Search Results (1,204)

Soil structural instability in reservoir riparian zones, induced by water level fluctuations, threatens sustainable land use by accelerating land degradation. This study examined the impact of water-level variations on soil aggregate composition and stability based on key indicators, including water-stable aggregate content (WSAC), mean weight diameter (MWD), and geometric mean diameter (GMD). The Savinov dry sieving, Yoder wet sieving, and Le Bissonnais (LB) methods were employed for analysis. Results indicated that, with decreasing water levels and increasing soil layer, aggregates larger than 5 mm decreased, while aggregates smaller than 0.25 mm increased. Rising water levels and increasing soil layer corresponded to reductions in soil stability indicators (MWD, GMD, and WSAC), highlighting a trend toward soil structural instability. The LB method revealed the lowest aggregate stability under rapid wetting and the highest under slow wetting conditions. Correlation analysis showed that soil organic matter positively correlated with the relative mechanical breakdown index (RMI) (p < 0.05) and negatively correlated with the relative slaking index (RSI), whereas soil pH was negatively correlated with both RMI and RSI (p < 0.05). Comparative analysis of aggregate stability methods demonstrated that results from the dry sieving method closely resembled those from the SW treatment of the LB method, whereas the wet sieving method closely aligned with the FW (Fast Wetting) treatment of the LB method. The Le Bissonnais method not only reflected the outcomes of dry and wet sieving methods but also effectively distinguished the mechanisms of aggregate breakdown. The study concluded that prolonged flooding intensified aggregate dispersion, with mechanical breakdown influenced by water levels and soil layer. Dispersion and mechanical breakdown represent primary mechanisms of soil aggregate instability, further exacerbated by fluctuating water levels. By elucidating degradation mechanisms, this research provides actionable insights for preserving soil health, safeguarding water resources, and promoting sustainable agricultural in ecologically vulnerable reservoir regions of the Yangtze River Basin. Full article

A just and sustainable energy transition in historically coal-dependent regions like Kentucky requires more than the adoption of new technologies and market-based solutions. This study uses a stated preferences approach to evaluate public support for various attributes of energy transition programs, revealing broad backing for moving away from coal, as indicated by a negative willingness to pay (WTP) for the status quo (–USD 4.63). Key findings show strong bipartisan support for solar energy, with Democrats showing the highest WTP at USD 8.29, followed closely by Independents/Others at USD 8.22, and Republicans at USD 8.08. Wind energy also garnered support, particularly among Republicans (USD 4.04), who may view it as more industry-compatible and less ideologically polarizing. Job creation was a dominant priority across political affiliations, especially for Independents (USD 9.07), indicating a preference for tangible, near-term economic benefits. Similarly, preserving cultural values tied to coal received support among Independents/Others (USD 4.98), emphasizing the importance of place-based identity in shaping preferences. In contrast, social support programs (e.g., job retraining) and certain post-mining land uses (e.g., recreation and conservation) were less favored, possibly due to their abstract nature, delayed benefits, and political framing. Findings from Kentucky offer insights for other coal-reliant states like Wyoming, West Virginia, Pennsylvania, Indiana, and Illinois. Ultimately, equitable transitions must integrate local voices, address cultural and economic realities, and ensure community-driven planning and investment. Full article

Object detection in remote sensing imagery is critical in environmental monitoring, urban planning, and land resource management. However, the task remains challenging due to significant scale variations, arbitrary object orientations, and complex background clutter. To address these issues, we propose a novel orientation module (SOAM Block) that jointly models object scale and directional features while exploiting geometric symmetry inherent in many remote sensing targets. The SOAM Block is constructed upon a lightweight and efficient Adaptive Multi-Scale (AMS) Module, which utilizes a symmetric arrangement of parallel depth-wise convolutional branches with varied kernel sizes to extract fine-grained multi-scale features without dilation, thereby preserving local context and enhancing scale adaptability. In addition, a Strip-based Context Attention (SCA) mechanism is introduced to model long-range spatial dependencies, leveraging horizontal and vertical 1D strip convolutions in a directionally symmetric fashion. This design captures spatial correlations between distant regions and reinforces semantic consistency in cluttered scenes. Importantly, this work is the first to explicitly analyze the coupling between object scale and orientation in remote sensing imagery. The proposed method addresses the limitations of fixed receptive fields in capturing symmetric directional cues of large-scale objects. Extensive experiments are conducted on two widely used benchmarks—DOTA and HRSC2016—both of which exhibit significant scale variations and orientation diversity. Results demonstrate that our approach achieves superior detection accuracy with fewer parameters and lower computational overhead compared to state-of-the-art methods. The proposed SOAM Block thus offers a robust, scalable, and symmetry-aware solution for high-precision object detection in complex aerial scenes. Full article

With the growing demand for ecological monitoring and geological exploration, high-quality satellite remote-sensing imagery has become indispensable for accurate information extraction and automated analysis. However, haze reduces image contrast and sharpness, significantly impairing quality. Existing dehazing methods, primarily designed for natural images, struggle with remote-sensing images due to their complex imaging conditions and scale diversity. Given this, we propose a novel Multi-Scale Contextual Attention Generative Adversarial Network (MCA-GAN), specifically designed for satellite image dehazing. Our method integrates multi-scale feature extraction with global contextual guidance to enhance the network’s comprehension of complex remote-sensing scenes and its sensitivity to fine details. MCA-GAN incorporates two self-designed key modules: (1) a Multi-Scale Feature Aggregation Block, which employs multi-directional global pooling and multi-scale convolutional branches to bolster the model’s ability to capture land-cover details across varying spatial scales; (2) a Dynamic Contextual Attention Block, which uses a gated mechanism to fuse three-dimensional attention weights with contextual cues, thereby preserving global structural and chromatic consistency while retaining intricate local textures. Extensive qualitative and quantitative experiments on public benchmarks demonstrate that MCA-GAN outperforms other existing methods in both visual fidelity and objective metrics, offering a robust and practical solution for remote-sensing image dehazing. Full article

Geographic object-based image analysis (GEOBIA) has demonstrated substantial utility in remote sensing tasks. However, its integration with deep learning remains largely confined to image-level classification. This is primarily due to the irregular shapes and fragmented boundaries of segmented objects, which limit its applicability in semantic segmentation. While convolutional neural networks (CNNs) excel at local feature extraction, they inherently struggle to capture long-range dependencies. In contrast, Transformer-based models are well suited for global context modeling but often lack fine-grained local detail. To overcome these limitations, we propose GOFENet (Geo-Object Feature Enhanced Network)—a hybrid semantic segmentation architecture that effectively fuses object-level priors into deep feature representations. GOFENet employs a dual-encoder design combining CNN and Swin Transformer architectures, enabling multi-scale feature fusion through skip connections to preserve both local and global semantics. An auxiliary branch incorporating cascaded atrous convolutions is introduced to inject information of segmented objects into the learning process. Furthermore, we develop a cross-channel selection module (CSM) for refined channel-wise attention, a feature enhancement module (FEM) to merge global and local representations, and a shallow–deep feature fusion module (SDFM) to integrate pixel- and object-level cues across scales. Experimental results on the GID and LoveDA datasets demonstrate that GOFENet achieves superior segmentation performance, with 66.02% mIoU and 51.92% mIoU, respectively. The model exhibits strong capability in delineating large-scale land cover features, producing sharper object boundaries and reducing classification noise, while preserving the integrity and discriminability of land cover categories. Full article

The rising demand for sustainable protein is driving interest in insects as a raw material for advanced food ingredients. This review collates and critically analyses over 300 studies on the conversion of crickets, mealworms, black soldier flies, and other farmed species into powders, protein isolates, oils, and chitosan-rich fibers with targeted techno-functional roles. This survey maps how thermal pre-treatments, blanch–dry–mill routes, enzymatic hydrolysis, and isoelectric solubilization–precipitation preserve or enhance the water- and oil-holding capacity, emulsification, foaming, and gelation, while also mitigating off-flavors, allergenicity, and microbial risks. A meta-analysis shows insect flours can absorb up to 3.2 g of water g⁻¹, stabilize oil-in-water emulsions for 14 days at 4 °C, and form gels with 180 kPa strength, outperforming or matching eggs, soy, or whey in specific applications. Case studies demonstrate a successful incorporation at 5–15% into bakery, meat analogs and dairy alternatives without sensory penalties, and chitin-derived chitosan films extend the bread shelf life by three days. Comparative life-cycle data indicate 45–80% lower greenhouse gas emissions and land use than equivalent animal-derived ingredients. Collectively, the evidence positions insect-based ingredients as versatile, safe, and climate-smart tools to enhance food quality and sustainability, while outlining research gaps in allergen mitigation, consumer acceptance, and regulatory harmonization. Full article

The Arctic Ocean is turning blue. Abrupt Arctic warming and amplification is driving rapid sea ice decline and irreversible deglaciation of Greenland. The already emerging, substantial consequences for the planet and society are intensifying and yet, model-based projections lack validatory consensus. To date, we cannot anticipate how a blue Arctic will respond to and amplify an increasingly warmer future climate, nor how it will impact the wider planet and society. Climate projections are inconclusive as we critically lack key Arctic geological archives that preserved the answers. This “Arctic Challenge” of global significance can only be addressed by investigating the processes, consequences, and impacts of past “greenhouse” (warmer-than-present) climate states. To address this challenge, the ERC Synergy Grant project Into the Blue (i2B) is undertaking a program of research focused on retrieving new Arctic geological archives of past warmth and key breakthroughs in climate model performance to deliver a ground-breaking, synergistic framework to answer the central question: “Why and what were the global ramifications of a “blue” (ice-free) Arctic during past warmer-than-present climates?” Here, we present the proposed research plan that will be conducted as part of this program. Into the Blue will quantify cryosphere (sea ice and land ice) change in a warmer world that will form the scientific basis for understanding the dynamics of Arctic cryosphere and ocean changes to enable the quantitative assessment of the impact of Arctic change on ocean biosphere, climate extremes, and society that will underpin future cryosphere-inclusive IPCC assessments. Full article

While the explosive growth in e-commerce stresses urban logistics systems, city planners lack of fine-grained data in order to anticipate and manage the resulting freight flows. Using a three-stage analytical approach combining descriptive zonal statistics, hotspot analysis and different regression modeling from univariate to geographically weighted regression, this study integrates one year of parcel deliveries from a leading courier with open spatial layers of land-use zoning, census population, mobile-signal activity and household income to model last-mile demand across different land use types. A baseline linear regression shows that residential population alone accounts for roughly 30% of the variance in annual parcel volumes (2.5–3.0 deliveries per resident) while adding daytime workforce and income increases the prediction accuracy to 39%. In a similar approach where coefficients vary geographically with Geographically Weighted Regression to capture the local heterogeneity achieves a significant raise of the overall R² to 0.54 and surpassing 0.70 in residential and institutional districts. Hot-spot analysis reveals a highly fragmented pattern where fewer than 5% of blocks generate more than 8.5% of all deliveries with no apparent correlation to the broaden land-use classes. Commercial and administrative areas exhibit the greatest intensity (1149 deliveries per ha) yet remain the hardest to explain (global R² = 0.21) underscoring the importance of additional variables such as retail mix, street-network design and tourism flows. Through this approach, the calibrated models can be used to predict city-wide last-mile demand using only public inputs and offers a transferable, privacy-preserving template for evidence-based freight planning. By pinpointing the location and the land uses where demand concentrates, it supports targeted interventions such as micro-depots, locker allocation and dynamic curb-space management towards more sustainable and resilient urban-logistics networks. Full article

Planning conservation for multiple species while accounting for habitat availability and connectivity under uncertain land-use changes presents a major challenge. This study proposes a protocol to identify strategic conservation areas by assessing the functional connectivity of key bird species under future land-use scenarios in the Chaco Serrano of Córdoba, Argentina. We modeled three land-use scenarios for 2050: business as usual, sustainability, and intensification. Using the Equivalent Connected Area index, we evaluated functional connectivity for Chlorostilbon lucidus, Polioptila dumicola, Dryocopus schulzii, Milvago chimango, and Saltator aurantiirostris for 1989, 2019, and 2050, incorporating information about habitat specialization and dispersal capacity to reflect differences in ecological responses. All species showed declining connectivity from 1989 to 2019, with further losses expected under future scenarios. Connectivity declines varied by species and were not always proportional to habitat loss, highlighting the complex relationship between land-use change and functional connectivity. Surprisingly, the sustainability scenario led to the greatest losses in connectivity, emphasizing that habitat preservation alone does not ensure connectivity. Using the Integral Connectivity Index, we identified habitat patches critical for maintaining connectivity, particularly those vulnerable under the business as usual scenario. With a spatial prioritization analysis we identified priority conservation areas to support future landscape connectivity. These findings underscore the importance of multispecies, connectivity-based planning and offer a transferable framework applicable to other regions. Full article

The complex plant cell wall heteropolysaccharide xylan, and its breakdown products xylo-oligosaccharides and xylose, are value-added compounds with a plethora of potential applications in diverse areas. They are nonetheless currently poorly exploited, with a major bottleneck being the unavailability of efficient, low-cost, high-yield production processes. The major objective of the present study is to identify and characterise a high-yield process for the preparation of highly pure xylan/XOS products from the macroalga Palmaria palmata. Currently, most xylan is extracted from land-sourced lignocellulosic feedstocks, but we take advantage of the high xylan content, xylan aqueous solubility, lignin-free nature, weakly linked cell wall matrix, and sustainability of the macroalga to identify a simple, sustainable, high-yield, novel-xylan-structure extraction process. This is composed of five steps: alga oven drying, milling, aqueous extraction, centrifugation, and dialysis, and we show that the alga preservation step plays a critical role in component extractability, with oven drying at high temperatures, ~100 °C, enhancing the subsequent aqueous extraction process, and providing for xylan yields as high as 80% of a highly pure (~90%) xylan product. The process developed herein and the insights gained will promote a greater availability of these bioactive compounds and open up their application potential. Full article

This study explores the role of community-centered farm-based hospitality in promoting sustainable rural development, with a focus on South Tyrol, Italy. A survey of 461 local residents assessed perceptions of agritourism’s impact on agricultural heritage, environmental sustainability, and community well-being. Factor analysis identified two main constructs—Agroheritage Sustainability and Empowered Eco-Tourism—which together capture the multifaceted benefits of agritourism. Agroheritage Sustainability reflects the preservation of traditional farming practices, cultural landscapes, and intergenerational knowledge, emphasizing the role of tourism in maintaining cultural identity and preventing land abandonment. Empowered Eco-Tourism highlights the socio-economic benefits of sustainable tourism, including community empowerment, environmental stewardship, and the creation of new economic opportunities. The study’s findings indicate that local residents view agritourism as a holistic approach that supports rural livelihoods while preserving cultural heritage and promoting ecological resilience. The analysis further supports the potential of farm-based hospitality as a model for sustainable rural development, aligning closely with EU policies and global best practices. The Roter Hahn initiative in South Tyrol serves as a practical example of this approach, demonstrating the value of certification programs in enhancing transparency, quality, and sustainability. These insights provide valuable guidance for policymakers and tourism developers seeking to promote sustainable rural tourism globally. The contribution of this research lies in its empirical validation of a dual-construct model that links community engagement with agroecological and cultural sustainability, offering a transferable framework for evaluating agritourism as a lever for sustainable rural development in diverse regional contexts. Full article

The objective of this study is to define groundwater management zones for a complex deformed and fissured Precambrian karst aquifer, which underlies one of the most important agricultural areas in the semi-arid region of Irecê, Bahia, Brazil. It is an unconfined aquifer, hundreds of meters thick, resulting from a large sequence of carbonates piled up by thrust faults during tectonic plate collisions. Groundwater recharge and flow in this aquifer are greatly influenced by karst features, through the high density of sinkholes and vertical wells. Over the past four decades, population and agricultural activities have increased in the region, resulting in unsustainable groundwater withdrawal and, at the same time, water quality degradation. Therefore, it is important to develop legal and environmental management strategies. This work proposes the division of the karst area into three well-defined management zones by mapping karst structures, land use, and urban occupation, as well as the concentrations of chloride and nitrate in the region’s groundwater. Zone 1 in the north possesses the lowest levels of karstification, anthropization, and contamination, while zone 2 in the central region has the highest levels and zone 3 in the south ranging in-between (except for stronger karstification). The delimitation of management zones will contribute to the development and implementation of optimized zone-specific groundwater preservation and restoration strategies. Full article

Oases in arid regions are critical ecosystems, providing essential ecological, agricultural, and socio-economic functions. However, urbanization and climate change increasingly threaten their sustainability. This study examines land cover (LULC) and land surface temperature (LST) dynamics in four representative North African oases: Tolga (Algeria), Nefta (Tunisia), Ghadames (Libya), and Siwa (Egypt) over the period 2000–2023, using Landsat satellite imagery. A three-step analysis was employed: calculation of NDVI (Normalized Difference Vegetation Index), NDBI (Normalized Difference Built-up Index), and LST, followed by supervised land cover classification and statistical tests to examine the relationships between the studied variables. The results reveal substantial reductions in bare soil (e.g., 48.10% in Siwa) and notable urban expansion (e.g., 136.01% in Siwa and 48.46% in Ghadames). Vegetation exhibited varied trends, with a slight decline in Tolga (0.26%) and a significant increase in Siwa (+27.17%). LST trends strongly correlated with land cover changes, demonstrating increased temperatures in urbanized areas and moderated temperatures in vegetated zones. Notably, this study highlights that traditional urban designs integrated with dense palm groves significantly mitigate thermal stress, achieving lower LST compared to modern urban expansions characterized by sparse, heat-absorbing surfaces. In contrast, areas dominated by fragmented vegetation or seasonal crops exhibited reduced cooling capacity, underscoring the critical role of vegetation type, spatial arrangement, and urban morphology in regulating oasis microclimates. Preserving palm groves, which are increasingly vulnerable to heat-driven pests, diseases and the introduction of exotic species grown for profit, together with a revival of the traditional compact urban fabric that provides shade and has been empirically confirmed by other oasis studies to moderate the microclimate more effectively than recent low-density extensions, will maintain the crucial synergy between buildings and vegetation, enhance the cooling capacity of these settlements, and safeguard their tangible and intangible cultural heritage. Full article

This study introduces Edible Streets as a distinct and scalable model of community-led urban food growing, specifically investigating the drivers and barriers to the initiative. Unlike traditional urban food-growing initiatives, Edible Streets explores the integration of edible plants into street verges and footpaths with direct community involvement of the people who live/work in a street. This study contributes new knowledge by evaluating Edible Streets through the COM-B model of behavioural change, through policy and governance in addition to behaviour change, and by developing practical frameworks to facilitate its implementation. Focusing on Oxford, the research engaged residents through 17 in-person interviews and 18 online surveys, alongside a stakeholder workshop with 21 policymakers, community leaders, and NGO representatives. Findings revealed strong motivation for Edible Streets, driven by values of sustainability, community resilience, and improved well-being. However, capability barriers, including knowledge gaps in gardening, land-use policies, and food preservation, as well as opportunity constraints related to land access, water availability, and environmental challenges, hindered participation. To address these, a How-to Guide was developed, and a pilot Edible Street project was launched. Future steps include establishing a licensing application model to facilitate urban food growing and conducting a Post-Use Evaluation and Impact Study. Nationally, this model could support Right to Grow policies, while globally, it aligns with climate resilience and food security goals. Locally grown food enhances biodiversity, reduces carbon footprints, and strengthens social cohesion. By tackling key barriers and scaling solutions, this study provides actionable insights for policymakers and practitioners to create resilient, equitable urban food systems. Full article

Century-long land-use practices have a profound impact on soil physical and chemical properties, with direct implications for soil health and agricultural sustainability. This study aimed to assess the effects of four contrasting land uses—remnant vegetation, pasture, cultivated areas, and loafing areas—on the physical and chemical properties of Red Ferrosols in the Toowoomba region, Queensland, Australia. Soil samples were collected from upper and lower slope positions for each land use. Physical properties, including bulk density, porosity, water retention, and permeability, as well as chemical properties such as organic carbon, nitrogen, phosphorus, and potassium, were analysed. The results showed that remnant vegetation preserved the most favourable soil conditions, with lower bulk density, higher porosity, and greater water retention. Cultivated areas exhibited significant soil degradation, marked by compaction, reduced infiltration, and depleted organic matter. Loafing areas displayed localised nutrient enrichment but higher compaction due to livestock trampling. Pastures maintained intermediate conditions, retaining some beneficial soil characteristics. These findings emphasise the critical need for sustainable land management strategies to protect soil structure and function, supporting the long-term productivity and resilience of Red Ferrosols. Full article