk Identification, Resource Mobilization, Institutional Adaptation, and Structural Carrying Capacity

by Man Chen, Ziang Ji and Xiaoyong Li

Land 2026, 15(7), 1311; https://doi.org/10.3390/land15071311 - 21 Jul 2026

Viewed by 459

Abstract

Urban ecological resilience is essential for mitigating environmental risks, supporting green urban transitions, and promoting sustainable development. However, existing studies have mainly explained urban ecological resilience through linear and single-factor approaches, paying insufficient attention to the configurational mechanisms through which technological, financial, institutional, [...] Read more.

Urban ecological resilience is essential for mitigating environmental risks, supporting green urban transitions, and promoting sustainable development. However, existing studies have mainly explained urban ecological resilience through linear and single-factor approaches, paying insufficient attention to the configurational mechanisms through which technological, financial, institutional, and structural conditions jointly shape resilience outcomes. Drawing on resilience theory, socio-ecological system theory, and synergetics, this study constructs a “risk identification–resource mobilization–institutional adaptation–structural carrying capacity” analytical framework. Using 249 prefecture-level cities in China as cases, we apply fuzzy-set qualitative comparative analysis (fsQCA) to examine how six antecedent conditions—FinTech, green finance, environmental regulation intensity, economic development, industrial structure, and urbanization—combine to generate high and non-high urban ecological resilience. The antecedent conditions are measured in 2021, while urban ecological resilience is measured in 2023 to capture the lagged effects of resilience-building conditions. The results show that no single condition constitutes a necessary condition for high urban ecological resilience, indicating that resilience is shaped by multi-condition conjunctions rather than isolated determinants. The sufficiency analysis identifies two pathways leading to high urban ecological resilience. Both pathways share FinTech, economic development, and urbanization as common foundational conditions, while green finance and industrial structure play complementary roles under different urban contexts. Specifically, the first pathway reflects a “risk identification–resource mobilization–structural carrying capacity” mechanism, whereas the second pathway reflects a “risk identification–structural carrying capacity” mechanism. In contrast, five configurations lead to non-high urban ecological resilience, demonstrating clear causal asymmetry. Non-high resilience is mainly associated with the joint absence of technological feedback, resource mobilization, and spatial carrying capacity, rather than being a simple reversal of the high-resilience pathways. These findings suggest that urban ecological resilience should be promoted through differentiated, combination-based strategies tailored to cities’ technological, financial, institutional, and structural endowments. Full article

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40 pages, 2735 KB

Open AccessArticle

From Spatial Siphoning to Green Spillovers: Dynamic Effects and Distance-Decay Boundaries of the Digital Economy on Green Land Use Efficiency

by Li Zhang, Kai Chen and Yang Zhang

Land 2026, 15(7), 1310; https://doi.org/10.3390/land15071310 - 21 Jul 2026

Viewed by 398

Abstract

Improving green land use efficiency is an important approach to reconciling urban development with resource and environmental constraints. Using panel data from 280 cities at the prefecture level and above in China from 2011 to 2024, this study employs a dynamic spatial Durbin [...] Read more.

Improving green land use efficiency is an important approach to reconciling urban development with resource and environmental constraints. Using panel data from 280 cities at the prefecture level and above in China from 2011 to 2024, this study employs a dynamic spatial Durbin model to examine the effects of the digital economy on green land use efficiency, focusing on temporal dynamics, spatial spillover effects, distance-decay boundaries, moderating mechanisms, and urban heterogeneity. The results show that the digital economy significantly improves local green land use efficiency. Its spatial externalities exhibit a pronounced dynamic transition from the spatial siphoning effect in the short term to the green spillover effect in the long term. The short-term spatial siphoning effect is mainly concentrated within approximately 200 km, whereas the long-term green spillover effect extends to approximately 250 km, indicating a clear distance-decay pattern. Green technological innovation and industrial upgrading mitigate short-term spatial siphoning and strengthen the long-term green spillover effect, whereas factor misallocation intensifies short-term spatial siphoning and weakens the long-term green spillover effect. The green-enabling effect of the digital economy is stronger in cities in eastern China, resource-based cities, high-tier cities, and cities with stricter environmental regulation. These findings underscore the importance of coordinating digital economy development with cross-regional green land governance, while strengthening regional absorptive capacity and improving factor allocation efficiency. Full article

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

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32 pages, 3288 KB

Open AccessArticle

Sustainability as a Key Outcome: Muisca-Inspired Life Choices in Ráquira, Colombia

by Jimena Hernández-Parra and Juan Antonio Senent-DeFrutos

Land 2026, 15(7), 1309; https://doi.org/10.3390/land15071309 - 21 Jul 2026

Viewed by 553

Abstract

The United Nations 2030 Agenda often employs universalist metrics that overlook situated territorial ontologies. This study analyzes the Reverdece Association in Ráquira, Colombia, where an evolving self-determined peasant-mestizo family has articulated a model of resilience rooted in a Muisca-inspired worldview. Utilizing Participatory Action [...] Read more.

The United Nations 2030 Agenda often employs universalist metrics that overlook situated territorial ontologies. This study analyzes the Reverdece Association in Ráquira, Colombia, where an evolving self-determined peasant-mestizo family has articulated a model of resilience rooted in a Muisca-inspired worldview. Utilizing Participatory Action Research (PAR) and qualitative modeling in ATLAS.ti 26, this research examines how community practices generate functional sustainability outcomes. The findings reveal that the association’s efficiency stems from a “Coherence Framework” that synchronizes Identity (Being), Social Agency (Doing), and an Economy of Rootedness (Having). Central to this operational logic is the community making resource management decisions based on direct, somatic interactions with the landscape—such as evaluating fiber quality or water cycles—rather than relying on abstract market signals. By intentionally prioritizing long-term permanence, the association demonstrates that ecological regeneration is a natural outcome of their daily practices. This study concludes that community-led initiatives are more successful in achieving global sustainability goals than top-down institutional interventions. By recognizing situated epistemologies as valid forms of knowledge, the research suggests that the most resilient approaches to sustainability emerge from a collective commitment to regenerate ecosystems and maintain a dignified life within the territory. This indicates that locally grounded practices can complement and, in some cases, surpass standardized global indicators. Full article

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

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26 pages, 25393 KB

Open AccessArticle

Asynchronous Evolution of Urbanisation and the Ecological Environment in Southeast Asia

by Hedong Wang, Ruyi Yang, Shuyang Liu, Chengfeng He, Yuya Liang, Zhuxia Wei, Bohan Zeng, Di Shi, Guojun Yu and Liangen Zeng

Land 2026, 15(7), 1308; https://doi.org/10.3390/land15071308 - 21 Jul 2026

Viewed by 631

Abstract

Accelerated urbanisation and associated land-use conversion are reshaping the composition and functions of terrestrial ecosystems globally. In Southeast Asia, ecological change is increasingly mediated not only by demographic urbanisation but also by urban expansion, peri-urban development, and the conversion of agricultural, coastal, and [...] Read more.

Accelerated urbanisation and associated land-use conversion are reshaping the composition and functions of terrestrial ecosystems globally. In Southeast Asia, ecological change is increasingly mediated not only by demographic urbanisation but also by urban expansion, peri-urban development, and the conversion of agricultural, coastal, and forest land into built-up surfaces. This study integrates multi-source geographical information from 2014 to 2024 to examine 351 provincial-level units in 11 Southeast Asian nations. To describe the spatial-material dimension of urbanisation and ecological conditions, two indices were created: the Composite Nighttime Light Index (CNLI), used as a proxy for urban expansion and built-up development intensity, and the Improved Remote Sensing Ecological Index (IRSEI), which is tailored to tropical coastal locations. The development of human-environment interactions was measured using the Coupling Coordination Degree (CCD) model. Pathways of synergy and trade-off were found using an incremental four-quadrant framework, and nonlinear causes of spatial differentiation were investigated using Spearman correlation and the Optimal Parameter-based Geographical Detector (OPGD). Uncertainty was addressed through data-quality masking, annual compositing, consistent index-construction rules, and cautious interpretation of CCD and driver results as relative provincial-scale patterns. The regional mean CCD rose from 0.250 to 0.314 during the decade, showing a slow improvement; nevertheless, most places still have low to moderate levels of coordination. There is clear pathway divergence, with 38.7% of locations enduring trade-offs where built-up development happens at the price of ecological quality and 58.4% of regions seeing synergistic improvement. The coupling pattern is primarily driven by built-up area expansion, with multiple factors jointly producing strong nonlinear enhancement effects. Climate conditions and forest disturbance further strengthen these effects. This study extends beyond single-country analyses by situating remote-sensing coupling results within land-use transition, peri-urbanisation, urban–rural linkage, and regional-governance perspectives. It provides quantitative evidence to support differentiated policy strategies in rapidly urbanising places. Full article

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26 pages, 70861 KB

Open AccessArticle

Forest Transition and Its Ecological and Environmental Effects in Hainan, China

by Longhui Lu, Yu Dai, Shuaiqi Chen and Huichun Ye

Land 2026, 15(7), 1307; https://doi.org/10.3390/land15071307 - 21 Jul 2026

Viewed by 397

Abstract

Forest transition is a defining feature of global terrestrial ecosystem change. Systematically identifying and quantitatively assessing its eco-environmental effects provides a critical scientific foundation for regional ecological conservation and territorial spatial governance. Here, we take the terrestrial area of Hainan Island from 1988 [...] Read more.

Forest transition is a defining feature of global terrestrial ecosystem change. Systematically identifying and quantitatively assessing its eco-environmental effects provides a critical scientific foundation for regional ecological conservation and territorial spatial governance. Here, we take the terrestrial area of Hainan Island from 1988 to 2020 as the study area. We examine the spatiotemporal heterogeneity of the eco-environmental effects of forest transition and decompose the associated contributions. The principal findings are as follows: The ERI displays a persistent concentric pattern of low values in the interior and high values in the periphery. High-ESV areas largely coincide with the concentrated distribution of natural forests in the central and southern parts of the island. The per-unit-area ESV of natural forests is significantly higher than that of plantations. GTWR results demonstrate that forest quantity, structure and quality all exert stable inhibitory effects on ecological risk. The structural factor exhibits the strongest effect and the greatest temporal stability. This study provides a quantitative basis for the refined management and conservation of the Hainan Tropical Rainforest National Park and for province-wide ecological restoration planning, and also offers a framework for assessing the eco-environmental effects of forest transition in tropical regions. Full article

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17 pages, 2338 KB

Open AccessArticle

Count-Based Trajectory Analysis Applied to Spatio-Temporal Larceny Incidence in Urban Environments

by Rodrigo Lopez-Farias, Rodrigo Tapia-McClung and Camilo Caudillo-Cos

Land 2026, 15(7), 1306; https://doi.org/10.3390/land15071306 - 21 Jul 2026

Viewed by 374

Abstract

Larceny is considered a high-impact crime in Mexico City because of its effect on public perceptions of safety. Understanding its spatial and temporal dynamics is therefore important for designing effective public safety policies. This study extends the Trajectory Analysis framework to examine the [...] Read more.

Larceny is considered a high-impact crime in Mexico City because of its effect on public perceptions of safety. Understanding its spatial and temporal dynamics is therefore important for designing effective public safety policies. This study extends the Trajectory Analysis framework to examine the spatio-temporal evolution of larceny in Mexico City from 2020 to 2024. The proposed approach incorporates Kendall’s Tau (

τ_{k}

) to quantify trend strength across trajectory types, including Gain, Loss, and alternation patterns, and introduces a multi-resolution analysis to identify and quantify spatial exchange patterns in crime distribution. Results indicate an overall decline in larceny across the city, but also reveal spatial exchanges, suggesting that reductions in some areas may reflect displacement rather than elimination. By capturing both crime reduction and redistribution patterns, the framework provides a more nuanced basis for data-driven public safety strategies. Full article

(This article belongs to the Special Issue Applications of Trajectory Analysis to Describe Changes in a Time Series of Maps)

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19 pages, 5799 KB

Open AccessFeature PaperArticle

Verifiable Nature Units (VNUs): A Scalable Outcome-Based Framework for Valorising Natural Capital

by Jeanette Greyvensteyn, Maryn van der Laarse, Matthias De Beenhouwer, Benjamin Leutner and Vincent N. Naude

Land 2026, 15(7), 1305; https://doi.org/10.3390/land15071305 - 21 Jul 2026

Viewed by 1601

Abstract

Global biodiversity loss undermines ecological integrity and natural capital, yet many biodiversity–finance mechanisms still reward activities rather than verified ecological outcomes, reducing accountability and investor confidence. We introduce Verifiable Nature Units (VNUs), a standardised, outcome-based framework that approximates annual change in ecological integrity [...] Read more.

Global biodiversity loss undermines ecological integrity and natural capital, yet many biodiversity–finance mechanisms still reward activities rather than verified ecological outcomes, reducing accountability and investor confidence. We introduce Verifiable Nature Units (VNUs), a standardised, outcome-based framework that approximates annual change in ecological integrity at 1 km² resolution. The framework combines an anthropogenic disturbance-based Habitat Intactness (HI) index, derived from remote sensing and spatial datasets, with an Indicator Species (IS) layer estimated through repeated on-site monitoring of selected indicator species across at least three functional guilds. Baselines, tolerance buffers, eligibility criteria, and independent verification requirements translate measured outcomes into investable units. In Majete Wildlife Reserve (711 km²), southern Malawi, HI remained consistently high (0.99) from 2018–2024, with localised declines linked to park infrastructure and extreme weather events. Occupancy analyses for six indicator species across four functional guilds showed high and stable park-level performance from 2021–2025, resulting in all 711 potential VNUs being eligible for issuance in 2024/5. The VNU is not an exhaustive measure of ecological integrity; it is a practical, auditable MRV approach for outcome-based biodiversity finance that can adapt as monitoring systems and ecological metrics mature. Full article

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

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27 pages, 7399 KB

Open AccessArticle

Identifying Key Drivers of Heavy Metal(loid)s Contamination in Farmland Soils Using Machine Learning with Source-Integrated Features

by Xiang Yue, Bin Li, Nannan Zhang, Jianjun Ma, Rongguang Shi, Yang Guan, Tiantian Ma, Hong Li, Junhua Ma, Xiangyu Liang and Cheng Ma

Land 2026, 15(7), 1304; https://doi.org/10.3390/land15071304 - 21 Jul 2026

Cited by 1 | Viewed by 480

Abstract

Accurate source identification is essential for the prevention and control of heavy metal(loid)s (HMs) contamination in farmland soils. Conventional source-apportionment approaches often rely on limited indicators and expert judgment, which can increase uncertainty in source interpretation. In this study, 800 topsoil samples collected [...] Read more.

Accurate source identification is essential for the prevention and control of heavy metal(loid)s (HMs) contamination in farmland soils. Conventional source-apportionment approaches often rely on limited indicators and expert judgment, which can increase uncertainty in source interpretation. In this study, 800 topsoil samples collected from farmland in Ningxia, together with 24 environmental and anthropogenic variables, were used to develop element-specific machine learning models for Cd, Cr, Hg, Pb, and As. Five algorithms, including random forest (RF), Extra Trees (ET), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and least absolute shrinkage and selection operator (LASSO-stacking), were compared, and Shapley additive explanations (SHAP) were used to interpret the variables statistically associated with the spatial variability of each metal. Positive matrix factorization (PMF) was further applied to identify potential source categories. Model performance varied among metals, indicating element-specific differences in predictability and controlling factors. SHAP analysis showed that precipitation, temperature, spatial coordinates (longitude/latitude), cropping intensity, and industrial-source fine particulate matter emissions were among the most important associated factors, although their relative importance differed across elements. PMF results suggested that 73.8% of Cd was associated with agricultural inputs, 87.6% of Hg with industrial atmospheric deposition, and 68.4% of Cr and 46.7% of As with natural sources, Pb showed relatively weak predictability, suggesting that its spatial variability may be influenced by unmeasured local or legacy inputs, while model-derived associations indicated possible links with spatial gradients, terrain-hydrological conditions, wind-related variables, and soil carrier properties. Overall, this study presents an integrated framework that combines machine learning-based associated-factor analysis with receptor-model source apportionment, providing a more nuanced understanding of HMs contamination in farmland soils and supporting targeted soil pollution prevention and control. Full article

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29 pages, 9815 KB

Open AccessArticle

Flood Susceptibility, Agricultural Land Vulnerability, and Landscape Structure Modeling Using GIS-Based Multicriteria Analysis in an Experimental Micro-Watershed

by Carmen Elena Maftei, Luminiţa L. Cojocariu and Loredana Copăcean

Land 2026, 15(7), 1303; https://doi.org/10.3390/land15071303 - 21 Jul 2026

Viewed by 454

Abstract

The aim of this study is to develop an integrated methodological framework for assessing flood susceptibility, agricultural land vulnerability, and landscape structure using Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP), thereby contributing to the integrated assessment of these components at [...] Read more.

The aim of this study is to develop an integrated methodological framework for assessing flood susceptibility, agricultural land vulnerability, and landscape structure using Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP), thereby contributing to the integrated assessment of these components at the scale of an experimental micro-watershed. The research was based on a 2.5 m resolution Digital Elevation Model (DEM) and detailed data obtained through field investigations. Flood susceptibility was modeled by integrating geomorphological, hydrological, pedological, and land-use factors. The results highlight the predominance of the moderate susceptibility class (64.53%), while the high and very high susceptibility classes account for 14.22% of the watershed area and are concentrated in the vicinity of the drainage network and in low-lying sectors. The assessment of land vulnerability revealed differences among land-use categories. Hayfields encompass the largest area exposed to high and very high flood susceptibility classes, whereas forested areas are predominantly associated with low and moderate susceptibility classes. The landscape structure analysis revealed very strong correlations between the exposed area and the landscape metrics used to characterize landscape structure. The proposed integrated methodological framework provides a transferable approach for the simultaneous assessment of flood susceptibility, agricultural land vulnerability, and landscape structure in micro-watersheds with similar characteristics. Full article

(This article belongs to the Special Issue GIS and Remote Sensing for Landscape Assessment and Monitoring)

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23 pages, 7651 KB

Open AccessArticle

Static–Dynamic Coupling of Landscape Ecological Risk and Ecosystem Service Value in an Arid Urban Agglomeration: Evidence from the Northern Slope of the Tianshan Mountains

by Jingjing Tian, Wenbin Deng and Qinghu Ba

Land 2026, 15(7), 1302; https://doi.org/10.3390/land15071302 - 20 Jul 2026

Viewed by 333

Abstract

Land-use change in arid urban agglomerations reshapes landscape ecological risk (LER) and ecosystem service value (ESV), yet few studies jointly diagnose their current coupling state, temporal trajectory, and future scenario response. Focusing on the urban agglomeration on the northern slope of the Tianshan [...] Read more.

Land-use change in arid urban agglomerations reshapes landscape ecological risk (LER) and ecosystem service value (ESV), yet few studies jointly diagnose their current coupling state, temporal trajectory, and future scenario response. Focusing on the urban agglomeration on the northern slope of the Tianshan Mountains, we integrated land-use data for 2000, 2010, and 2020 with LER assessment, ESV estimation, static–dynamic coupling zoning, and intPLUS-based 2030 scenario simulation. From 2000 to 2020, cropland and construction land expanded by 46.43% and 107.84%, whereas forest and water bodies declined by 49.76% and 47.64%. LER was dominated by low- and medium-low-risk classes, although medium-high-risk areas expanded locally. Total ESV declined from 512.16 to 429.97 billion CNY, with continued contraction of medium-high- and high-ESV zones. In 2020, potential enhancement zones (PEZs) dominated the integrated management pattern, accounting for 43.64% of the study area. By 2030, static zoning changed only slightly, whereas dynamic and integrated zoning showed clear scenario sensitivity: PEZs accounted for 40.55% under the natural development scenario, while priority governance zones reached 49.06% and 49.26% under economic development and ecological protection scenarios. By treating LER as risk pressure and ESV as service-supply capacity, this framework links static risk–service matching, dynamic trajectory diagnosis, and future scenario response, thereby supporting ecological zoning in arid urban agglomerations. Full article

(This article belongs to the Special Issue Land Use Transition and Its Economic, Ecological, and Environmental Effects)

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29 pages, 14208 KB

Open AccessArticle

Nonlinear Thresholds of Multifunctional Blue–Green Infrastructure: Balancing Urban Cooling, Habitat Quality, and Green Equity in High-Density Shenzhen

by Yihai Chen, Senhong Cai, Jintao Xu and Kaida Chen

Land 2026, 15(7), 1301; https://doi.org/10.3390/land15071301 - 20 Jul 2026

Viewed by 506

Abstract

Climate adaptation in high-density cities requires equitable access to cooling and habitat benefits from blue–green infrastructure (BGI). However, the critical thresholds where human activity overwhelms these services remain unknown. Taking Shenzhen as a case study, we quantified habitat quality using the InVEST model [...] Read more.

Climate adaptation in high-density cities requires equitable access to cooling and habitat benefits from blue–green infrastructure (BGI). However, the critical thresholds where human activity overwhelms these services remain unknown. Taking Shenzhen as a case study, we quantified habitat quality using the InVEST model and divided the urban landscape into low-, medium-, and high-quality zones. After screening significant drivers via multiple linear regression, we compared six machine learning algorithms and selected XGBoost (for low- and medium-quality zones) and LightGBM (for high-quality zones) with Optuna-tuned hyperparameters, then applied SHAP dependence analysis to identify nonlinear, threshold-driven responses. We identify a systemic thermal threshold of 23.7 °C. Above this temperature, BGI cooling efficiency decouples from habitat quality. We also quantify actionable intervention windows. Low-quality habitats—dominated by dense residential areas—collapse when building density exceeds 0.7 or road density exceeds 0.009. Medium-quality habitats offer a balance window (core area > 2844 m², building density < 0.361) that enables incidental nature contact during daily travel. High-quality refugia require a core area > 8600 m² with near-zero disturbance. These thresholds expose a stark green inequity: socioeconomically vulnerable groups in low-quality zones are systematically disconnected from cooling services. We translate these findings into a tiered spatial intervention framework—restoration, accessibility enhancement, and strict protection—to advance climate-resilient and socially equitable urban planning. Full article

(This article belongs to the Special Issue Urban Green Spaces as Multi-Functional Infrastructure: Integrating Climate Resilience, Environmental Health and Social Equity)

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41 pages, 30023 KB

Open AccessArticle

A Hybrid Ecological Typology Proposal Based on Structural and Functional Connectivity for the Büyükçekmece Lake Basin: An Integrated Decision Support Framework

by Tülay Erbesler Ayaşlıgil and Dana Aleıt

Land 2026, 15(7), 1300; https://doi.org/10.3390/land15071300 - 20 Jul 2026

Viewed by 462

Abstract

Anthropogenic pressures increasingly threaten ecological connectivity and basin-scale ecological sustainability in peri-urban landscapes. This study proposes a Hybrid Ecological Typology framework for the Büyükçekmece Lake Basin (Istanbul, Türkiye), integrating Morphological Spatial Pattern Analysis (MSPA), Analytic Hierarchy Process (AHP), and Minimum Cumulative Resistance (MCR) [...] Read more.

Anthropogenic pressures increasingly threaten ecological connectivity and basin-scale ecological sustainability in peri-urban landscapes. This study proposes a Hybrid Ecological Typology framework for the Büyükçekmece Lake Basin (Istanbul, Türkiye), integrating Morphological Spatial Pattern Analysis (MSPA), Analytic Hierarchy Process (AHP), and Minimum Cumulative Resistance (MCR) analysis within a unified spatial decision-support system. The framework is applied to a 67,627.06 ha basin area, including a 25,976.99 ha terrestrial focus area. The results indicate a structurally heterogeneous landscape dominated by interior habitat zones (85.94%) distributed across 93 core patches. Despite this dominance, ecological connectivity is maintained through a highly fragmented network of 484 landscape elements, where limited bridge (0.08%) and branch (0.62%) structures highlight structural vulnerability. Edge-dominated zones (12.87%) further reflect strong anthropogenic fragmentation pressures. Connectivity analysis identifies 10 key habitat patches with dPC (Probability of Connectivity index) values exceeding 5% and 12 strategic ecological corridors supporting basin-scale ecological flows. The proposed hybrid typology delineates five functional planning categories: conservation areas (22.72%), ecological corridors (1.91%), restoration areas (1.63%), sustainable use areas (0.51%), and controlled development areas (8.11%). Although high-quality habitat cores dominate the basin, ecological connectivity remains spatially constrained, with bottleneck zones (0.89%) concentrated along transportation corridors that significantly reduce landscape permeability. Overall, the findings demonstrate that basin-scale ecological sustainability in peri-urban environments is governed not only by habitat quantity but also by the interaction between spatial configuration and resistance structures. The framework provides a transferable decision-support tool that bridges landscape ecology theory with spatial planning practice for basin management and ecological network design. Full article

(This article belongs to the Special Issue Linking Ecological Networks and Ecosystem Service Flow: Toward Regional Ecological Conservation and Sustainability)

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24 pages, 3305 KB

Open AccessArticle

Evolution of Land Use Suitability and Adaptation Strategies of the Agro-Pastoral Transitional Zone in Northern China Under Multiple Climate Change Scenarios

by Kaige Wang, Yan Xu, Fengrong Zhang and Zengqiang Duan

Land 2026, 15(7), 1299; https://doi.org/10.3390/land15071299 - 20 Jul 2026

Viewed by 387

Abstract

The Agro-Pastoral Transitional Zone in northern China is a typical ecologically fragile area highly sensitive to climate change. Understanding how future climate change will affect the suitability of agricultural and pastoral land use in this region is a critical scientific issue for both [...] Read more.

The Agro-Pastoral Transitional Zone in northern China is a typical ecologically fragile area highly sensitive to climate change. Understanding how future climate change will affect the suitability of agricultural and pastoral land use in this region is a critical scientific issue for both climate change research and regional sustainable development. This study integrates multi-scenario climate projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) with a land use suitability evaluation framework. Three Shared Socioeconomic Pathways (SSPs) are employed, driven by three Integrated Assessment Models (IAMs): IMAGE (SSP1-2.6, low emission), MESSAGE (SSP2-4.5, moderate emission), and REMIND-MAGPIE (SSP5-8.5, high emission). Future climate variables (annual precipitation and accumulated temperature ≥ 10 °C) are statistically downscaled to 1 km resolution for the years 2030, 2050, and 2100. Using a restrictive factor evaluation method that incorporates climatic, topographic, and edaphic indicators, we assess the evolution of land use suitability for both agriculture and livestock farming under each scenario. The results reveal that under moderate- and high-emission scenarios, thermal conditions gradually improve across the study area, particularly in the central and eastern parts, leading to enhanced natural suitability for agricultural and pastoral production. However, precipitation shows no consistent trend of increase or decrease. The moderate emission scenario (SSP2-4.5) yields the most balanced improvement in suitability, with the proportion of unsuitable agricultural land decreasing from 84.5% in 2030 to 37.4% in 2100, and unsuitable pastoral land decreasing from 53.1% to 13.6%. In contrast, the low-emission scenario (SSP1-2.6) results in a sharp contraction of suitable areas by 2100 due to concurrent warming and drying. These findings suggest that climate warming may benefit mid-to-high-latitude agro-pastoral transition zones under moderate emission pathways, but the benefits are spatially heterogeneous and contingent on precipitation stability. This study provides a scientific basis for regional land use planning and climate adaptation strategies. Full article

(This article belongs to the Special Issue Assessment of Spatial and Temporal Landscape Patterns Under Land Use Change (2nd Edition))

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23 pages, 34806 KB

Open AccessArticle

Mapping Landslide-Affected Land Surfaces in Complex Mountainous Landscapes Using a Twin-Path Multi-Scale Deep Learning Network

by Heming Yang, Wenhui Liu and Yabin Liu

Land 2026, 15(7), 1298; https://doi.org/10.3390/land15071298 - 20 Jul 2026

Viewed by 399

Abstract

Accurate mapping of landslide-affected land surfaces from very-high-resolution optical imagery is essential for mountainous land monitoring and hazard-related land management, yet it remains difficult in complex terrain because landslide bodies are fragmented, elongated, shadowed, and easily confused with bare soil, terraces, roads, and [...] Read more.

Accurate mapping of landslide-affected land surfaces from very-high-resolution optical imagery is essential for mountainous land monitoring and hazard-related land management, yet it remains difficult in complex terrain because landslide bodies are fragmented, elongated, shadowed, and easily confused with bare soil, terraces, roads, and erosion features. This study presents TM-Net as a task-oriented decoder-centric architecture for landslide-affected land surface mapping. The Inception Token Mixer is adopted from InceptionNeXt as an encoder-side component, whereas TM-Block is newly designed as a decoder-side twin-path refinement module for boundary recovery, slender target preservation, and complex-background suppression. On the fused public benchmark, TM-Net achieved the highest IoU (73.56%) and F1 (84.76%) under the identical evaluation protocol. On XBLD, TM-Net achieved the highest IoU (44.94%) and F1 (62.01%). These results indicate that TM-Net provides a favorable balance between missed detections and false-positive predictions for mapping visually identifiable landslide-affected land surfaces in heterogeneous mountainous landscapes. Full article

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21 pages, 8635 KB

Open AccessArticle

Assessing Public Experience of Waterfronts and Its Coupling with Urban Vitality: Evidence from Shanghai, China

by Xiangjun Lin, Lingge Zhai, Yaoyi Liu, Kgosietsile Velempini and Lingzhi Deng

Land 2026, 15(7), 1297; https://doi.org/10.3390/land15071297 - 19 Jul 2026

Viewed by 535

Abstract

Urban waterfronts are important components of urban blue-green infrastructure, supporting ecological functions and public activities. However, existing assessments often examine waterfronts from separate perspectives, limiting an integrated understanding of waterfront experience. Building upon existing research on waterfront environments, this study develops an integrated [...] Read more.

Urban waterfronts are important components of urban blue-green infrastructure, supporting ecological functions and public activities. However, existing assessments often examine waterfronts from separate perspectives, limiting an integrated understanding of waterfront experience. Building upon existing research on waterfront environments, this study develops an integrated socio-ecological framework that incorporates multiple environmental and spatial attributes to assess the Public Experience of Waterfronts (PEW) across four dimensions: amenity, comfort, experiential diversity, and access equity. By applying this framework to river segments in central Shanghai, the study examines spatial variations in PEW and its spatial coordination with surrounding urban vitality within 15 min living circles. Results reveal clear differences across river groups and spatial locations. Large rivers generally exhibit higher PEW levels, while medium and small rivers show relatively lower performance. High PEW areas are mainly concentrated along major waterfront corridors, whereas urban vitality is stronger in inner urban areas and declines outward. The coordination between PEW and urban vitality follows similar spatial patterns, with large rivers showing higher coordination levels and smaller rivers more frequently experiencing spatial mismatches. These findings highlight the importance of integrated assessment of waterfront qualities and surrounding urban contexts, providing practical insights for differentiated waterfront planning and sustainable urban development. Full article

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28 pages, 10266 KB

Open AccessArticle

A Spatial Mismatch Analysis of Blue–Green–Gray Infrastructure for Urban Cooling: Linking Supply, Thermal Pressure, and Heat-Sensitive Demand

by Binbin Peng and Victoria Chanse

Land 2026, 15(7), 1296; https://doi.org/10.3390/land15071296 - 19 Jul 2026

Viewed by 394

Abstract

Urban green spaces are increasingly recognized as cooling infrastructure for climate resilience, environmental health, and spatial equity. However, their planning value depends not only on where green spaces are located but also on whether cooling supply is translated into lower thermal pressure and [...] Read more.

Urban green spaces are increasingly recognized as cooling infrastructure for climate resilience, environmental health, and spatial equity. However, their planning value depends not only on where green spaces are located but also on whether cooling supply is translated into lower thermal pressure and aligned with heat-sensitive demand. This study examines blue–green–gray infrastructure cooling supply, thermal regulation, human-relevant thermal pressure, and supply–demand mismatch across 1385 census tracts in Maryland, USA. An Infrastructure Cooling Supply Index (ICSI) was constructed from green, blue, and gray infrastructure components and evaluated against maximum land surface temperature (LSTmax), Heat Index, extreme heat days, and a Human-Relevant Thermal Pressure Index (HTPI) integrating ambient heat intensity and recurrent extreme heat exposure. Explainable machine learning was used to identify the relative contributions of individual infrastructure components, and cooling supply was compared with socially differentiated heat-sensitive demand. The results show that higher ICSI is significantly associated with lower LSTmax, Heat Index, and HTPI. The association was strongest for surface thermal conditions, remained significant for Heat Index and integrated human-relevant thermal pressure, and was comparatively weaker for recurrent extreme heat days, indicating that infrastructure cooling supply affects thermal outcomes through distinct pathways. Cooling supply was also spatially uneven, with stronger provision generally associated with greater vegetation and tree-canopy coverage, higher park provision, larger water-area proportions, and lower gray-infrastructure pressure. Explainable GeoAI results identify impervious cover, tree canopy, water-area proportion, road density, and park provision as the principal contributors to tract-level thermal pressure. The mismatch analysis identifies 433 census tracts, or 31.3% of all Maryland tracts, as low-supply–high-demand priority areas. These tracts reveal substantial spatial convergence among elevated heat-sensitive demand, insufficient cooling infrastructure, and persistent thermal pressure. This study provides a tract-level approach for targeting cooling interventions where thermal pressure, vulnerability, and infrastructure deficits converge. Full article

(This article belongs to the Special Issue Urban Green Spaces as Multi-Functional Infrastructure: Integrating Climate Resilience, Environmental Health and Social Equity)

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31 pages, 10773 KB

Open AccessArticle

Spatiotemporal Dynamics and Associated Factors of New Urbanization Efficiency in Chinese Cities Under a Green Development Orientation: An Interpretable Machine Learning Approach

by Li Chen, Wei Yu, Zhiding Hu and Siqi Gao

Land 2026, 15(7), 1295; https://doi.org/10.3390/land15071295 - 19 Jul 2026

Viewed by 447

Abstract

Rapid urbanization presents a fundamental challenge to global sustainable development, as urban expansion increasingly conflicts with resource constraints, ecological carrying capacity, and carbon emission mandates. Serving as a highly spatially heterogeneous laboratory, China offers a critical context for embedding green development into urban [...] Read more.

Rapid urbanization presents a fundamental challenge to global sustainable development, as urban expansion increasingly conflicts with resource constraints, ecological carrying capacity, and carbon emission mandates. Serving as a highly spatially heterogeneous laboratory, China offers a critical context for embedding green development into urban efficiency assessments. This study reconceptualizes new urbanization efficiency (NUE) through a multidimensional framework encompassing resource inputs, coordinated development processes, and sustainable outcomes. Using a panel of 281 prefecture-level cities, we evaluated NUE via a remote-sensing-constrained Super-SBM model, utilizing LISA time paths and an interpretable spatial machine learning framework (GWR-XGBoost-SHAP) to unpack its spatiotemporal dynamics. Key findings indicate: (1) China’s NUE exhibited a fluctuating upward trajectory, transitioning from an east-high/west-low to a south-high/north-low spatial pattern. (2) Spatiotemporal analysis revealed strong spatial inertia and profound path dependency in North China, characterizing it as a persistent low-value basin, whereas southeastern coastal cities demonstrated dynamic, path-breaking trajectories. (3) While green development intensity, industrial upgrading, and technological innovation emerged as primary drivers, they operate through complex nonlinear mechanisms. Specifically, green development and innovation exhibit threshold-triggered synergies, population agglomeration acts as a nonlinear amplifier, and external openness presents context-dependent negative interactions. These findings refine NUE measurement methodologies and provide a transferable analytical framework to inform differentiated, place-based urbanization policies for regions navigating the friction between urban growth and ecological limits. Full article

(This article belongs to the Special Issue The Dynamics of Urbanization: Challenges and Solutions in Land Development and Regional Planning)

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16 pages, 8724 KB

Open AccessArticle

Spatial Variation of Zooplankton Diversity and Taxonomic Group Responses in the Nanming River, Guiyang: Coupling Effects of Urbanization Disturbance and Multiple Environmental Factors

by Lifen Du, Qiuhua Li, Haiquan Yang and Long He

Land 2026, 15(7), 1294; https://doi.org/10.3390/land15071294 - 19 Jul 2026

Viewed by 312

Abstract

This study investigated the effects of urbanization on zooplankton communities in the Nanming River, a typical karst urban river in Southwest China. Thirty-three sampling sites were set along an urbanization gradient: urban, suburban, and exurban areas. We identified 33 zooplankton species, with rotifers [...] Read more.

This study investigated the effects of urbanization on zooplankton communities in the Nanming River, a typical karst urban river in Southwest China. Thirty-three sampling sites were set along an urbanization gradient: urban, suburban, and exurban areas. We identified 33 zooplankton species, with rotifers dominating (84.62%). Zooplankton abundance and diversity were significantly higher in the exurban area, showing a negative correlation with urbanization intensity. Lepadella ovalis and Monostyla angulata were dominant, while Lecane cornuta was exclusive to the exurban zone. Gradient Boosting Models (GBMs) and Structural Equation Modeling (SEM) indicated that Cu, Zn, TN, and NH3-N were key drivers, and urbanization acted via heavy metal pollution and nutrient regulation. Rotifers showed strong urbanization adaptability, while copepods were most sensitive. Controlling nitrogen and heavy metals is critical for protecting karst urban river ecosystems. Full article

(This article belongs to the Section Land, Biodiversity, and Human Wellbeing)

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Land, Volume 15, Issue 7 (July 2026) – 218 articles

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