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Multi-scale feature mixed attention network for cloud and snow segmentation in remote sensing images
Get PDFThe coexistence of cloud and snow is very common in remote sensing images. It presents persistent challenges for automated interpretation systems, primarily due to their highly similar visible light spectral characteristic in optical remote sensing images. This intrinsic spectral ambiguity significantly impedes accurate cloud and snow segmentation tasks, particularly in delineating fine boundary features between cloud and snow regions. Much research on cloud and snow segmentation based on deep learning models has been conducted, but there are still deficiencies in the extraction of fine boundaries between cloud and snow regions. In addition, existing segmentation models often misjudge the body of clouds and snow with similar features. This work proposes a Multi-scale Feature Mixed Attention Network (MFMANet). The framework integrates three key components: (1) a Multi-scale Pooling Feature Perception Module to capture multi-level structural features, (2) a Bilateral Feature Mixed Attention Module that enhances boundary detection through spatial-channel attention, and (3) a Multi-scale Feature Convolution Fusion Module to reduce edge blurring. We opted to test the model using a high-resolution cloud and snow dataset based on WorldView2 (CSWV). This dataset contains high-resolution images of cloud and snow, which can meet the training and testing requirements of cloud and snow segmentation tasks. Based on this dataset, we compare MFMANet with other classical deep learning segmentation algorithms. The experimental results show that the MFMANet network has better segmentation accuracy and robustness. Specifically, the average MIoU of the MFMANet network is 89.17%, and the accuracy is about 0.9% higher than CSDNet and about 0.7% higher than UNet. Further verification on the HRC_WHU dataset shows that the MIoU of the proposed model can reach 91.03%, and the performance is also superior to other compared segmentation methods
Mean wind speed profile parameterisation over an urban canopy with building height variability
No full textThis study builds a parameterisation strategy for the vertical profile of the horizontal mean wind speed over urban canopies with building height variability (BHV). An intermediate layer (IL) is introduced between the layers deep inside and far above the urban canopies, where exponential (EL) and logarithmic layers (LL) are assumed, respectively. Based on the momentum flux budget, in the IL we propose a linear velocity profile as a simple estimation. Input parameters reflect the BHV geometry (namely the standard deviation and average building height, the highest and lowest building height, and the frontal and plan area indices). Physical parameters such as the bulk drag coefficient and the correction factor for eddy diffusivity in the IL are parametrised using a database containing large eddy simulations (LES) of flows through various random height block arrays covering a wide range of geometries. Our new fully analytical model provides wind speed profiles spanning the top of the surface layer to the ground. There is good agreement to a LES database with realistic urban cases for both mean wind speed and the momentum flux. Analysis of a correction strategy for thermal stratification reveals qualitative consistency with observations in the literature under weakly stable and unstable conditions. This model provides in-canopy wind information, data that are essential for many applications such as estimating thermal sensation at the pedestrian level and evaluating energy consumption in urban agglomerations under changing climate
Farmers’ perceived financial and non-financial costs of their biodiversity measures – exploring viewpoints with Q-methodology
Get PDFFarmers’ willingness to continue participation in their agri-environmental program and maintain biodiversity
measures in the long term is shaped by the nature of costs they perceive during implementation. Research
emphasizes the need to account for both financial and non-financial costs, but holistic assessments which both
put these costs into relation and account for farmers’ varied perceptions remain lacking. To capture the plurality
of perceived costs, as well as the plurality of viewpoints farmers have of these costs, we applied Q-methodology
across four European study areas. Building upon scientific literature and expert interviews, we defined a Q-set
comprising 41 cost aspects from four dimensions, i.e. financial, management-related, emotional and social costs.
34 farmers with different socio-demographic and farming background Q-sorted these cost aspects. Elicited
viewpoints showed that participating farmers are either most impacted by perceived governance-related uncertainty, unproductiveness, lack of support, administrative burden, underpayment, or social non-conformity.
Findings give indications of highly diverse needs when implementing a biodiversity measure, within and
across study areas. The systematic insights into farmers’ cost perceptions and the structure established for this Qstudy can guide research and policymakers who aim to comprehensively explore and evaluate well-targeted ways
to improve farmers’ experiences of biodiversity measures within agri-environmental programs
Oceanic drivers of UK summer droughts
Get PDFUK droughts are projected to become more frequent under climate change, reinforcing the need to understand their underlying causes. Our study examines oceanic drivers of UK summer droughts and the associated teleconnection pathways. Specifically, we evaluate statistical links between standardized precipitation and streamflow indices for the UK and two North Atlantic Sea surface temperature (SST) patterns which have previously been linked to the influx of freshwater into the subpolar region. Our findings reveal that the North Atlantic SST influences UK hydrology up to 1.5 years in advance by altering the position of the North Atlantic Current, which is coupled to the location of the North Atlantic summer jet stream. The long lead time of this teleconnection pathway can inform UK drought forecasting across seasonal to interannual timescales and ultimately contribute to the advancement of sustainable water resource management in the face of increasing drought risks in the UK
Accounting for non-exposure bias, self-selection, and heterogeneity in production technology: evidence from rice cultivation in Ghana
Get PDFThis study applied stochastic metafrontier whilst correcting for non-exposure and selection bias to assess the adoption of improved rice varieties on output and technical efficiency of Ghanaian households. Varietal awareness was estimated to account for non-exposure bias and adoption using treatment effect. The exposure and adoption rates of improved rice varieties were 82.5% and 67.2%. Adoption was influenced by rice projects, agricultural extension, higher yield motive, and irrigated production. Application of herbicides, fertilizer, seed, labour and farm size raised rice output amongst adopters. The difference in metafrontier technical efficiency of adopters (42.7%) and non-adopters (44.5%) was statistically insignificant, albeit adopters had higher metatechnology ratio (0.909) compared with nonadopters (0.785). Therefore, adopters applied the best production technology than nonadopters. Weeding twice with herbicides, managing plot water levels and agricultural extension raised the technical efficiency amongst adopters. This study recommends cultivation of improved rice varieties whilst improving technical efficiency
Associations between local-scale soil and tree context factors and acute oak decline (AOD): plant-soil feedbacks and the cause-effect conundrum
Get PDFBackground and aims: Acute oak decline (AOD), a decline syndrome affecting mature oaks, involves bacterial pathogens which likely act as opportunists under host stress. Trees displaying symptoms (bleeding cankers) appear in localized clusters, not whole stands. This study investigates the potential involvement of local-scale factors, in interaction with large-scale environmental drivers, in influencing onset and progression of AOD.
Methods: AOD-symptomatic (n=30) and asymptomatic trees (n=30) across three UK oak woodlands were assessed for tree characteristics, their surrounding context, and soil properties.
Results: Tree health status was linked to significant differences in soil and tree properties across sites. Symptomatic trees exhibited greater loss of crown density, lower local stand (0-20 m) basal area and shallower depth to gleying. Significant differences in soil properties included lower concentrations of Olsen P, total N, and exchangeable Mg in symptomatic trees, alongside higher exchangeable Fe, especially at 40–50 cm depth. Depth to gleying and exchangeable Fe were identified as the most influential predictors of AOD.
Conclusions: AOD symptomatic trees may experience seasonal soil water saturation closer to the surface compared to asymptomatic trees, resulting in a higher proportion of their roots being exposed to an anoxic, iron-reducing environment. This study is the first to report such an association between gleying depth, likely seasonal water saturation, and symptom status for AOD. It is unclear whether water balance and associated soil nutrient variations are predisposing factors or consequences of declining tree health, though the identified local-scale factors likely contribute to AOD. A feedback loop is conceptualised where declining tree health worsens soil conditions, creating a negative cycle that accelerates tree decline
The role of intentional exploration in processing difficult moments
Get PDFThe capacity to regulate emotions is essential for well-being (Houle & Philippe, 2020; Roth
& Benita, 2023b; Ryan et al., 2015b; Weinstein et al., 2011). The research presented in my
thesis examined the role of intentional exploration of emotional experiences, a form of
regulation that is motivated and energised by active interest and curiosity (Roth et al., 2019),
in processing difficult moments in community samples. The first empirical chapter (Chapter
2) investigated three emotion regulatory styles (integrative emotion regulation, suppression,
and emotion dysregulation) and their associations with adaptive and maladaptive coping
strategies in a one-month longitudinal study. It then contrasted two integrative emotion
regulation forms, intentional exploration and receptive attention (receptive and
nonjudgmental attention of emotional experiences; Roth et al., 2019), in daily well-being
through a seven-day daily diary study. Chapter 3 reports three studies that investigated
interest-taking and trait-level intentional exploration in processing shame experiences. The
current literature indicates that shame is associated with avoidance tendencies (McLachlan et
al., 2011; Schmader & Lickel, 2006), but can be countered by interest-taking, an essential
quality of intentional exploration that can help individuals connect with themselves again
through self-reflection, insight, and introspection. Studies 3-5 attempted to manipulate
interest when writing about recent shame experiences. Chapter 4 presents three additional
studies that explored how individual differences in intentional exploration influence solitude
experiences (e.g., rumination, introspection, and peaceful affect) and different solitude forms
(distracted vs. private). In these chapters, intentional exploration was associated with (1)
adaptive coping and daily well-being, (2) constructive tendencies about shame experiences
but not lower shame, and (3) self-connection in solitude. The implications of the findings and
potential future studies are discussed
Approaching future flight: urban life and design in the drone age
No full textFrom infrastructure inspection to emergency services, drones increasingly feature in UK skies. Drones are celebrated as enabling diverse applications and are associated with social, economic, and sustainability benefits. To this end, a 2022 UK Government ambition statement outlined aims for commercial drones to be ‘commonplace by 2030’. While the majority of operations are conducted by ground-based operators and flown within Visual Line of Sight, appetite is growing for Beyond Visual Line of Sight (BVLOS) drone flight, which does not require visual reference and relies on alternative operational mitigations for collision avoidance. Following the association of BVLOS with economic and efficiency opportunities, initiatives such as ‘Project Skyway’, the world’s longest BVLOS drone superhighway poised to connect 165-miles of airspace above six UK towns and cities, have emerged. Through the lens of Project Skyway, this chapter examines diverse understandings of future flight by unpacking different methods deployed in its
investigation. From routinised drones prompting visual and noise disruption concerns to the drone’s reliance on digital and physical infrastructures, such emergent and anticipated
Advanced Air Mobility (AAM) technologies are variously poised to impact urban populations and built environments, and can be fruitfully interrogated at the interdisciplinary intersection of geography and design
Central bank digital currency rhetoric and stablecoin market responses
No full textThis paper examines how central-bank digital currency (CBDC) rhetoric affects the stablecoin market. Using data from 2020 to 2023, we analyse the effects of central-bank speeches on stablecoin supply and retail attention, controlling for central-bank-specific factors and other shocks. We find that pro-CBDC communication is associated with declines in stablecoin supply, while at the same time retail attention to stablecoins increases. Our results suggest that central-bank CBDC rhetoric can meaningfully influence stablecoin dynamics through anticipatory market responses, including information, signalling, and regulatory-expectations, even in the absence of fully implemented CBDCs
Key physicochemical parameters influencing reactive species in Plasma‐Processed‐Air (PPA) originated from microwave discharge
Get PDFFourier transformation infrared (FTIR) spectroscopy was used to identify the antimicrobial chemical composition of plasma
processed air (PPA) generated by a microwave plasma source—MidiPLexc. NO was found to be the first product with maximum
concentration of 1030 ppm. NO2 was the dominant long‐living species with maximum concentration of 10 520 ppm, which was
in equilibrium with its dimer—N2O4. Key physicochemical parameters influencing the concentrations were identified. Elevated
input power mainly promoted NO2 generation and 1.5 SLM was determined to be the critical flow rate for the maximum NO2
yield. NO2 concentration was reduced by 40% under humid condition with 50W power input. A prediction model of NOx
generation was made based on specific input energy (SIE)