Land

14 pages, 2320 KiB

Open AccessArticle

Differentiated Microbial Strategies in Carbon Metabolic Processes Responding to Salt Stress in Cold–Arid Wetlands

by Yongman Wang, Mingqi Wang, Tiezheng Wu, Jialin Zhao, Junyi Li, Hongliang Xie, Lixin Wang and Linhui Wu

Land 2025, 14(8), 1607; https://doi.org/10.3390/land14081607 - 7 Aug 2025

Abstract

With the rising concerns about climate change and continuous increase in the salinity of soil, it is essential to understand the C-cycling functioning of saline soil to better predict the ecological functions and health of soil. Microbes play critical roles in C-cycling. However, [...] Read more.

With the rising concerns about climate change and continuous increase in the salinity of soil, it is essential to understand the C-cycling functioning of saline soil to better predict the ecological functions and health of soil. Microbes play critical roles in C-cycling. However, limited research has been conducted to understand the impact of soil salinity on the microbial functional genes involved in C-cycling. In this study, effects of varying soil salinity levels in wetlands on the C-cycling functions and diversity of soil microbes were investigated by metagenomic sequencing. The results showed a higher relative abundance of genes related to decomposition of easily degradable organic C at low salinity. On the other hand, higher abundance of genes participating in the decomposition of recalcitrant organic C were observed at high salinity. These findings indicate distinct metabolic bias of soil microbes based on the salinity levels. Proteobacteria and Actinobacteria were dominant in soils with low to medium salinity levels, while Bacteroidetes phyla was prominent in highly saline soils. Furthermore, partial least squares path modeling (PLS-PM) identified electrical conductivity, total nitrogen, and total phosphorus as key regulators of C-cycling gene expression. Overall, the present study highlights the intricate connections between salinity, microbial attributes, and carbon metabolism in soil, suggesting that the soil microbes adapt to saline stress through divergent eco-adaptations. The findings of this study highlight the significance of exploring these microbial interactions for effective management and conservation of saline wetlands. Full article

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22 pages, 2484 KiB

Open AccessArticle

Urban Land Revenue and Common Prosperity: An Urban Differential Rent Perspective

by Fang He, Yuxuan Si and Yixi Hu

Land 2025, 14(8), 1606; https://doi.org/10.3390/land14081606 - 6 Aug 2025

Abstract

Common prosperity serves as a pivotal condition for achieving sustainable development by fostering social equity, bolstering economic resilience, and promoting environmental stewardship. Differential land revenue, as a crucial form of property based on spatial resource occupation, significantly contributes to the achievement of common [...] Read more.

Common prosperity serves as a pivotal condition for achieving sustainable development by fostering social equity, bolstering economic resilience, and promoting environmental stewardship. Differential land revenue, as a crucial form of property based on spatial resource occupation, significantly contributes to the achievement of common prosperity, though empirical evidence of its impact is limited. This study explores the potential influence of land utilization revenue disparity on common prosperity from the perspective of urban macro differential rent (UMDR). Utilizing panel data from 280 Chinese cities spanning 2007 to 2020, we discover that UMDR and common prosperity levels exhibit strikingly similar spatiotemporal evolution. Further empirical analysis shows that UMDR significantly raises urban common prosperity levels, with a 0.217 standard unit increase in common prosperity for every 1 standard unit rise in UMDR. This boost stems from enhanced urban prosperity and the sharing of development achievements, encompassing economic growth, improved public services, enhanced ecological civilization, and more equitable distribution of development gains between urban and rural areas and among individuals. Additionally, we observe that UMDR has a more pronounced effect on common prosperity in eastern cities and those with a predominant service industry. This study enhances the comprehension of the relationship between urban land revenue disparities, prosperity, and equitable sharing, presenting a new perspective for the administration to contemplate the utilization of land-based policy tools in pursuit of the common prosperity goal and ultimately achieve sustainable development. Full article

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15 pages, 1258 KiB

Open AccessArticle

Biochar Affects Greenhouse Gas Emissions from Urban Forestry Waste

by Kumuduni Niroshika Palansooriya, Tamanna Mamun Novera, Dengge Qin, Zhengfeng An and Scott X. Chang

Land 2025, 14(8), 1605; https://doi.org/10.3390/land14081605 - 6 Aug 2025

Abstract

Urban forests are vital to cities because they provide a range of ecosystem services, including carbon (C) sequestration, air purification, and urban cooling. However, urban forestry also generates significant amounts of organic waste, such as grass clippings, pruned tree branches, and fallen tree [...] Read more.

Urban forests are vital to cities because they provide a range of ecosystem services, including carbon (C) sequestration, air purification, and urban cooling. However, urban forestry also generates significant amounts of organic waste, such as grass clippings, pruned tree branches, and fallen tree leaves and woody debris that can contribute to greenhouse gas (GHG) emissions if not properly managed. In this study, we investigated the effect of wheat straw biochar (produced at 500 °C) on GHG emissions from two types of urban forestry waste: green waste (GW) and yard waste (YW), using a 100-day laboratory incubation experiment. Overall, GW released more CO₂ than YW, but biochar addition reduced cumulative CO₂ emissions by 9.8% in GW and by 17.6% in YW. However, biochar increased CH₄ emissions from GW and reduced the CH₄ sink strength of YW. Biochar also had contrasting effects on N₂O emissions, increasing them by 94.3% in GW but decreasing them by 61.4% in YW. Consequently, the highest global warming potential was observed in biochar-amended GW (125.3 g CO₂-eq kg⁻¹). Our findings emphasize that the effect of biochar on GHG emissions varies with waste type and suggest that selecting appropriate biochar types is critical for mitigating GHG emissions from urban forestry waste. Full article

(This article belongs to the Special Issue Land Use Effects on Carbon Storage and Greenhouse Gas Emissions)

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28 pages, 5190 KiB

Open AccessArticle

Assessing the Coevolution Between Ecosystem Services and Human Well-Being in Ecotourism-Dominated Counties: A Case Study of Chun’an, Zhejiang Province, China

by Weifeng Jiang and Lin Lu

Land 2025, 14(8), 1604; https://doi.org/10.3390/land14081604 - 6 Aug 2025

Abstract

Investigating the coevolution between ecosystem services (ES) and human well-being (HWB) holds significant implications for achieving the sustainable operation of human–environment systems. However, limited research has focused on ES-HWB interactions in ecotourism-dominated counties. To address this gap, this study takes Chun’an County in [...] Read more.

Investigating the coevolution between ecosystem services (ES) and human well-being (HWB) holds significant implications for achieving the sustainable operation of human–environment systems. However, limited research has focused on ES-HWB interactions in ecotourism-dominated counties. To address this gap, this study takes Chun’an County in Zhejiang Province, China, as a case study, with the research objective of exploring the processes, patterns, and mechanisms of the coevolution between ecosystem services (ES) and human well-being (HWB) in ecotourism-dominated counties. By integrating multi-source heterogeneous data, including land use data, the normalized difference vegetation index (NDVI), and statistical records, and employing methods such as the dynamic equivalent factor method, the PLUS model, the coupling coordination degree model, and comprehensive evaluation, we analyzed the synergistic evolution of ES-HWB in Chun’an County from 2000 to 2020. The results indicate that (1) the ecosystem service value (ESV) fluctuated between 30.15 and 36.85 billion CNY, exhibiting a spatial aggregation pattern centered on the Qiandao Lake waterbody, with distance–decay characteristics. The PLUS model confirms ecological conservation policies optimize ES patterns. (2) The HWB index surged from 0.16 to 0.8, driven by tourism-led economic growth, infrastructure investment, and institutional innovation, facilitating a paradigm shift from low to high well-being at the county level. (3) The ES-HWB interaction evolved through three phases—disordered, antagonism, and coordination—revealing tourism as a key mediator driving coupled human–environment system sustainability via a pressure–adaptation–synergy transmission mechanism. This study not only advances the understanding of ES-HWB coevolution in ecotourism-dominated counties, but also provides a transferable methodological framework for sustainable development in similar regions. Full article

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23 pages, 4515 KiB

Open AccessArticle

Monitoring Post-Fire Deciduous Shrub Cover Using Machine Learning and Multiscale Remote Sensing

by Hannah Trommer and Timothy Assal

Land 2025, 14(8), 1603; https://doi.org/10.3390/land14081603 - 6 Aug 2025

Abstract

Wildfire and drought are key drivers of shrubland expansion in southwestern US landscapes. Stand-replacing fires in conifer forests induce shrub-dominated stages, and changing climatic patterns may cause a long-term shift to deciduous shrubland. We assessed change in deciduous fractional shrub cover (DFSC) in [...] Read more.

Wildfire and drought are key drivers of shrubland expansion in southwestern US landscapes. Stand-replacing fires in conifer forests induce shrub-dominated stages, and changing climatic patterns may cause a long-term shift to deciduous shrubland. We assessed change in deciduous fractional shrub cover (DFSC) in the eastern Jemez Mountains from 2019 to 2023 using topographic and Sentinel-2 satellite data and evaluated the impact of spatial scale on model performance. First, we built a 10 m and a 20 m random forest model. The 20 m model outperformed the 10 m model, achieving an R-squared value of 0.82 and an RMSE of 7.85, compared to the 10 m model (0.76 and 9.99, respectively). We projected the 20 m model to the other years of the study using imagery from the respective years, yielding yearly DFSC predictions. DFSC decreased from 2019 to 2022, coinciding with severe drought and a 2022 fire, followed by an increase in 2023, particularly within the 2022 fire footprint. Overall, DFSC trends showed an increase, with elevation being a key variable influencing these trends. This framework revealed vegetation dynamics in a semi-arid system and provided a close look at post-fire regeneration in deciduous resprouting shrubs and could be applied to similar systems. Full article

(This article belongs to the Section Land – Observation and Monitoring)

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19 pages, 8835 KiB

Open AccessArticle

The Spatial Distribution Characteristics and Driving Factors of Traditional Villages’ Tourism Transformation Level in Shaanxi, China

by Huidi Jia, Lanbo Li, Siying Wu, Ruiqi Zhao and Huan Yang

Land 2025, 14(8), 1602; https://doi.org/10.3390/land14081602 - 6 Aug 2025

Abstract

Although numerous studies have examined the spatial patterns of traditional villages and their driving factors, limited attention has been devoted to the transformation of tourism. This study focused on traditional villages in Shaanxi Province, employing geodetector and grounded theory methods to analyze their [...] Read more.

Although numerous studies have examined the spatial patterns of traditional villages and their driving factors, limited attention has been devoted to the transformation of tourism. This study focused on traditional villages in Shaanxi Province, employing geodetector and grounded theory methods to analyze their spatial distribution characteristics and influencing factors. First, most traditional villages have not developed tourism. Only 11.98% reached the relatively mature tourism stage. Second, the spatial distribution of mature traditional tourism villages is scattered and primarily clustered in Liuba County, Mizhi County, and Jia County. Third, the factors influencing spatial distribution characteristics include resource endowment, transportation accessibility, and regional economic conditions. Among these factors, the level of traditional villages, village heritage values, and the local tourism environment show the strongest explanatory power. These findings can help enhance cultural resilience, promote economic transformation and upgrading, and support the sustainable development of traditional villages. Full article

(This article belongs to the Special Issue Rural Tourism Development: Land Use, Ecosystem Services, and Community Interactions)

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22 pages, 10285 KiB

Open AccessArticle

Biophysical and Social Constraints of Restoring Ecosystem Services in the Border Regions of Tibet, China

by Lizhi Jia, Silin Liu, Xinjie Zha and Ting Hua

Land 2025, 14(8), 1601; https://doi.org/10.3390/land14081601 - 6 Aug 2025

Abstract

Ecosystem restoration represents a promising solution for enhancing ecosystem services and environmental sustainability. However, border regions—characterized by ecological fragility and geopolitical complexity—remain underrepresented in ecosystem service and restoration research. To fill this gap, we coupled spatially explicit models (e.g., InVEST and RUSLE) with [...] Read more.

Ecosystem restoration represents a promising solution for enhancing ecosystem services and environmental sustainability. However, border regions—characterized by ecological fragility and geopolitical complexity—remain underrepresented in ecosystem service and restoration research. To fill this gap, we coupled spatially explicit models (e.g., InVEST and RUSLE) with scenario analysis to quantify the ecosystem service potential that could be achieved in China’s Tibetan borderlands under two interacting agendas: ecological restoration and border-strengthening policies. Restoration feasibility was evaluated through combining local biophysical constraints, economic viability (via restoration-induced carbon gains vs. opportunity costs), operational practicality, and simulated infrastructure expansion. The results showed that per-unit-area ecosystem services in border counties (particularly Medog, Cona, and Zayu) exceed that of interior Tibet by a factor of two to four. Combining these various constraints, approximately 4–17% of the border zone remains cost-effective for grassland or forest restoration. Under low carbon pricing (US$10 t⁻¹ CO₂), the carbon revenue generated through restoration is insufficient to offset the opportunity cost of agricultural production, constituting a major constraint. Habitat quality, soil conservation, and carbon sequestration increase modestly when induced by restoration, but a pronounced carbon–water trade-off emerges. Planned infrastructure reduces restoration benefits only slightly, whereas raising the carbon price to about US$50 t⁻¹ CO₂ substantially expands such benefits. These findings highlight both the opportunities and limits of ecosystem restoration in border regions and point to carbon pricing as the key policy lever for unlocking cost-effective restoration. Full article

(This article belongs to the Special Issue The Role of Land Policy in Shaping Rural Development Outcomes)

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18 pages, 8682 KiB

Open AccessArticle

Urban Carbon Metabolism Optimization Based on a Source–Sink–Flow Framework at the Functional Zone Scale

by Cui Wang, Liuchang Xu, Xingyu Xue and Xinyu Zheng

Land 2025, 14(8), 1600; https://doi.org/10.3390/land14081600 - 6 Aug 2025

Abstract

Carbon flow tracking and spatial pattern optimization at the scale of urban functional zones are key scientific challenges in achieving carbon neutrality. However, due to the complexity of carbon metabolism processes within urban functional zones, related studies remain limited. To address these scientific [...] Read more.

Carbon flow tracking and spatial pattern optimization at the scale of urban functional zones are key scientific challenges in achieving carbon neutrality. However, due to the complexity of carbon metabolism processes within urban functional zones, related studies remain limited. To address these scientific challenges, this study, based on the “source–sink–flow” ecosystem services framework, develops an integrated analytical approach at the scale of urban functional zones. The carbon balance is quantified using the CASA model in combination with multi-source data. A network model is employed to trace carbon flow pathways, identify critical nodes and interruption points, and optimize the urban spatial pattern through a low-carbon land use structure model. The research results indicate that the overall carbon balance in Hangzhou exhibits a spatial pattern of “deficit in the center and surplus in the periphery.” The main urban area shows a significant carbon deficit and relatively poor connectivity in the carbon flow network. Carbon sequestration services primarily flow from peripheral areas (such as Fuyang and Yuhang) with green spaces and agricultural functional zones toward high-emission residential–commercial and commercial–public functional zones in the central area. However, due to the interruption of multiple carbon flow paths, the overall carbon flow transmission capacity is significantly constrained. Through spatial optimization, some carbon deficit nodes were successfully converted into carbon surplus nodes, and disrupted carbon flow edges were repaired, particularly in the main urban area, where 369 carbon flow edges were restored, resulting in a significant improvement in the overall transmission efficiency of the carbon flow network. The carbon flow visualization and spatial optimization methods proposed in this paper provide a new perspective for urban carbon metabolism analysis and offer theoretical support for low-carbon city planning practices. Full article

(This article belongs to the Special Issue The Second Edition: Urban Planning Pathways to Carbon Neutrality)

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24 pages, 6924 KiB

Open AccessArticle

Long-Term Time Series Estimation of Impervious Surface Coverage Rate in Beijing–Tianjin–Hebei Urbanization and Vulnerability Assessment of Ecological Environment Response

by Yuyang Cui, Yaxue Zhao and Xuecao Li

Land 2025, 14(8), 1599; https://doi.org/10.3390/land14081599 - 6 Aug 2025

Abstract

As urbanization processes are no longer characterized by simple linear expansion but exhibit leaping, edge-sparse, and discontinuous features, spatiotemporally continuous impervious surface coverage data are needed to better characterize urbanization processes. This study utilized GAIA impervious surface binary data and employed spatiotemporal aggregation [...] Read more.

As urbanization processes are no longer characterized by simple linear expansion but exhibit leaping, edge-sparse, and discontinuous features, spatiotemporally continuous impervious surface coverage data are needed to better characterize urbanization processes. This study utilized GAIA impervious surface binary data and employed spatiotemporal aggregation methods to convert thirty years of 30 m resolution data into 1 km resolution spatiotemporal impervious surface coverage data, constructing a long-term time series annual impervious surface coverage dataset for the Beijing–Tianjin–Hebei region. Based on this dataset, we analyzed urban expansion processes and landscape pattern indices in the Beijing–Tianjin–Hebei region, exploring the spatiotemporal response relationships of ecological environment changes. Results revealed that the impervious surface area increased dramatically from 7579.3 km² in 1985 to 37,484.0 km² in 2020, representing a year-on-year growth of 88.5%. Urban expansion rates showed two distinct peaks: 800 km²/year around 1990 and approximately 1700 km²/year during 2010–2015. In high-density urbanized areas with impervious surfaces, the average forest area significantly increased from approximately 2500 km² to 7000 km² during 1985–2005 before rapidly declining, grassland patch fragmentation intensified, while in low-density areas, grassland area showed fluctuating decline with poor ecosystem stability. Furthermore, by incorporating natural and social factors such as Fractional Vegetation Coverage (FVC), Habitat Quality Index (HQI), Land Surface Temperature (LST), slope, and population density, we assessed the vulnerability of urbanization development in the Beijing–Tianjin–Hebei region. Results showed that high vulnerability areas (EVI > 0.5) in the Beijing–Tianjin core region continue to expand, while the proportion of low vulnerability areas (EVI < 0.25) in the northern mountainous regions decreased by 4.2% in 2020 compared to 2005. This study provides scientific support for the sustainable development of the Beijing–Tianjin–Hebei urban agglomeration, suggesting location-specific and differentiated regulation of urbanization processes to reduce ecological risks. Full article

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20 pages, 5212 KiB

Open AccessArticle

Assessing the Land Surface Temperature Trend of Lake Drūkšiai’s Coastline

by Jūratė Sužiedelytė Visockienė, Eglė Tumelienė and Rosita Birvydienė

Land 2025, 14(8), 1598; https://doi.org/10.3390/land14081598 - 5 Aug 2025

Abstract

This study investigates long-term land surface temperature (LST) trends along the shoreline of Lake Drūkšiai, a transboundary lake in eastern Lithuania that formerly served as a cooling reservoir for the Ignalina Nuclear Power Plant (INPP). Although the INPP was decommissioned in 2009, its [...] Read more.

This study investigates long-term land surface temperature (LST) trends along the shoreline of Lake Drūkšiai, a transboundary lake in eastern Lithuania that formerly served as a cooling reservoir for the Ignalina Nuclear Power Plant (INPP). Although the INPP was decommissioned in 2009, its legacy continues to influence the lake’s thermal regime. Using Landsat 8 thermal infrared imagery and NDVI-based methods, we analysed spatial and temporal LST variations from 2013 to 2024. The results indicate persistent temperature anomalies and elevated LST values, particularly in zones previously affected by thermal discharges. The years 2020 and 2024 exhibited the highest average LST values; some years (e.g., 2018) showed lower readings due to localised environmental factors such as river inflow and seasonal variability. Despite a slight stabilisation observed in 2024, temperatures remain higher than those recorded in 2013, suggesting that pre-industrial thermal conditions have not yet been restored. These findings underscore the long-term environmental impacts of industrial activity and highlight the importance of satellite-based monitoring for the sustainable management of land, water resources, and coastal zones. Full article

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

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28 pages, 10144 KiB

Open AccessArticle

Decoding the Spatial–Temporal Coupling Dynamics of Land Use Intensity and Balance in China’s Chengdu–Chongqing Economic Circle: A 1 km Grid-Based Analysis

by Zijia Yan, Chenxi Zhou, Ziyi Tang, Hanfei Wang and Hao Li

Land 2025, 14(8), 1597; https://doi.org/10.3390/land14081597 - 5 Aug 2025

Abstract

Amid China’s national strategic prioritization of the Chengdu–Chongqing Economic Circle and accelerated territorial spatial planning, this study deciphered the synergistic evolution of Land Use Intensity (LUI) and Balance Degree of Land Use Structure (BDLUS) during rapid urbanization. Leveraging 1 km grid units and [...] Read more.

Amid China’s national strategic prioritization of the Chengdu–Chongqing Economic Circle and accelerated territorial spatial planning, this study deciphered the synergistic evolution of Land Use Intensity (LUI) and Balance Degree of Land Use Structure (BDLUS) during rapid urbanization. Leveraging 1 km grid units and integrating emerging spatiotemporal hotspot analysis, BFAST, and geographic detectors, we systematically analyzed spatiotemporal patterns and drivers of LUI, BDLUS, and their Coupling Coordination Degree (CCD) from 2000 to 2022. Key findings: (1) LUI strongly correlated with economic growth, with core areas reaching high-intensity development (average > 2.96) versus ecologically constrained marginal zones (<2.42), marked by abrupt changes during 2011–2014; (2) BDLUS improvements covered 82.22% of the study area, driven by the Yangtze River Economic Belt strategy (21.96% hotspot concentration), yet structural imbalance persisted in transitional zones (18.81% cold spots); (3) CCD exhibited center-edge dichotomy, contrasting high-value cores (CCD > 0.68) with ecologically sensitive edges (9.80% cold spots), peaking in regulatory shifts around 2010; (4) terrain constraints and intensified human activities (the interaction effect between nighttime lighting and population density increased by 219.49% after 2020) jointly governed coupling mechanisms, with urbanization and industrial transition becoming dominant drivers. This research advances an “intensity–structure–coordination” framework and elucidates “dual-core resonance” dynamics, offering theoretical foundations for spatial optimization and ecological civilization. Full article

(This article belongs to the Special Issue Integration of Remote Sensing and GIS for Land Use Change Assessment)

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5 pages, 131 KiB

Open AccessEditorial

The Coordinated Development of Territorial Space and Transportation

by Gaoru Zhu, Linchuan Yang and Jing Chen

Land 2025, 14(8), 1596; https://doi.org/10.3390/land14081596 - 5 Aug 2025

Abstract

As a foundational, pioneering, and strategic sector of the national economy, transportation is deeply intertwined with the layout and structure of territorial space [...] Full article

(This article belongs to the Special Issue Territorial Space and Transportation Coordinated Development)

21 pages, 9265 KiB

Open AccessArticle

Towards a Sustainable Process of Conservation/Reuse of Built Cultural Heritage: A “Coevolutionary” Approach to Circular Economy in the Case of the Decommissioned Industrial Agricultural Consortium in the Corbetta, Metropolitan Area of Milan, Italy

by Mehrnaz Rajabi, Stefano Della Torre and Arian Heidari Afshari

Land 2025, 14(8), 1595; https://doi.org/10.3390/land14081595 - 5 Aug 2025

Abstract

This paper aims to explore the potentialities and systemic relationships between the ‘regenerative’ process and ‘circular economy’ concept within the conservation and reuse of a built cultural heritage framework through contextualizing the concept of ‘process programming’ of the Preventive and Planned Conservation methodology. [...] Read more.

This paper aims to explore the potentialities and systemic relationships between the ‘regenerative’ process and ‘circular economy’ concept within the conservation and reuse of a built cultural heritage framework through contextualizing the concept of ‘process programming’ of the Preventive and Planned Conservation methodology. As a case study, it depicts a decommissioned industrial agricultural silo in Corbetta—a small historic city with its hinterland located in the protected Southern Milan Regional Agricultural Park. The context includes the industrial agricultural lands of the 20th century, together with historical water infrastructure, farmhouses, and the typical flora of the Lombardy region, all evidences of Corbetta’s rural archaeological values and the sophisticated material culture of its past collective production/economy system—the locus in which the silo was once one of the main productive symbols of Corbetta’s agricultural identity. Within such a complex and challenging context, this paper argues in favor of the constructive role of such a methodology in upholding circular economy principles within the process of conservation and reuse of the silo, highlighting its broader application of the ‘coevolution’ concept from a multidisciplinary long-term perspective. Full article

(This article belongs to the Special Issue Preservation, Reuse and Reveal of Cultural Heritage Through Sustainable Land Management, Rural and Urban Development (Third Edition))

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17 pages, 3063 KiB

Open AccessArticle

Spatiotemporal Variation in Carbon Storage in the Central Plains Urban Agglomeration Under Multi-Scenario Simulations

by Jinxin Wang, Chengyu Zhao, Zhiyi Shi and Xiangkai Cheng

Land 2025, 14(8), 1594; https://doi.org/10.3390/land14081594 - 5 Aug 2025

Abstract

Understanding changes in land use structures under multiple scenarios and their impacts on carbon storage is essential for revealing the evolution of regional development patterns and the underlying mechanisms of carbon cycle dynamics. This study adopted an integrated PLUS-InVEST modeling framework to analyze [...] Read more.

Understanding changes in land use structures under multiple scenarios and their impacts on carbon storage is essential for revealing the evolution of regional development patterns and the underlying mechanisms of carbon cycle dynamics. This study adopted an integrated PLUS-InVEST modeling framework to analyze and predict changes in carbon storage in the Central Plains Urban Agglomeration (CPUA) under different scenarios for the years 2030 and 2060. The results showed the following: (1) From 2000 to 2020, the areas of forest land, water bodies, and construction land expanded, while the areas of cropland, grassland, and barren land decreased. Over this 20-year period, carbon storage showed a declining trend, decreasing from 2390.07 × 10⁶ t in 2000 to 2372.19 × 10⁶ t in 2020. (2) In both 2030 and 2060, cropland remained the primary land use type in the CPUA. Overall, carbon storage in the CPUA was higher in the southwestern area and decreased in the central and eastern parts, which was mainly related to the land use distribution pattern in the CPUA. (3) Carbon storage under the EP (ecological protection) and CP (cropland protection) scenarios was significantly higher than under the other two scenarios, and in 2030, carbon storage under the CP and EP scenarios exceeded that in 2020, while the UD (urban development) scenario had the lowest total carbon storage. This indicated that the expansion of construction land was detrimental to carbon storage enhancement, underscoring the importance of implementing ecological protection strategies. In summary, the results of this study quantitatively reflected the changes in carbon storage in the CPUA under different future development scenarios, providing a reference for formulating regional development strategies. Full article

(This article belongs to the Special Issue Integration of Remote Sensing and GIS for Land Use Change Assessment)

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31 pages, 2983 KiB

Open AccessReview

Sustainable Management of Willow Forest Landscapes: A Review of Ecosystem Functions and Conservation Strategies

by Florin Achim, Lucian Dinca, Danut Chira, Razvan Raducu, Alexandru Chirca and Gabriel Murariu

Land 2025, 14(8), 1593; https://doi.org/10.3390/land14081593 - 4 Aug 2025

Abstract

Willow stands (Salix spp.) are an essential part of riparian ecosystems, as they sustain biodiversity and provide bioenergy solutions. The present review synthesizes the global scientific literature about the management of willow stands. In order to achieve this goal, we used a [...] Read more.

Willow stands (Salix spp.) are an essential part of riparian ecosystems, as they sustain biodiversity and provide bioenergy solutions. The present review synthesizes the global scientific literature about the management of willow stands. In order to achieve this goal, we used a dual approach combining bibliometric analysis with traditional literature review. As such, we consulted 416 publications published between 1978 and 2024. This allowed us to identify key species, ecosystem services, conservation strategies, and management issues. The results we have obtained show a diversity of approaches, with an increase in short-rotation coppice (SRC) systems and the multiple roles covered by willow stands (carbon sequestration, biomass production, riparian restoration, and habitat provision). The key trends we have identified show a shift toward topics such as climate resilience, ecological restoration, and precision forestry. This trend has become especially pronounced over the past decade (2014–2024), as reflected in the increasing use of these keywords in the literature. However, as willow systems expand in scale and function—from biomass production to ecological restoration—they also raise complex challenges, including invasive tendencies in non-native regions and uncertainties surrounding biodiversity impacts and soil carbon dynamics over the long term. The present review is a guide for forest policies and, more specifically, for future research, linking the need to integrate and use adaptive strategies in order to maintain the willow stands. Full article

(This article belongs to the Special Issue Sustainable Forest Landscape Management Towards Ecosystem Services and Biodiversity)

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14 pages, 5995 KiB

Open AccessArticle

Integrated Remote Sensing Evaluation of Grassland Degradation Using Multi-Criteria GDCI in Ili Prefecture, Xinjiang, China

by Liwei Xing, Dongyan Jin, Chen Shen, Mengshuai Zhu and Jianzhai Wu

Land 2025, 14(8), 1592; https://doi.org/10.3390/land14081592 - 4 Aug 2025

Abstract

As an important ecological barrier and animal husbandry resource base in arid and semi-arid areas, grassland degradation directly affects regional ecological security and sustainable development. Ili Prefecture is located in the western part of Xinjiang, China, and is a typical grassland resource-rich area. [...] Read more.

As an important ecological barrier and animal husbandry resource base in arid and semi-arid areas, grassland degradation directly affects regional ecological security and sustainable development. Ili Prefecture is located in the western part of Xinjiang, China, and is a typical grassland resource-rich area. However, in recent years, driven by climate change and human activities, grassland degradation has become increasingly serious. In view of the lack of comprehensive evaluation indicators and the inconsistency of grassland evaluation grade standards in remote sensing monitoring of grassland resource degradation, this study takes the current situation of grassland degradation in Ili Prefecture in the past 20 years as the research object and constructs a comprehensive evaluation index system covering three criteria layers of vegetation characteristics, environmental characteristics, and utilization characteristics. Net primary productivity (NPP), vegetation coverage, temperature, precipitation, soil erosion modulus, and grazing intensity were selected as multi-source indicators. Combined with data sources such as remote sensing inversion, sample survey, meteorological data, and farmer survey, the factor weight coefficient was determined by analytic hierarchy process. The Grassland Degeneration Comprehensive Index (GDCI) model was constructed to carry out remote sensing monitoring and evaluation of grassland degradation in Yili Prefecture. With reference to the classification threshold of the national standard for grassland degradation, the GDCI grassland degradation evaluation grade threshold (GDCI reduction rate) was determined by the method of weighted average of coefficients: non-degradation (0–10%), mild degradation (10–20%), moderate degradation (20–37.66%) and severe degradation (more than 37.66%). According to the results, between 2000 and 2022, non-degraded grasslands in Ili Prefecture covered an area of 27,200 km², representing 90.19% of the total grassland area. Slight, moderate, and severe degradation accounted for 4.34%, 3.33%, and 2.15%, respectively. Moderately and severely degraded areas are primarily distributed in agro-pastoral transition zones and economically developed urban regions, respectively. The results revealed the spatial and temporal distribution characteristics of grassland degradation in Yili Prefecture and provided data basis and technical support for regional grassland resource management, degradation prevention and control and ecological restoration. Full article

(This article belongs to the Topic Remote Sensing and GIS for Monitoring Land Use Change and Its Ecological Effects)

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26 pages, 6044 KiB

Open AccessArticle

Mapping Tradeoffs and Synergies in Ecosystem Services as a Function of Forest Management

by Hazhir Karimi, Christina L. Staudhammer, Matthew D. Therrell, William J. Kleindl, Leah M. Mungai, Amobichukwu C. Amanambu and C. Nathan Jones

Land 2025, 14(8), 1591; https://doi.org/10.3390/land14081591 - 4 Aug 2025

Abstract

The spatial variation of forest ecosystem services at regional scales remains poorly understood, and few studies have explicitly analyzed how ecosystem services are distributed across different forest management types. This study assessed the spatial overlap between forest management types and ecosystem service hotspots [...] Read more.

The spatial variation of forest ecosystem services at regional scales remains poorly understood, and few studies have explicitly analyzed how ecosystem services are distributed across different forest management types. This study assessed the spatial overlap between forest management types and ecosystem service hotspots in the Southeastern United States (SEUS) and the Pacific Northwest (PNW) forests. We used the InVEST suite of tools and GIS to quantify carbon storage and water yield. Carbon storage was estimated, stratified by forest group and age class, and literature-based biomass pool values were applied. Average annual water yield and its temporal changes (2001–2020) were modeled using the annual water yield model, incorporating precipitation, potential evapotranspiration, vegetation type, and soil characteristics. Ecosystem service outputs were classified to identify hotspot zones (top 20%) and to evaluate the synergies and tradeoffs between these services. Hotspots were then overlaid with forest management maps to examine their distribution across management types. We found that only 2% of the SEUS and 11% of the PNW region were simultaneous hotspots for both services. In the SEUS, ecological and preservation forest management types showed higher efficiency in hotspot allocation, while in PNW, production forestry contributed relatively more to hotspot areas. These findings offer valuable insights for decision-makers and forest managers seeking to preserve the multiple benefits that forests provide at regional scales. Full article

(This article belongs to the Special Issue Sustainable Forest Landscape Management Towards Ecosystem Services and Biodiversity)

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26 pages, 6220 KiB

Open AccessArticle

Estimating Urbanization’s Impact on Soil Erosion: A Global Comparative Analysis and Case Study of Phoenix, USA

by Ara Jeong, Dylan S. Connor, Ronald I. Dorn and Yeong Bae Seong

Land 2025, 14(8), 1590; https://doi.org/10.3390/land14081590 - 4 Aug 2025

Abstract

Healthy soils are an essential ingredient of land systems and ongoing global change. Urbanization as a global change process often works through the lens of urban planning, which involves urban agriculture, urban greening, and leveraging nature-based solutions to promote resilient cities. Yet, urbanization [...] Read more.

Healthy soils are an essential ingredient of land systems and ongoing global change. Urbanization as a global change process often works through the lens of urban planning, which involves urban agriculture, urban greening, and leveraging nature-based solutions to promote resilient cities. Yet, urbanization frequently leads to soil erosion. Despite recognition of this tension, the rate at which the urban growth boundary accelerates soil erosion above natural background levels has not yet been determined. Our goal here is to provide a first broad estimate of urbanization’s impact of soil erosion. By combining data on modern erosion levels with techniques for estimating long-term natural erosion rates through cosmogenic nuclide ¹⁰Be analysis, we modeled the impact of urbanization on erosion across a range of cities in different global climates, revealing an acceleration of soil erosion ~7–19x in environments with mean annual precipitation <1500 mm; growth in wetter urban centers accelerated soil erosion ~23–72x. We tested our statistical model by comparing natural erosion rates to decades of monitoring soil erosion on the margins of Phoenix, USA. A century-long expansion of Phoenix accelerated soil erosion by ~12x, an estimate that is roughly at the mid-point of model projections for drier global cities. In addition to urban planning implications of being able to establish a baseline target of natural rates of soil erosion, our findings support the urban cycle of soil erosion theory for the two USA National Science Foundation urban long-term ecological research areas of Baltimore and Phoenix. Full article

(This article belongs to the Special Issue Feature Papers for Land Systems and Global Change Section: 2nd Edition)

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24 pages, 8993 KiB

Open AccessArticle

A Lightweight Spatiotemporal Graph Framework Leveraging Clustered Monitoring Networks and Copula-Based Pollutant Dependency for PM_2.5 Forecasting

by Mohammad Taghi Abbasi, Ali Asghar Alesheikh and Fatemeh Rezaie

Land 2025, 14(8), 1589; https://doi.org/10.3390/land14081589 - 4 Aug 2025

Abstract

Air pollution threatens human health and ecosystems, making timely forecasting essential. The spatiotemporal dynamics of pollutants, shaped by various factors, challenge traditional methods. Therefore, spatiotemporal graph-based deep learning has gained attention for its ability to capture spatial and temporal dependencies within monitoring networks. [...] Read more.

Air pollution threatens human health and ecosystems, making timely forecasting essential. The spatiotemporal dynamics of pollutants, shaped by various factors, challenge traditional methods. Therefore, spatiotemporal graph-based deep learning has gained attention for its ability to capture spatial and temporal dependencies within monitoring networks. However, many existing models, despite their high predictive accuracy, face computational complexity and scalability challenges. This study introduces clustered and lightweight spatio-temporal graph convolutional network with gated recurrent unit (ClusLite-STGCN-GRU), a hybrid model that integrates spatial clustering based on pollutant time series for graph construction, Copula-based dependency analysis for selecting relevant pollutants to predict PM_2.5, and graph convolution combined with gated recurrent units to extract spatiotemporal features. Unlike conventional approaches that require learning or dynamically updating adjacency matrices, ClusLite-STGCN-GRU employs a fixed, simple cluster-based structure. Experimental results on Tehran air quality data demonstrate that the proposed model not only achieves competitive predictive performance compared to more complex models, but also significantly reduces computational cost—by up to 66% in training time, 83% in memory usage, and 84% in number of floating-point operations—making it suitable for real-time applications and offering a practical balance between accuracy, interpretability, and efficiency. Full article

(This article belongs to the Section Land Innovations – Data and Machine Learning)

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