Search Results (1,063)

Walking tourism is increasingly supported by a wide range of digital technologies that are crucial for mitigating environmental impacts and promoting sustainable territorial development, yet their adoption remains fragmented and rarely interpreted within a unified infrastructure perspective. While systemic infrastructure perspectives are well-established in smart city and transport literature, existing studies on walking trails still tend to focus on individual tools or user-oriented applications. Drawing upon broader smart mobility concepts, this paper proposes a system-level framework, the SmartTrail Framework (STF), for the classification, functional interpretation and integration assessment of digital technologies in walking trail infrastructures. The framework is conceived as a transferable analytical and operational instrument applicable both to academic literature and to real-world trail systems, supporting infrastructure assessment, planning and digital maturity evaluation. Following an initial bibliometric analysis of a broader Scopus dataset comprising 1697 records, a structured literature review of 253 publications was conducted to operationalise and illustrate the framework through the systematic classification of digital technologies, the mapping of functional requirements, and the assessment of Integration Levels (IL). The STF integrates three analytical dimensions: a technology domain taxonomy (six categories), a functional requirement model (five infrastructure functions) and an IL scheme (IL0–IL3) that characterises the degree of systemic coherence among digital components. The results reveal a critical functional imbalance in current digitalisation: while user-oriented navigation and information services are widely adopted, backend infrastructure functions, particularly safety and operational logistics, remain severely underdeveloped, keeping most trail systems trapped in low-integration configurations. Applied to real-world trail systems, the framework enables the identification of architectural gaps, the prioritisation of integration investments and the definition of development pathways towards intelligent trail ecosystems. The paper aims to contribute to field research by providing a structured interpretative framework for understanding digital technologies as infrastructural components of walking trails. This supports a shift from tool-based thinking to system-based infrastructure design and offers practical implications for planners, managers and policymakers involved in the development of smart, resilient and environmentally sustainable trail infrastructures. Full article

Forests reduce water-driven soil erosion, yet their protective contribution has not been assessed consistently across the European Union (EU) in a framework that separates per-area service intensity from aggregate service flow. We quantified erosion regulation service (ERS) as RUSLE-based avoided sheet and rill erosion: the difference between structural soil-loss potential (C = P = 1) and loss under forest conditions. Spatially aligned European RUSLE factors were combined with the CORINE Land Cover 2018 forest mask and summarised by country, biogeographical region and elevation. Across 134.10 Mha, ERS totalled 6806.15 Mt yr⁻¹ (mean 50.75; median 12.36 t ha⁻¹ yr⁻¹), revealing strong spatial concentration. Slovenia had the highest mean intensity (257.45 t ha⁻¹ yr⁻¹) across 1.13 Mha of mapped forest, whereas Italy provided the largest national total (1437.05 Mt yr⁻¹) across 7.83 Mha of mapped forest. Alpine and Mediterranean forests supplied 64.0% of total ERS in the 27 EU Member States (EU27) while occupying 27.7% of mapped forest area. Mean intensity increased from 9.70 t ha⁻¹ yr⁻¹ below 200 m to 248.53 t ha⁻¹ yr⁻¹ at ≥2000 m, but total service peaked at 500–1000 m. This intensity–area trade-off distinguishes priority locations from major national contributions and provides a spatially consistent baseline for multifunctional forest management, soil protection and ecosystem restoration. ERS represents modelled avoided hillslope erosion, not sediment yield or a deforestation scenario. Full article

Fine-scale mapping of forest types is a prerequisite for accurately assessing forest biomass, biodiversity, ecosystem service values, and carbon budgets. Shihe County, located within an ecotone transitioning from subtropical to temperate monsoon climates in China, was selected as the case study area. By integrating Sentinel-1 SAR and Sentinel-2 multispectral imagery, along with derived vegetation indices, texture features, and backscattering coefficients, as well as statistical features extracted from the 2022 NDVI time-series, we employed a hierarchical classification framework and a random forest algorithm to generate the forest type map. The results indicated the following: (1) With a single-date multi-feature dataset, late winter (3 March) was determined to be the optimal period for forest type classification in Shihe County. (2) Shortwave infrared bands, red-edge bands, the modified vegetation index, the normalized difference red-edge index, mean texture features, and VH-polarization data were the most influential variables. (3) Incorporating yearly NDVI time-series statistical features into the single-date winter subset significantly improved classification performance, yielding an overall accuracy of 86.39% and a Kappa of 0.781, which represents a 10.83% improvement over the baseline. Persistent misclassification between bamboo forests and tea plantations remained a primary constraint on further accuracy enhancement, while the classification accuracy for evergreen broadleaf forest and deciduous coniferous forest exhibited considerable uncertainty, likely attributable to limited reference sample sizes. (4) Deciduous broadleaf forests constituted the dominant land cover type in Shihe County, whereas evergreen coniferous forests, bamboo, and tea plantations were also widely distributed, collectively reflecting the region’s transitional ecological characteristics. Full article

Cultural ecosystem service (CES) assessment is essential for comprehensively understanding and evaluating ecosystem services. Optimizing the spatial zoning of CESs can provide more targeted information for ecosystem management. By identifying the typical landscape characteristics of different CESs, rural landscape value can be more effectively recognized. This study constructed a set of rural landscape characteristics indicators, identified the typical characteristics of different CESs based on public preferences, mapped their spatial distributions using the Maxent model, and applied K-means clustering analysis to optimize the spatial zoning in rural Huzhou. The results show that the four CESs categories are associated with different rural landscape characteristics. The spatial distributions of the CESs showed substantial overlap and were mainly concentrated in southern Anji County, around the Moganshan Scenic Area, and along the shoreline of Lake Taihu. Five types of rural landscapes were identified based on spatial distribution of the CESs. This study provides a reference for identifying the landscape value of CESs in rural areas and supports the incorporation of CES assessment into rural landscape management decision-making. Full article

Land consolidation (LC) is increasingly expected to support food security, ecological restoration, rural development, and climate mitigation, yet evidence on its carbon effects remains fragmented across engineering, ecological, spatial, and governance research. This review combines bibliometric mapping with structured evidence synthesis of 355 records from WoS and CNKI to examine knowledge evolution, analytical paradigms, and their integration. The field has expanded from component-based assessments of construction emissions, soil carbon, and land-cover change toward life-cycle accounting, carbon fractions, ecosystem-service interactions, spatial optimization, and policy evaluation. WoS-indexed and Chinese-language literature show distinct but increasingly convergent orientations shaped by differences in intervention contexts, disciplinary traditions, analytical scales, and available evidence. Four complementary paradigms are identified: carbon accounting, biogeochemical processes, spatial land systems, and decision support and governance. Together, these paradigms reveal interconnected carbon pathways but remain constrained by inconsistent accounting boundaries, weak process–scale–time linkages, and limited integration with land-governance decisions. Future research should therefore advance standardized life-cycle and multi-scale accounting, mechanism-based assessment of long-term carbon and ecosystem-service dynamics, and digitally and institutionally enabled low-carbon governance. Full article

As religious tourism expands across Asia, it remains unclear who benefits from its growth and who is overlooked in policy and industry accounts. Drawing on fieldwork in the temple-towns of Jejuri and Tuljapur in Maharashtra, India, this paper aims to make a timely and original contribution about the significance of informal, family-run and ritual-linked enterprises to the centre of debates on entrepreneurship and inclusive tourism development. The study combines visitor surveys, detailed enterprise mapping and entrepreneur interviews to reveal a dense but precarious local economy which is sustained by religious retail (a term articulated for sale of items related to rituals), street vending and small-scale service provision. These micro-enterprises are culturally central but economically fragile, low-margin and weakly recognised in policy. The paper argues that entrepreneurship is constrained by traditional religious authority, informality, seasonality and limited innovation capacity, while rising visitor numbers are creating opportunities in travel, accommodation and food. It shows that sustainability in temple-towns depends on livelihood durability, socio-cultural continuity, participatory governance and distributional justice. By foregrounding actors often omitted from formal economic analysis, the paper reframes religious tourism as an embedded entrepreneurial ecosystem and calls for policies that strengthen local enterprise capability, resilience and participation. Full article

Thai Buddhist funeral services constitute a substantial multi-actor service ecosystem that remains largely dependent on conventional, fragmented coordination among bereaved families, temples, service providers, and administrative actors, with limited digital integration. This study reports a pre-deployment acceptance evaluation of a conceptually specified GenAI-assisted funeral-coordination service and proposes an Evidence-to-Design Translation Framework (EDTF) for translating acceptance evidence into initial design and governance requirements. Using non-probability convenience sampling through online recruitment, 342 screened adults with prior funeral-arrangement experience in the Bangkok Metropolitan Area evaluated a standardized vignette and representative interface mockups rather than an operational platform. PLS-SEM was used to examine prospective acceptance under five predefined safeguards: traceability, auditability, contestability and redress, verification, and risk-based human review. Perceived usefulness was the strongest predictor of intention to use, while attitude toward use provided a secondary pathway. The EDTF maps empirically supported user-evaluation signals to candidate workflow features, accountability controls, required records, monitoring indicators, and escalation rules. The findings provide bounded pre-deployment evidence for subsequent prototyping and pilot validation; they do not demonstrate actual adoption, live-system effectiveness, safeguard causality, or realized industry transformation. Full article

Urban parks provide recreation, cultural ecosystem services, microclimate regulation, and benefits for well-being, but their realized value may vary with air pollution and heat. This exploratory study linked 2947 Google Maps reviews posted in 2024–2025 to daily PM2.5, temperature, humidity, and precipitation and assessed a BERT-based workflow for classifying star-linked sentiment and dominant emotion text labels. Star-linked sentiment classifications were highly favorable (mean score of 4.86/5; 88.39% very positive). Independent weighting of the rounded air-quality and heat-stress subgroup summaries yielded consistent approximate overall shares for provisional joy (28.9%) and anger (32.5%), but the full seven-class distribution could not be reconstructed from the archive. All emotion-label analyses remain provisional. All 25 tested environmental correlations were negligible (absolute Spearman ρ ≤ 0.049), and none met the Bonferroni-corrected significance threshold (α = 0.002). Posting dates classified as heat-stress days showed descriptive differences in provisional anger and joy labels, but posting date is an uncertain proxy for the visit date. The findings do not establish individual-level exposure associations. They instead illustrate the methodological safeguards needed before user-generated park feedback and environmental monitoring can support climate-responsive management. Full article

The Ifrane National Park (INP), situated in the Middle Atlas Mountains in Morocco, is renowned for its unique bioecological attributes and rich biodiversity. The park provides key ecosystem services, notably climate regulation, with its Atlas cedar forests serving as an important carbon reservoir. Despite its importance, the park faces challenges associated with Land Use Land Cover Changes (LULCCs). These dynamics, driven by population settlement in mountain areas, intensify pressure on forest resources and accelerate the conversion of rangelands into croplands. Our study aims to examine the carbon sequestration service (CSS) in INP and its changes in response to land use dynamics before and after the park’s creation. We first use Google Earth Engine platform to map Land Use Land Cover (LULC) over three decades (1992/2022). Then, we quantify and map CSS using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST 3.10.2) model. Finally, we assess the economic value of this service over time using the social cost of carbon, adjusted by an appropriate discount rate. Our findings show that CSS declined by −217,738.4 tC/year (1992–2002) and −177,903.2 tC/year (2002–2012) prior to the park’s establishment, before rising to +61,786.8 tC/year during 2012–2022, following the park’s establishment and subsequent forest restoration, increasing its economic value from a net loss to +12,340,544 USD/year. By addressing a significant knowledge gap regarding CSS dynamics and economic value within a protected area, this study highlights the effectiveness of conservation measures and offers a practical tool for managers to inform decision makers, promote conservation and restoration investments, and engage local communities in sustainable development initiatives. Full article

High-altitude Andean páramo ecosystems are critical socio-ecological assets that provide key regulating and supporting services, yet they remain highly vulnerable to climate change and anthropogenic pressures. Understanding these services requires frameworks that integrate biophysical capacity with social valuation and demographic accessibility. In this study, we mapped and assessed belowground and aboveground carbon storage and species habitat provision across the altitudinal gradient (3160–4400 m.a.s.l.) of Cajas National Park (PNC), Ecuador, using a spatially explicit socio-ecological approach. Carbon stocks were modeled following The Intergovernmental Panel on Climate Change (IPCC) 2019 Refined Guidelines, combining reference soil organic carbon (SOC) stocks with aboveground biomass coefficients. Habitat provision was modeled through a multi-factor suitability index integrating Normalized Difference Vegetation Index (NDVI), elevation, water bodies, and interpolated climate surfaces. Biophysical supplies were weighted via a Delphi-based expert consultation and integrated with demographic census data (173,672 inhabitants in four adjacent parishes) to estimate actual service capture and effective benefits. Total carbon stocks in PNC were estimated at 1.49 million Mg C, with volcanic Andisols acting as the primary reservoir (97.5% of the total stock). Habitat suitability was highly heterogeneous, with critical refuge patches clustered around the park’s lacustric network and stable microclimatic zones. Socio-ecological mapping revealed that the eastern boundary of the park represents the highest hotspot of effective benefit capture, directly supplying vital water regulation and cultural services to the peri-urban populations of Sayausí and Baños. These results demonstrate the utility of integrating standard IPCC guidelines with the ECOSER protocol, offering a repeatable and transparent framework to guide spatial conservation planning and sustainable land-use zoning in vulnerable high-altitude protected areas. Full article

The sustainability of Coffea arabica L. production in Oaxaca, Mexico, is increasingly threatened by climate change, biodiversity loss, and pest pressure, along with other factors that undermine the responsiveness of small-scale producers in the state, such as trade restrictions and coffee-related regulatory frameworks. These challenges are particularly acute in mountainous regions like Oaxaca, where coffee cultivation plays a central role in rural livelihoods, cultural identity, and territorial development. Studies demonstrate that localized models are vital for rural improvement, reducing the carbon footprint, and maintaining economic viability. Despite extensive research on agronomic, environmental, and market factors, sustainability strategies for coffee production often remain fragmented and insufficiently integrated. This systematic review used the Scopus Review database, searching by title, abstract, and keywords such as “sustainable coffee production” from 2015 to 2026. A total of 1085 documents were retrieved and processed using VOSviewer software to generate a bibliographic map in which frequently used words are grouped by color to show their relationships. Using Oaxaca as a regional case study, the article synthesizes the key factors influencing coffee productivity and quality, examines the main socio-environmental challenges, and proposes a conceptual framework that integrates agroecosystem management with socioeconomic processes under external climate and market pressures. The proposed framework highlights the central role of agroforestry systems and ecosystem services in improving climate resilience, conserving biodiversity, and supporting quality-oriented value chains. These processes generate feedback loops that influence farmers’ livelihoods, food security, and territorial sustainability. While grounded in the context of Oaxaca, the socio-ecological review and conceptual framework presented here are applicable to other Arabica-producing regions facing similar challenges, providing a structured basis for future research, policy design, and integrated sustainability strategies. Full article

Mangroves provide critical ecosystem services, including coastal protection, biodiversity conservation, carbon sequestration, and environmental purification. Detailed mangrove mapping is therefore essential for effective conservation, restoration, and management. With the proliferation of remotely sensed imagery across diverse spatial resolutions, comparative studies on mapping efficiency are vital for optimizing long-term, large-scale monitoring strategies. This study utilized multi-source satellite imagery, which includes Landsat-8 (15 m and 30 m), Sentinel-2 (10 m), ZiYuan-3 (ZY-3), and GaoFen-1 (GF-1) (2 m), to map mangroves in the Beibu Gulf by integrating spectral, texture, and topographic features. The optimal feature combination was determined experimentally. We comprehensively compared the identification accuracy, identification results, and area estimates derived from three distinct methods: pixel-based Random Forest (RF), object-oriented RF, and a U-Net + ResNet-34 deep learning model. Key findings include the following: (1) Feature importance varied by resolution; terrain features significantly improved accuracy for medium-resolution images (e.g., Landsat-8), increasing the F1-score by 1.91%, while texture features were critical for high-resolution images (e.g., ZY-3 and GF-1), improving the F1-score by 2.99%. (2) Deep learning achieved the highest accuracy using Sentinel-2 combined with terrain features, yielding an F1-score of 96.45%. (3) Higher-resolution imagery enabled the detection of smaller mangrove patches; deep learning produced the fewest internal gaps, whereas pixel-based RF suffered from severe “salt-and-pepper” noise. (4) While object-oriented RF using Sentinel-2 imagery produced results most consistent with the validation set (recall = 94.38%), notable area discrepancies (9.7%) persisted, primarily due to tidal dynamics. We conclude that deep learning models, particularly when integrating Sentinel-2 data with terrain features, provide superior accuracy for mangrove mapping. Nevertheless, tidal dynamics continue to pose a significant challenge for computer-aided identification approaches. Full article

Land-use and land-cover (LULC) change is a major driver of ecosystem degradation and ecosystem service loss in tropical landscapes. This study assessed the impacts of LULC changes between 1985 and 2023 on the potential of different LULC classes to supply ecosystem services in the Upper Rio Pardo Basin (Rio Pardo and Rio São João do Paraíso watersheds), northern Minas Gerais, Brazil. LULC data from the MapBiomas Project were used to quantify transitions among LULC classes within the study area. The potential supply of ecosystem services was assessed using the Burkhard matrix, adapted to local environmental conditions and informed by expert knowledge, while the relative importance of ecosystem services was evaluated through a participatory assessment involving local communities. The expansion of pasturelands and commercial forest plantations was identified as the primary driver of ecosystem service loss in the study region. Native ecosystems showed the highest potential to provide regulating, supporting, provisioning, and cultural ecosystem services, particularly water regulation, soil protection, carbon sequestration, and biodiversity conservation. In contrast, anthropogenic land uses were primarily associated with provisioning services and showed limited capacity to sustain regulating and supporting services, indicating clear trade-offs between production and ecosystem functioning. Local communities identified water-related services as the highest priority, followed by climate regulation, soil fertility, and food provision. These findings demonstrate the value of integrating expert-based and participatory approaches to ecosystem service assessment and provide a basis for territorial planning strategies that prioritize the conservation and restoration of native vegetation, particularly in hydrologically sensitive areas. Full article

Wetlands have been noted to provide us with a wide range of ecosystem services—climate, water quality, flood regulation, and habitat benefits among others. The evidence that supports these service benefits is fairly well documented in the literature. However, it is often scattered across studies, metrics, and valuation methods, making it difficult for planners and landscape architects to use in physical projects and plans. The empirical result of this difficulty is that wetlands are often overlooked and under-utilized as part of broader ecosystem and land based planning solution sets. This paper addresses this usability deficiency using an ecosystem accounting framework that translates wetland science into spatially specific design and planning metrics. The framework follows the System of Environmental-Economic Accounting-Ecosystem Accounting (SEEA EA), an international statistical framework adopted by the UN to measure the environment’s contribution to the economy and human well-being. In our study, wetland extents in the state of Illinois are mapped on a statewide 30 m × 30 m grid. Individual wetland system conditions are estimated from floristic quality using a generalized additive model trained on 244 wetland sites that are part of the long-term Critical Trends Assessment Program (CTAP) at the Illinois Department of Natural Resources (IDNR). A floristic condition scalar, $w\left(x\right)$, provides a screening-level measure of ecological condition. It is applied only to a nonmonetary habitat-condition account and is not used to scale the monetary service accounts. Climate regulation, water purification, and flood regulation are quantified through service-specific physical models and reported as carbon-price and replacement-cost proxies. Under the central scenarios, these three monetary proxy accounts produce a combined subtotal of USD 1408.6 million per year. The annualized surface-storage replacement-cost scenario accounts for USD 1048.5 million, load-gated nitrogen-removal replacement cost for USD 338.0 million, and the climate-regulation carbon-price proxy for USD 22.1 million. These estimates are planning proxies rather than observed market benefits or realized avoided damages. The separate habitat-condition account totals 198,280 condition-weighted hectares, with a statewide mean $w\left(x\right)$ of 0.502, and is not added to the monetary subtotal. Climate performance varies across wetland types: methane emissions cause some emergent wetland categories to function as net greenhouse-gas sources under the central assumptions, while other categories remain net sinks. A protection-gap analysis shows that Tier 4 wetlands contain 70.1% of the classified vegetated-wetland area and 67.0% of the condition-weighted habitat area within the classified domain. Broadly, the framework demonstrates how ecosystem accounting can translate fragmented wetland evidence into consistent spatial metrics for planning. The resulting layers support statewide screening, comparison among wetland categories, conservation and restoration screening, and protection-gap analysis while preserving the distinction between monetary service proxies and nonmonetary ecological condition. Full article

Understanding how land change affects water yield is essential for sustainable land management and water security. However, previous studies often rely on a single model or spatial scale, limiting their ability to capture fine-scale land-surface heterogeneity and basin-integrated hydrological processes; consequently, cross-scale consistency in water-yield patterns and drivers remains unresolved. This study developed a dual-spatial-scale framework for the Upper Yangtze River Basin. The Patch-generating Land-Use Simulation (PLUS) model projected land patterns for 2030, the Integrated Valuation of Ecosystem Services and Tradeoffs Annual Water Yield (InVEST-AWY) model mapped grid-scale water yield, the Soil and Water Assessment Tool (SWAT) model simulated sub-basin hydrological responses, and Geodetector identified dominant drivers. Their integration links local land transitions with basin-scale hydrological consequences under consistent scenarios, thereby overcoming the limitations of single-model assessments. Results showed that high water-yield areas were concentrated in the eastern and central basin, while the two scales exhibited similar spatial patterns but locally different magnitudes and trends. Built-up land under urban development was 7.96% greater than under ecological protection. Climatic variability increased runoff by 2115.33 m³/s under ecological protection, while precipitation dominated water-yield variation, with explanatory powers of 0.81 and 0.67 at the grid and sub-basin scales, respectively. These findings advance understanding of scale-dependent responses and support land optimization and watershed planning. Full article