Search Results (904)

Rapid urbanization has intensified the systemic inequities of resources and infrastructure distribution in informal settlements, particularly in the Global South. Digital Twin Modeling (DTM), as an effective data-driven representation, enables real-time analysis, scenario simulation, and design optimization, making it a promising tool to support urban resilience. This study introduces the Integrated Modification Methodology (IMM), developed by Politecnico di Milano (Italy), to explore how DTM can be systematically structured and transformed into an active instrument, linking theories with practical application. Focusing on Paranoá (Brasília), a case study developed under the NBSouth project in collaboration with the Politecnico di Milano and the University of Brasília, this research integrates advanced spatial mapping with comprehensive key performance indicators (KPIs) analysis to address developmental and environmental challenges during the regeneration process. Key metrics—Green Space Diversity, Ecosystem Service Proximity, and Green Space Continuity—were analyzed by a Geographic Information System (GIS) platform on 30 m by 30 m sampling grids. Additional KPIs across urban structural, environmental, and mobility layers were calculated to support the decision-making process for strategic mapping. This study contributes to theoretical advancements in DTM and broader discourse on urban regeneration under climate stress, offering a systemic and practical approach for multi-dimensional digitalization of urban structure and performance, supporting a more adaptive, data-based, and transferable planning process in the Global South. Full article

Assessment of cultural ecosystem services (CESs) is a key component in advancing the sustainable development of urban ecosystems. Mapping the spatial distribution of CESs provides spatially explicit insights for urban landscape planning. However, most assessments lack regional adaptability, particularly in cities with pronounced environmental and cultural heterogeneity. To address this gap, this study focused on the central urban area of Lhasa, using communities as units to develop a tailored CES assessment framework. The framework integrated the MaxEnt model with multi-source indicators to analyze the spatial distribution of five CES categories and their relationships with environmental variables. Spatial statistics and classification at community level informed the CES spatial optimization strategies. Results indicated that high-value CES areas were predominantly concentrated in the old city cluster, typified by Barkhor and Jibenggang subdistricts, following an east–west spatial pattern along the Lhasa River. Distance to tourist spot contributed 78.3% to cultural heritage, 86.1% to spirit and religion, and 42.2% to ecotourism and aesthetic services, making it the most influential environmental variable. At the community level, CESs exhibited a distinct spatial gradient, with higher values in the central area and lower values in the eastern and western peripheries. For the ecotourism and aesthetic category, 61.47% of the community area was classified as low service, whereas only 1.48% and 7.33% were identified as excellent and high. Moreover, communities within subdistricts such as Barkhor and Zhaxi demonstrated excellent service across four CES categories, with notably lower performance in the health category. This study presents a quantitative and adaptable framework and planning guidance to support the sustainable development of CESs in cities with similar characteristics. Full article

This research objective is to overcome the shortcomings of the updated values added of the System of National Accounts 2025 (SNA 2025) in order to measure the spatialized total sustainable social income from forest ecosystems through an experimentally refined System of Environmental-Economic Accounting (rSEEA). Sustainable income measured at observed, imputed, and simulated market transaction prices is defined as the maximum potential consumption of products generated in the forest ecosystem without a real decline in the environmental asset and manufactured fixed capital at the closing of the current period, assuming idealized future conditions of stable real prices and dynamics of institutional and other autonomous processes. A key finding of this research is that sustainable income extends the SNA 2025 net value added by incorporating the omissions by the latter of environmental net operating surplus (or ecosystem service in the absence of environmental damage), ordinary changes in the environmental asset condition and manufactured fixed capital adjusted according to a less ordinary entry of manufactured fixed capital plus the manufactured consumption of fixed capital. Sustainable income was measured spatially for 15 individual products, the area units being the map tiles for Andalusia, Spain, Stone pine forest (Pinus pinea L.) canopy cover was predominant, covering an area of 243,559 hectares. In 2010, the SNA 2025 gross and net values added accounted for 24% and 27%, respectively, of the Stone pine forest sustainable income measured by the rSEEA. The ecosystem services omitted by the SNA 2025 made up 69% of the rSEEA sustainable income. Full article

Droughts are becoming more frequent, severe, and impactful across the globe. Agroecosystems, which are human-made ecosystems with high water demand that provide essential ecosystem services, are vulnerable to extreme droughts. Although water use efficiency in agriculture has increased in rec ent decades, drought management should be based on long-term, proactive strategies rather than crisis management. The AgrHyS network of sites in French Brittany collects high-resolution soil moisture data from agronomic stations and catchments to improve understanding of temporal soil moisture dynamics and enhance water use efficiency. Frequent mapping of soil moisture and plant water stress is crucial for assessing water stress risk in the context of global warming. Although satellite remote sensing provides reliable, periodic global data on surface soil moisture, it does so at a very coarse spatial resolution. The intrinsic spatial heterogeneity of surface soil moisture requires a higher spatial resolution in order to address upcoming challenges on a local scale. Drones are an excellent tool for upscaling point measurements to catchment level using different onboard cameras. In this study, we evaluated the potential of multispectral images, thermal images and LiDAR data captured in several concurrent drone flights for high-resolution mapping of soil moisture spatial variability, using in situ point measurements of soil water content and plant water stress in both agricultural areas and natural ecosystems. Statistical models were fitted to map soil water content in two areas: a natural marshland and a grassland-covered agricultural field. Our results demonstrate the statistical significance of topography, land surface temperature and red band reflectance in the natural area for retrieving soil water content. In contrast, the grasslands were best predicted by the transformed normalised difference vegetation index (TNDVI). Full article

Urban sprawl and suburbanization are reshaping peri-urban areas, challenging urban planning and community well-being. Our study investigates questions regarding the perception of Cultural Ecosystem Services (CES) and development preferences (DP) related to Green Infrastructure (GI) in Vác, Hungary, including how CES and DP indicators related to GI vary spatially; how they align with municipal DI designations; how they relate to sociodemographic factors; and how they are applicable to urban planning practices. We used PPGIS and structured interviews with 375 residents to collect over 4900 spatial data points in order to analyze how perceived values, development preferences, officially designated GI elements and sociodemographic characteristics, relate to each other. The results show that CES are strongly associated with GI elements, especially along the riverfront and in downtown areas. However, development preferences, especially congestion and safety concerns, were more dispersed, often located in outer residential areas and along transportation routes. Statistical analyses showed significant differences across age, marital status, and co-residence with children, influencing both CES perception and development preferences. Our study highlights the gap between official GI designations and community-valued spaces, emphasizing the importance of participatory planning and the integration of sociodemographic dimensions into planning practices in rapidly transforming suburban environments. Full article

With rapid urbanization and increasing climate risks, cities are facing complex challenges related to environmental degradation and public health. This study conducts a bibliometric analysis of 1555 publications from the Web of Science Core Collection (2000–2025), using CiteSpace and VOSviewer to map global research trends, hotspots, and thematic evolution in the field of NbS and urban health. Results show that research interest in NbS has significantly accelerated since 2020, with Europe leading in publication output and international collaboration. Keyword analysis reveals that early studies focused on ecosystem services and climate adaptation, while recent trends emphasize governance, public participation, and environmental justice. The study also constructs a knowledge framework that illustrates how NbS contributes to urban heat mitigation, carbon management, health co-benefits, and resilience governance. This research provides a comprehensive overview of the NbS field and offers theoretical insights and empirical references for integrating NbS into urban planning, health strategies, and environmental governance, with practical relevance for cities worldwide. Full article

A comprehensive exploration of the trade-offs/synergies and drivers of ecosystem services (ESs) is essential for formulating ecological plans. However, owing to the limited attention given to multiple scales, the relationship of ESs still needs to be further explored. Taking the Yangtze River Delta region of China as the study area, a multiscale data framework with a 1 km grid and 10 km grid and county was established, and six ESs were evaluated for 2000, 2010, and 2020. Then, the trade-offs and synergies between ESs were explored by Spearman’s correlation analysis and geographically weighted regression (GWR), and the ecosystem service bundles (ESBs) were identified by self-organizing maps (SOMs). Finally, the socioecological drivers of ESs were further analyzed via GeoDetector. The results showed that (1) the distribution of ESs exhibited spatial heterogeneity. (2) At the grid scale, there were very strong trade-off effects between crop production and the other ESs. The synergistic effects between ESs at the county level were further strengthened. (3) The ESBs identified at different temporal and spatial scales were different. (4) Land use had the strongest explanatory power for all the ESs. At the grid scale, climatic and biophysical factors had great impacts on ESs, whereas population density and night light remote sensing had significant impacts on crop production, carbon storage, and water yield at the county scale. Full article

Digital innovation is rapidly transforming the agriculture sector, drawing attention from global development institutions, policymakers, tech firms, and scholars aimed at aligning food systems with international goals like Zero Hunger and the FAO agendas. Small and medium enterprises in agriculture (Agri-SMEs) represent a significant portion of processing and production units but face challenges in digital transformation despite their importance. Technologies such as Artificial Intelligence (AI), blockchain, cloud services, IoT, and mobile platforms offer tools to improve efficiency, access, value creation, and traceability. However, the patterns and applications of these transformations in Agri-SMEs remain fragmented and under-theorized. This paper presents a systematic review of interactions between digital transformation and innovation in Agri-SMEs based on findings from ninety-five peer-reviewed studies. Key themes identified include AI-based decision support, blockchain traceability, cloud platforms, IoT precision agriculture, and mobile technologies for financial integration. The review maps these themes against business model values and highlights barriers like capacity gaps and infrastructure deficiencies that hinder scalable adoption. It concludes with recommendations for future research, policy, and ecosystem coordination to promote the sustainable development of digitally robust Agri-SMEs. Full article

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

As urbanization accelerates and climate change intensifies, the ecological integrity of urban riparian forests faces growing threats, underscoring the need for a systematic framework to guide their sustainable management. To address this gap, we developed a causal framework by applying text mining and sentence classification to 1001 abstracts from previous studies, structured within the DPSIR (Driver–Pressure–State–Impact–Response) model. The analysis identified six dominant thematic clusters—water quality, ecosystem services, basin and land use management, climate-related stressors, anthropogenic impacts, and greenhouse gas emissions—which reflect the multifaceted concerns surrounding urban riparian forest research. These themes were synthesized into a structured causal model that illustrates how urbanization, land use, and pollution contribute to ecological degradation, while also suggesting potential restoration pathways. To validate its applicability, the framework was applied to four major urban streams in Seoul, where indicator-based analysis and correlation mapping revealed meaningful linkages among urban drivers, biodiversity, air quality, and civic engagement. Ultimately, by integrating large-scale text mining with causal inference modeling, this study offers a transferable approach to support adaptive planning and evidence-based decision-making under the uncertainties posed by climate change. Full article

This study investigates the concept of landscape services (LS), which integrate environmental and sociocultural dimensions of sustainable development. Recognizing landscapes as essential to daily life and well-being, the research aims to support sustainable spatial planning by analyzing both their potential and their actual use. The study has three main objectives: (1) to assess the potential of 16 selected landscape types to provide six key LS through expert evaluation; (2) to determine actual LS usage patterns among the local community (residents); and (3) to identify agreements and discrepancies between expert assessments and resident use. The services analyzed include providing space for daily activities; regulating spatial structure through diversity and compositional richness; enhancing physical and mental health; enabling passive and active recreation; supporting personal fulfillment; and fostering social interaction. Expert-based surveys and participatory mapping with residents were used to assess the provision and use of LS. The results indicate consistent evaluations for forest and historical urban landscapes (high potential and use) and mining and transportation landscapes (low potential and use). However, significant differences emerged for mountain LS, rated highly by experts but used minimally by residents. These insights highlight the importance of aligning expert planning with community needs to promote sustainable land use policies and reduce spatial conflicts. Full article

An indicator-based approach was implemented to assess the contributions of soils in supplying ecosystem services, providing a scalable tool for modeling the spatial heterogeneity of soil functions at regional and local scales. The method consisted of (i) the definition of soil-based ecosystem services (SESs), using available point data and thematic maps; (ii) the definition of appropriate SES indicators; (iii) the assessment and mapping of potential SESs provision for the Emilia-Romagna region (22.510 km²) in NE Italy. Depending on data availability and on the role played by terrain features and soil geography and its complexity, maps of basic soil characteristics (textural fractions, organic C content, and pH) covering the entire regional territory were produced at a 1 ha resolution using digital soil mapping techniques and geostatistical simulations to explicitly consider spatial variability. Soil physical properties such as bulk density, porosity, and hydraulic conductivity at saturation were derived using pedotransfer functions calibrated using local data and integrated with supplementary information such as land capability and remote sensing indices to derive the inputs for SES assessment. Eight SESs were mapped at 1:50,000 reference scale: buffering capacity, carbon sequestration, erosion control, food provision, biomass provision, water regulation, water storage, and habitat for soil biodiversity. The results are discussed and compared for the different pedolandscapes, identifying clear spatial patterns of soil functions and potential SES supply. Full article

Aquatic vegetation plays a crucial role in freshwater ecosystems by providing habitats, regulating water quality, and supporting biodiversity. This study aims to monitor and analyze the dynamics of aquatic vegetation in Chimaditida Shallow Lake, Greece, using Sentinel-2 satellite imagery, with validation from field measurements. Data processing was performed using Google Earth Engine and QGIS. The study focuses on discriminating and mapping two classes of aquatic surface conditions: areas covered with Floating and Emergent Aquatic Vegetation and open water, covering all seasons from 1 March 2024, to 28 February 2025. Spectral bands such as B04 (red), B08 (near infrared), B03 (green), and B11 (shortwave infrared) were used, along with indices like the Modified Normalized Difference Water Index and Normalized Difference Vegetation Index. The classification was enhanced using Otsu’s thresholding technique to distinguish accurately between Floating and Emergent Aquatic Vegetation and open water. Seasonal fluctuations were observed, with significant peaks in vegetation growth during the summer and autumn months, including a peak coverage of 2.08 km² on 9 September 2024 and a low of 0.00068 km² on 28 December 2024. These variations correspond to the seasonal growth patterns of Floating and Emergent Aquatic Vegetation, driven by temperature and nutrient availability. The study achieved a high overall classification accuracy of 89.31%, with producer accuracy for Floating and Emergent Aquatic Vegetation at 97.42% and user accuracy at 95.38%. Validation with Unmanned Aerial Vehicle-based aerial surveys showed a strong correlation (R² = 0.88) between satellite-derived and field data, underscoring the reliability of Sentinel-2 for aquatic vegetation monitoring. Findings highlight the potential of satellite-based remote sensing to monitor vegetation health and dynamics, offering valuable insights for the management and conservation of freshwater ecosystems. The results are particularly useful for governmental authorities and natural park administrations, enabling near-real-time monitoring to mitigate the impacts of overgrowth on water quality, biodiversity, and ecosystem services. This methodology provides a cost-effective alternative for long-term environmental monitoring, especially in regions where traditional methods are impractical or costly. Full article

The construction and maintenance of an ecological security pattern (ESP) are important for promoting the regional development of ecological civilizations, realizing sustainable and healthy development, and creating a harmonious and beautiful space for human beings and nature to thrive. Traditional construction methods have the limitations of a single dimension, a single method, and excessive human subjective intervention for source and corridor identification, without considering the multidimensional quality of the sources and the structural connectivity and resilience optimization of the corridors. Therefore, an ecological civilization demonstration area (Jiangxi Province) was used as the study area, a new research method for ESP was proposed, and an empirical study was conducted. To evaluate ecosystem service (ES) importance–disturbance–risk and extract sustainability sources through the deep embedded clustering–self-organizing map (DEC–SOM) deep unsupervised learning clustering algorithm, ecological networks (ENs) were constructed by applying the minimum cumulative resistance (MCR) gravity model and circuit theory. The ENs were then optimized to improve performance by combining the comparative advantages of the two approaches in terms of structural connectivity and resilience. A comparative analysis of EN performance was constructed among different functional control zones, and the ESP was constructed to include 42 ecological sources, 134 corridors, 210 restoration nodes, and 280 protection nodes. An ESP of ‘1 nucleus, 3 belts, 6 zones, and multiple corridors’ was constructed, and the key restoration components and protection functions were clarified. This study offers a valuable reference for ecological management, protection, and restoration and provides insights into the promotion of harmonious symbiosis between human beings and nature and sustainable regional development. Full article

The growing mismatch between ecosystem service (ES) supply and demand underscores the importance of thoroughly understanding their spatiotemporal patterns and key drivers to promote ecological civilization and sustainable development at the regional level in China. This study investigates six key ES indicators across mainland China—habitat quality (HQ), carbon sequestration (CS), water yield (WY), sediment delivery ratio (SDR), food production (FP), and nutrient delivery ratio (NDR)—by integrating a suite of analytical approaches. These include a spatiotemporal analysis of trade-offs and synergies in supply, demand, and their ratios; self-organizing maps (SOM) for bundle identification; and interpretable machine learning models. While prior research studies have typically examined ES at a single spatial scale, focusing on supply-side bundles or associated drivers, they have often overlooked demand dynamics and cross-scale interactions. In contrast, this study integrates SOM and SHAP-based machine learning into a dual-scale framework (grid and city levels), enabling more precise identification of scale-dependent drivers and a deeper understanding of the complex interrelationships between ES supply, demand, and their spatial mismatches. The results reveal pronounced spatiotemporal heterogeneity in ES supply and demand at both grid and city scales. Overall, the supply services display a spatial pattern of higher values in the east and south, and lower values in the west and north. High-value areas for multiple demand services are concentrated in the densely populated eastern regions. The grid scale better captures spatial clustering, enhancing the detection of trade-offs and synergies. For instance, the correlation between HQ and NDR supply increased from 0.62 (grid scale) to 0.92 (city scale), while the correlation between HQ and SDR demand decreased from −0.03 to −0.58, indicating that upscaling may highlight broader synergistic or conflicting trends missed at finer resolutions. In the spatiotemporal interaction network of supply–demand ratios, CS, WY, FP, and NDR persistently show low values (below −0.5) in western and northern regions, indicating ongoing mismatches and uneven development. Driver analysis demonstrates scale-dependent effects: at the grid scale, HQ and FP are predominantly influenced by socioeconomic factors, SDR and WY by ecological variables, and CS and NDR by climatic conditions. At the city level, socioeconomic drivers dominate most services. Based on these findings, nine distinct supply–demand bundles were identified at both scales. The largest bundle at the grid scale (B3) occupies 29.1% of the study area, while the largest city-scale bundle (B8) covers 26.5%. This study deepens the understanding of trade-offs, synergies, and driving mechanisms of ecosystem services across multiple spatial scales; reveals scale-sensitive patterns of spatial mismatch; and provides scientific support for tiered ecological compensation, integrated regional planning, and sustainable development strategies. Full article