Shaded Areas Research Articles

PRODUCTION OF SWEET POTATO (Ipomoea batatas (L.) Lam) IN AGROFORESTRY SYSTEM: CASE STUDY OF AN EXPERIMENTAL UNIT IN SANTARÉM, PARÁ, BRAZIL

Agroforestry systems (AFS) play a key role in recovering degraded areas and restoring fragmented landscapes, enabling the diversification of species that can be cultivated simultaneously. In this context, the introduction of short-cycle crops, such as sweet potato (Ipomoea batatas (L.) Lam), in agroforestry systems is a viable and affordable option for income generation due to low production costs and the relatively short cycle of this crop. A species of the Convolvulaceae family, sweet potatoes are recommended for hot climates. In this scenario, the present study aims to evaluate the production of sweet potatoes in different agroforestry arrangements. The experiment was conducted at the Experimental Farm of the Federal University of Western Pará in Santarém, State of Pará, Brazil. Sweet potato was cultivated in agroforestry systems in a completely randomized design, with three plots in each treatment (full sun, African mahogany reforestation, and teak reforestation). The results showed that, in the specific conditions of this study, sweet potato did not adapt to cultivation in shaded areas. The highest production was in full sun, where the consortium with forest species still does not provide shading for cultivation. These findings highlight the importance of considering the specific characteristics of sweet potato and its sunlight needs when planning and implementing agroforestry systems. Understanding these results contributes to making informed decisions regarding the development of cultivation and management strategies aiming to optimize sweet potato production in agroforestry systems.

Maskless fabrication of quasi-omnidirectional V-groove solar cells using an alkaline solution-based method

Silicon passivated emitter and rear contact (PERC) solar cells with V-groove texture were fabricated using maskless alkaline solution etching with in-house developed additive. Compared with the traditional pyramid texture, the V-groove texture possesses superior effective minority carrier lifetime, enhanced p–n junction quality and better applied filling factor (FF). In addition, a V-groove texture can greatly reduce the shading area and edge damage of front Ag electrodes when the V-groove direction is parallel to the gridline electrodes. Due to these factors, the V-groove solar cells have a higher efficiency (21.78%) than pyramid solar cells (21.62%). Interestingly, external quantum efficiency (EQE) and reflectance of the V-groove solar cells exhibit a slight decrease when the incident light angle (θ) is increased from 0° to 75°, which confirms the excellent quasi omnidirectionality of the V-groove solar cells. The proposed V-groove solar cell design shows a 2.84% relative enhancement of energy output over traditional pyramid solar cells.

A Simulation Study of the Impact of Urban Street Greening on the Thermal Comfort in Street Canyons on Hot and Cold Days

The urban heat island effect has become a widely concerning issue worldwide. Many researchers have made great efforts to improve the summer thermal comfort of urban street canyons by optimizing street greening. Relatively less research has focused on how to improve the thermal comfort of street canyons by optimizing street greening during cold days. Many researchers have proposed strategies to improve the summer thermal comfort of street canyons using road greening. This may have a significant negative impact on the winter thermal comfort of street canyons due to the lack of consideration of the impact on hot and cold days simultaneously, especially when the road green space is mainly composed of evergreen tree species. We aimed to explore the impacts of urban street greening on thermal comfort on hot and cold days at the same time. We used Zhutang West Road in Changsha, China, as an example and built six different models to explore the impacts of the street vegetation types, number of street trees, tree heights, crown widths, and Leaf Area Index on the thermal comfort of the street canyon. In addition, we also considered the impact of different building features and wind directions on the thermal comfort of the street canyon. We employed ENVI-met (version 5.5.1) to simulate different urban street greening models. The results show that the model with a high tree canopy density, tall trees, large and dense crowns, and sufficient building shade has good thermal comfort on hot days (the average physiological equivalent temperature (PET) is 31.1 °C for the study period) and bad thermal comfort on cold days (the PET is 13.3 °C) when it is compared with the other models (the average PETs are 36.2 °C, 31.5 °C, 41.5 °C, 36.2 °C, and 35.5 °C, respectively, on hot days and for other models). In addition, the model with a very large number of short hedges has a positive impact on thermal comfort during hot days (the PET is 31.1 °C). The PET value of another comparable model which does not have hedges is 31.5 °C. Even if the model with a small building area has good ventilation, the small building shade area in the model has a more obvious impact and the model has relatively good thermal comfort during cold days (the PET is 14.2 °C) when it is compared to models with bigger building areas (the PET is 13.9 °C). In summer, when the wind is parallel to the direction of the street canyon, the wind speed in the street canyon is high and the model has relatively good thermal comfort (the PET is 35.5 °C) compared with another model which has different wind direction and lower wind speed at the street canyon (the PET is 36.2 °C). In winter, when the wind is perpendicular to the direction of the street canyon, buildings and trees have a strong windproof effect and this is beneficial to the improvement of thermal comfort (the PET is 15.3 °C for this model and 13.9 °C for another comparable model). This research lays a solid foundation and encourages people to think about the impact of building and tree composition and configuration on the thermal comfort of street canyons during hot and cold days simultaneously.

Efficacy of Violet-Blue (405 nm) LED Lamps for Disinfection of High-Environmental-Contact Surfaces in Healthcare Facilities: Leading to the Inactivation of Microorganisms and Reduction of MRSA Contamination.

Effective disinfection procedures in healthcare facilities are essential to prevent transmission. Chemical disinfectants, hydrogen peroxide vapour (HPV) systems and ultraviolet (UV) light are commonly used methods. An emerging method, violet-blue light at 405 nm, has shown promise for surface disinfection. Its antimicrobial properties are based on producing reactive oxygen species (ROS) that lead to the inactivation of pathogens. Studies have shown significant efficacy in reducing bacterial levels on surfaces and in the air, reducing nosocomial infections. The aim of this study was to evaluate the antimicrobial effectiveness of violet-blue (405 nm) LED lamps on high-contact surfaces in a hospital infection-control laboratory. High-contact surfaces were sampled before and after 7 days of exposure to violet-blue light. In addition, the effect of violet-blue light on MRSA-contaminated surfaces was investigated. Exposure to violet-blue light significantly reduced the number of bacteria, yeasts and moulds on the sampled surfaces. The incubator handle showed a low microbial load and no growth after irradiation. The worktable and sink showed an inconsistent reduction due to shaded areas. In the second experiment, violet-blue light significantly reduced the microbial load of MRSA on surfaces, with a greater reduction on steel surfaces than on plastic surfaces. Violet-blue light at 405 nm has proven to be an effective tool for pathogen inactivation in healthcare settings Violet-blue light shows promise as an additional and integrated tool to reduce microbial contamination in hospital environments but must be used in combination with standard cleaning practices and infection control protocols. Further research is needed to optimise the violet-blue, 405 nm disinfection method.

Long-term recurrence of new-onset post-operative AF in cardiac surgery patients as detected by an implantable loop recorder: a systematic review and individual participant data meta-analysis

Abstract Introduction New-onset atrial fibrillation (AF) occurs in 25-50% of patients after cardiac surgery. For some patients, post-operative AF (POAF) is thought to be a transient entity, while in others it represents a first presentation of paroxysmal or persistent AF. The long-term rate of AF recurrence in patients with POAF is not well defined. Objective To estimate the recurrence of AF in patients who had new-onset POAF following cardiac surgery as evaluated with an implantable loop recorder (ILR). Methods We searched MEDLINE, Embase and Cochrane CENTRAL to August 18, 2022 for studies of adult patients without a history of AF, who had POAF detected following cardiac surgery and received an ILR. We defined AF occurring in the first 30 days after surgery as POAF. We defined AF occurring beyond 30 days after surgery as AF recurrence. We contacted authors of eligible studies with a request to contribute individual participant time-to-event data on AF recurrence and participant demographics at the study level. When individual data were not available, we estimated events from figures in published study records. We constructed a Kaplan-Meier curve illustrating the time to first AF recurrence, with 95% confidence intervals (CIs). Results From 8111 screened records, we identified 8 eligible studies (Table 1). All studies were single-centre cohorts from 7 countries including the United States of America (2), Canada, Denmark, Israel, The Netherlands, Russia and Sweden. Two studies defined AF recurrence as lasting 30 seconds, four defined AF recurrence as lasting at least 2 minutes, one defined AF recurrence as lasting at least 5 minutes and one defined AF recurrence as lasting at least 6 minutes. We received data for 6 studies and estimated events for one study; data were not available from one study. We pooled data from a total of 186 participants, with a median follow-up of 1.7 (interquartile range (IQR): 1.3 – 2.8) years. Overall, 19.7% of participants were female, 79.8% of participants had isolated CABG, and the median (IQR) CHA2DS2-VASc was 3 (1 – 6). Rates of AF recurrence beginning after the 30-day post-operative period were: 15.1% (95% CI 10.5% – 21.2%) at 3 months, 23.9% (95% CI 18.1% – 31.0%) at 6 months, 30.7% (95% CI 24.1% – 38.1%) at 12 months and 39.2% (95% CI 32.0% – 47.0%) at 18 months (Figure 1, wherein the shaded area indicates the 95% CI). Conclusions For patients with new-onset POAF following cardiac surgery, AF recurrence, as detected by an ILR, is common, with approximately 1 in 3 experiencing recurrence in the first year after surgery. The optimal strategy for monitoring for AF recurrence and its clinical sequelae in this population remains uncertain.Figure 1:Incidence of AF RecurrenceTable 1:Study Characteristics Table

Strategi Promosi Pemasaran Ikan Koi Di CV. Agra Koi Farm Blitar

The main problem in this research is how to implement the marketing promotion strategy for koi fish by CV. Agra Koi Farm Blitar uses SWOT Analysis, aiming to find out and describe the right promotional strategy using SWOT Analysis. This can be seen from the lack of activity or promotional activities carried out by CV. Agra Koi Farm Blitar and many competitors in the same business field. The type of research used is qualitative research. The data collection techniques used were observation, documentation, interviews and literature study. The instruments in this research are the researcher himself, interview guidelines, documentation and field notes. The analysis technique used is SWOT Analysis using the SWOT Matrix. Based on the results of the IFAS and EFAS matrix analysis, it is proven that the strength value is greater than the weakness value, namely with a difference of (+) 0.56. Meanwhile, the opportunities value is greater than the threats value, namely with a difference of (+) 0.77. The SWOT diagram shows that the shaded area is in quadrant I. The strategy that must be implemented in this condition is to support aggressive growth policies (Grow Oriented Strategy). Under these conditions, the most appropriate strategy was implemented by CV. Agra Koi Farm Blitar uses the SO strategy, namely a strategy that utilizes strengths to manage existing opportunities.

Performance Analysis of Novel Solar PV Array Configurations with Reduced Tie Interconnection to Extract Maximum Power under Partial Shading

The non-uniform irradiation pattern causes the partial shading effects and decreases the performance of the solar Photovoltaic (PV) array. The effect of uneven shading condition depends on its pattern and area. The PV array’s performance is determined by the cross ties that are connected within the array. This research proposes eight different PV array tie interconnection configurations to obtain the maximum power output under uneven insolation conditions. Experimental analysis is done in the PV array consists of 16 numbers of 10 W PV panels which has a total capacity of 160 W. The practical results reveal that the losses due to partial shading are influenced by the shade pattern, shade area, and the placement of the cross ties. Overall, among the conventional configurations, the hybrid bridge link total cross tied interconnection pattern produced the best results, followed by the hybrid series parallel total cross tied and bridge link patterns. In the proposed configurations, the plus tie configuration outperformed the others in maximum of the partial shading scenarios. In general, the PLT configuration demonstrated an average power efficiency increase of 19.17%, 8.37%, and 8.28% compared to the series parallel, hybrid series parallel total cross-tied, bridge link, and bridge link total cross-tied configurations, respectively. The effectiveness of the proposed configurations is validated by the practical verifications.

KARAKTERISASI DAN OPTIMASI EMULGEL NA DIKLOFENAK DENGAN METODE SIMPLEX LATTICE DESIGN

Diclofenac Na is an NSAID class of drugs that functions to treat pain and inflammation of rheumatoid arthritis, osteoarthritis or joint disease. The aim of this study is to investigate the effect of carbopol 940, HPMC K15M and propyleneglycol variations on the emulgel physical properties, carbopol concentration, HPMC, propyleneglycol to produce an optimum formula.The method used in this optimization is Simplex Lattice Design. The independent variables which include carbopol 490 , HPMC K15M , propylene glycol were then included in the expert design to obtain 16 runs. Each formula was tested for viscosity, spreadability, adhesion, pH, diffusivity and physical stability. Each parameter has a contour plot and by superimposing it can be determined the shaded area which is the area of ​​the optimum formula. The optimum formula was carried out using a one sample t-test with a 95% confidence level. Based on the results of superimposed superimposed graphic observations for the manufacture of diclofenac narium emulgel with test parameters including spreadability, viscosity, adhesion, PH, diffusion ability and stability test, the composition of Carbobol 940 0.5 - 1.22%, HPMC K-15M 3.24 - 3.77 Propylene glycol 5 - 6.26%. The results of the t-test showed that the Simplex Lattice Design equation in the formula showed results that were not significantly different, this shows the significance value of the results before treatment with treatment results > 0.05. This shows that the equation is valid and the stability test is stable.

62 The Impact of Hair Coat Color on Body Temperature in Beef Cattle

Abstract Ambient temperature has a fundamental role in animal health and performance. Selecting for coat color may improve animal productivity and welfare through management and breeding decisions. The thermoneutral zone of cattle, 0°C - 25°C, is characterized as the range in ambient temperature that does not require cattle to expend energy to maintain core body temperature. When the ambient temperature is above or below these values, cattle must expend energy to keep their body temperature in homeostasis resulting in a reduction in efficiency. A proper herd management plan to mitigate heat stress can increase efficiency and decrease mortality in serious cases. Registered Hereford and commercial black cows (n = 39; average 4 yr of age) were placed in a 23-ha pasture, to determine if coat color affects internal body temperature. Cattle were on a typical fescue dominated pasture located in Mountain Grove, MO, with areas of shade and one pond centralized in the pasture. Cattle were divided into treatments based on hair coat color: black (n =13) or red (n = 26). Using temperature data loggers, vaginal temperatures were recorded in 5-min intervals during a 14-d period in Mid-July 2022, and combined into 6-hour timing intervals, A = 0400-1000 h, B = 1001-1600 h, C = 1601-2200 h, and D = 2201-0359 h. Environmental temperature data loggers were suspended in two locations of partial sun to record ambient temperature. In addition, the Mountain Grove weather station operated by the University of Missouri Extension provided a daily data archive that recorded wind speed, total precipitation, maximum and minimum air temperature. Throughout the study, the mean environmental temperature was 34.4°C and ranged from 19.5°C to 40.2°C. Temperature data were evaluated using the Glimmix procedure of SAS and pairwise comparisons between timepoints were determined utilizing the GLM procedure of SAS. Differences were considered significant at P = 0.05. Black-haired cattle were warmer at all intervals (P ≤ 0.04) with temperature differences between the treatments of 0.07, 0.10, 0.03, and 0.09°C for timepoints A, B, C and D, respectively (Table 1). Based on our results black-hided cattle get warmer earlier in the day and take longer to dissipate heat than those with red hair coats.

High prevalence of pathogenic Eimeria spp. and the main risk factors associated with infection in goats from a semiarid region of Northeastern Brazil.

This study aimed to analyze the epidemiology of infections caused by Eimeria spp. in goats bred in an extensive production system in Northeast Brazil. To this end, an epidemiological survey was performed, wherein 350 fecal samples were collected from goats ranging from 3months to 8years old across 30 farms. The number of oocysts per gram of feces (OPG) was counted using the Mini-FLOTAC method. Species were identified based on their morphological and morphometric characteristics. Frequencies between animal categories were assessed using the chi-square test and known risk factors after multivariate analysis. Eimeria oocysts were found in 99.4% (346/348) of samples and 100% (30/30) of the farms. The OPG was influenced by the age of the animals; therefore, young goats (up to 6months old) eliminated more oocysts (2302.6 + 5454.8) than adult goats (881.7 + 1551.5). Three pathogenic species were identified, with two demonstrating a high prevalence: Eimeria arloingi (88.83%) and Eimeria christenseni (44.7%), in addition to Eimeria caprina (3.72%). In the study, the habit of ground feeding and the use of cisterns as water sources were identified as risk factors, with odds ratios of 4.04 and 9.82, respectively. However, cleaning facilities at shorter intervals was a protective factor (OR = 0.19). We concluded that there was a high prevalence of Eimeria infection in goats bred in extensive production systems, even those in semiarid regions. This high prevalence can be attributed to the congregation of animals in shaded areas and the substantial accumulation of fecal matter at night.

Performance assessment of compound parabolic concentrating photovoltaic system based on optical-thermal-electrical-environmental coupling

Based on established optical-thermal-electrical-environmental coupling model and proposed method for calculating electrical efficiency, the effects of tilt angle (θ) on the optical performance, thermal performance and electrical performance of compound parabolic concentrating photovoltaic (CPC-PV) system were numerically investigated by using the coupled Monte Carlo ray tracing (MCRT) and finite volume method (FVM). The results show that with the increase of θ, the peak irradiation flux on the PV panel surface increases sharply. When θ is larger than the critical angle, the shadow area appears and the distribution uniformity of irradiation flux decreases rapidly. Under natural convection condition, increasing θ reduces the distribution uniformity of temperature on the silicon elements with a maximum temperature difference of 120.93 °C at the same position. While, the air average flow velocity around PV panel and reflector surfaces decreases, and the maximum flow velocity appears on reflector surface. Radiative heat loss is dominant in CPC-PV system, and convective heat transfer on the glass surface has a greater impact on the combined heat transfer than that on the TPT surface. From the aspects of values and variation trends, the electrical efficiency calculated by using traditional empirical formula defies the facts. The regional discrete integral method proposed in this study accounts for the effects of shaded areas and non-uniform temperatures on electrical performance. The maximum difference between the electrical efficiency calculated by using the present method and the traditional empirical formula is 10.59 %.

Enhancing solar photovoltaic modules quality assurance through convolutional neural network-aided automated defect detection

Detecting cracks in solar photovoltaic (PV) modules plays an important role in ensuring their performance and reliability. The development of convolutional neural networks (CNNs) has introduced a game-changing dimension in the detection of defects in PV modules. This paper proposes an automated defect detection method for PV, by leveraging custom-designed CNN to accurately analyse electroluminescence (EL) images, identifying defects such as cracks, mini-cracks, potential induced degradation (PID), and shaded areas. The proposed system achieves a high level of validation accuracy of 98.07%, reducing manual inspection demands, enhancing quality standards, and saving costs. The system was validated in a case study for PV installations faulty with PID, where it identified all defective modules with a high degree of precision of 96.6%, surpassing existing methods. This methodology holds promise for revolutionizing PV industry quality control, improving module reliability, and supporting sustainable solar energy growth.

Underground hydrogen storage in Germany: Geological and infrastructural requirements

Hydrogen storage is crucial for the success of the hydrogen economy. In addition to storage tanks and pipes the geological subsurface could also offer cost-effective solutions for storing large quantities of hydrogen in salt caverns, aquifers, and depleted hydrocarbon fields. However, experience with underground hydrogen storage is limited to salt caverns, which have size and space limitations. In this contribution we therefore define positive indicators for pore storage systems and estimate storage capacities based on national CO2 and natural gas storage assessments in Germany.
 With a focus on the geological assessment of potential storage horizons, we first define positive and cautionary indicators for safe storage operations on the basis of a thorough literature review, including theoretical and experimental studies. For example, we find that optimal storage conditions in terms of energy content and hydrogen quality are found in sandstone reservoirs in the absence of carbonate and iron-bearing accessory minerals at a depth of approximately 1100 m and a temperature of at least 40 °C. Porosity and permeability of the reservoir formation should be at least 20 % and 5x10-13 m2 (~500 mD), respectively. The pH of the brine should moreover fall below 6 and the salinity should exceed 100 mg/L in order to limit microbial activities and hydrogen solubility in brine water.
 
 Second, we estimate hydrogen storage capacities based on published natural gas and CO2 storage volumes [1,2] and their respective physical properties. These estimates provide an upper bound that is independent of the positive and cautionary indicators defined in here. Nevertheless, we show that up to 8 billion cubic metres, or 29 TWh energy equivalent of hydrogen could be stored in underground gas storage facilities if all natural gas were to be replaced by hydrogen (Figure 1). In addition, saline aquifers could offer storage capacities of 81.6 to 691.8 Mt of hydrogen, based on CO2 storage assesments [2]. This corresponds to 3.2 to 27.3 PWh of hydrogen energy equivalent. The majority of which (~95 %) is located in the North German Basin. Fig. 3 shows the distribution of all pore storages (active and inactive; red and grey dots) and saline aquifers (green shaded areas) comparing it to the planned grid expansion initiative IPCEI (important projects of common European interests) [3]. These capacities would meet predicted storage requirements in Germany considering industrial, transport, and heating demands of 34 to 667 TWh (final hydrogen demand in 2050) many times over [4].
 
 We conclude that pore storage systems could play a crucial role in the future German hydrogen infrastructure, especially in regions with large industrial hydrogen demand and likely hydrogen imports via pipelines and ships. We therefore recommend that future research focus on assessing the technical storage potential of these sites and their compatibility with planned hydrogen infrastructures and industrial demand.

The effects of warm weather on children’s outdoor heat stress and physical activity in a preschool yard in Gothenburg, Sweden

Hot weather conditions can have negative impacts on the thermal comfort and physical activity of vulnerable groups such as children. The aim of this study is to analyze the effects of warm weather on 5-year-old children’s thermal comfort and physical activity in a preschool yard in Gothenburg, Sweden. In situ measurements were conducted for 1–1.5 h in the early afternoon on 8 days in May, June, and August of 2022. The thermal comfort and physical activity was estimated with GPS-tracks, heart rate monitors, and step counts and compared to observed weather conditions. Results show that physical activity decreases under warmer weather conditions, depicted by a decrease in distance moved, step counts, and highest registered pulse. Moreover, on warm days, the children avoid sunlit areas. For 50% or more of the time spent in sunlit areas, the children are exposed to cautious levels of heat. In shaded areas, on the other hand, the children are less exposed, with five out of 8 days having 50% or more of the time at neutral levels. The study demonstrates the importance of access to shaded areas in preschool yards where children can continue their active play while simultaneously maintaining a safe thermal status.

Characterization of Thermal Patterns Using Infrared Thermography and Thermolytic Responses of Cattle Reared in Three Different Systems during the Transition Period in the Eastern Amazon, Brazil.

In the Lower Amazon mesoregion, there are basically three types of production systems: the traditional (without shade and no bathing area), the silvopastoral (with shade and no bathing area), and the integrated (with shade and bathing area). It is considered that the type of production system influences the thermal comfort and productivity of cattle, so this research aims to evaluate the influence of these three types of production systems on the thermoregulation of Nellore cattle. The experiment was carried out on a rural property for raising cattle, located in Mojuí dos Campos, Pará, Brazil, during the transition period (June/July). Thirty bovine males (not castrated, aged between 18 and 20 months, average weight of 250 ± 36 kg, body condition score of 3.5, clinically healthy) were randomly divided into three groups: Silvopastoral System-SS (n = 10), Traditional System-TS (n = 10), and Integrated System-IS (n = 10). Climate variables were collected (air temperature (AT °C), relative humidity (RH %), wind speed (WS, m/s), solar radiation (SR), black globe temperature (BGT °C), and physiological parameters, such as respiratory rate (RR) and rectal temperature (RT)) at 6 a.m., 12 p.m., 6 p.m., and 12 a.m. to determine the thermal comfort situation of the animals. Thermographic images of the environment and animals were captured in order to obtain the body surface temperature (BST) through infrared thermography. The Benezra Thermal Comfort Index (BTCI), Environmental Stress Index (ESI), Equivalent Temperature Index (ETI), and Iberian Heat Tolerance Index (Iberian HTI) were used. The results showed that the silvopastoral system, with shading by chestnut trees and an ample vegetative area, presented better thermal conditions, with an average of 28.98 °C, in comparison with the traditional system (35.93 °C) and the integrated one (34.11 °C). It was observed that the body surface temperature of cattle did not differ significantly between the anatomical regions of the body and the studied systems (p > 0.05). As for the respiratory rate, the traditional system registered higher values, with an average of 41 movements per minute, indicating possible thermal stress (p < 0.05). The thermal comfort indices revealed that all systems presented moderate stress conditions during times of higher solar intensity. It is concluded that the silvopastoral system proved to be more favorable for cattle, providing shade and reducing thermal stress, which may have a positive impact on animal welfare and productivity in this region.

Cast shadows reveal changes in glacier surface elevation

Abstract. Increased rates of glacier retreat and thinning need accurate local estimates of glacier elevation change to predict future changes in glacier runoff and their contribution to sea level rise. Glacier elevation change is typically derived from digital elevation models (DEMs) tied to surface change analysis from satellite imagery. Yet, the rugged topography in mountain regions can cast shadows onto glacier surfaces, making it difficult to detect local glacier elevation changes in remote areas. A rather untapped resource comprises precise, time-stamped metadata on the solar position and angle in satellite images. These data are useful for simulating shadows from a given DEM. Accordingly, any differences in shadow length between simulated and mapped shadows in satellite images could indicate a change in glacier elevation relative to the acquisition date of the DEM. We tested this hypothesis at five selected glaciers with long-term monitoring programmes. For each glacier, we projected cast shadows onto the glacier surface from freely available DEMs and compared simulated shadows to cast shadows mapped from ∼40 years of Landsat images. We validated the relative differences with geodetic measurements of glacier elevation change where these shadows occurred. We find that shadow-derived glacier elevation changes are consistent with independent photogrammetric and geodetic surveys in shaded areas. Accordingly, a shadow cast on Baltoro Glacier (the Karakoram, Pakistan) suggests no changes in elevation between 1987 and 2020, while shadows on Great Aletsch Glacier (Switzerland) point to negative thinning rates of about 1 m yr−1 in our sample. Our estimates of glacier elevation change are tied to occurrence of mountain shadows and may help complement field campaigns in regions that are difficult to access. This information can be vital to quantify possibly varying elevation-dependent changes in the accumulation or ablation zone of a given glacier. Shadow-based retrieval of glacier elevation changes hinges on the precision of the DEM as the geometry of ridges and peaks constrains the shadow that we cast on the glacier surface. Future generations of DEMs with higher resolution and accuracy will improve our method, enriching the toolbox for tracking historical glacier mass balances from satellite and aerial images.

Spatially continuous snow depth mapping by aeroplane photogrammetry for annual peak of winter from 2017 to 2021 in open areas

Abstract. Information on snow depth and its spatial distribution is important for numerous applications, including natural hazard management, snow water equivalent estimation for hydropower, the study of the distribution and evolution of flora and fauna, and the validation of snow hydrological models. Due to its heterogeneity and complexity, specific remote sensing tools are required to accurately map the snow depth distribution in Alpine terrain. To cover large areas (&gt;100 km2), airborne laser scanning (ALS) or aerial photogrammetry with large-format cameras is needed. While both systems require piloted aircraft for data acquisition, ALS is typically more expensive than photogrammetry but yields better results in forested terrain. While photogrammetry is slightly cheaper, it is limited due to its dependency on favourable acquisition conditions (weather, light conditions). In this study, we present photogrammetrically processed high-spatial-resolution (0.5 m) annual snow depth maps, recorded during the peak of winter over a 5-year period under different acquisition conditions over a study area around Davos, Switzerland. Compared to previously carried out studies, using the Vexcel UltraCam Eagle Mark 3 (M3) sensor improves the average ground sampling distance to 0.1 m at similar flight altitudes above ground. This allows for very detailed snow depth maps in open areas, calculated by subtracting a snow-off digital terrain model (DTM, acquired with ALS) from the snow-on digital surface models (DSMs) processed from the airborne imagery. Despite challenging acquisition conditions during the recording of the UltraCam images (clouds, shaded areas and fresh snow), 99 % of unforested areas were successfully photogrammetrically reconstructed. We applied masks (high vegetation, settlements, water, glaciers) to increase the reliability of the snow depth calculations. An extensive accuracy assessment was carried out using check points, the comparison to DSMs derived from unpiloted aerial systems and the comparison of snow-free DSM pixels to the ALS DTM. The results show a root mean square error of approximately 0.25 m for the UltraCam X and 0.15 m for the successor, the UltraCam Eagle M3. We developed a consistent and reliable photogrammetric workflow for accurate snow depth distribution mapping over large regions, capable of analysing snow distribution in complex terrain. This enables more detailed investigations on seasonal snow dynamics and can be used for numerous applications related to snow depth distribution, as well as serving as a ground reference for new modelling approaches and satellite-based snow depth mapping.

M2GF: Multi-Scale and Multi-Directional Gabor Filters for Image Edge Detection

An image edge detection algorithm using multi-directional and multi-scale Gabor filters is proposed in this paper. The main merit of this method is that high edge detection accuracy can be obtained while maintaining noise robustness. The approach proposed in this paper consists of three procedures: firstly, the transformation to the CIE L*a*b* color space, which has a wide shading area and uniform distribution; secondly, under different scales, the edge feature information of the image is extracted from several different directions by Gabor filters, and a new edge strength map is obtained by feature fusion; thirdly, the new fused edge strength map is enhanced with local features, and a noise-resistant image edge detector is obtained under a novel hysteresis threshold calculation. The experiments illustrate that, compared to the methods involved, the designed edge detector outperforms by about 2% to 4%, and also shows competitive performance regarding the ability to handle noise.

Using Local Knowledge and Remote Sensing in the Identification of Informal Settlements in Riyadh City, Saudi Arabia

Urban planning within Riyadh, the capital of Saudi Arabia, has been impacted by the presence of informal settlements. An understanding of the spatial distribution of these settlements is essential in developing urban policies. This study used remotely sensed imagery to evaluate and characterize informal settlements within the city, both with and without expert knowledge of the study area (defined as expert knowledge, EK). An informal settlement ontology for four study sites within Riyadh City was developed using an analytical hierarchy process (AHP). Local knowledge was translated into a ruleset to identify and map settlement areas using spatial, spectral, textural, and geometric techniques. These were combined with an object-based image analysis (OBIA) approach. The study demonstrated that combining expert knowledge and remotely sensed data can efficiently and accurately identify informal settlements. Two classified images were produced, one with EK, and one without EK, to investigate how a detailed understanding of local conditions could affect the final image classification. Overall accuracy when using EK was 94%, with a kappa coefficient of 89%, while without EK accuracy was 68% (kappa coefficient of 61%). The final OBIA classes included formal and informal settlements, road networks, vacant blocks, shaded areas, and vegetation. This study demonstrated that local expert knowledge and OBIA helpful in urban mapping. It also indicated the value of integrating a local ontological process during digital image classification. This work provided improved techniques for mapping informal settlements in Middle Eastern cities.

Study on the relationship between morphological characterizations of dough crumb particles at different mixing stages and noodles quality

To overcome the existing artificial experience evaluation approaches of wheat dough crumb (DC), image processing technique combined migration learning technique has been developed as the precise quantitative on-line evaluation methodology, the core indicator with stacked shaded area (SSA) for DC image evaluation can be used for DC quality evaluation. This study used image characteristics of DC to explore the correlation between noodle qualities at different mixing stages and uniformity of particles. The results showed that the changing regularities of noodle qualities were generally consistent at different mixing stages and finally reached stability. The mean value of SSA of DC showed a highly significant positive correlation with cooking loss (r = 0.93) and a highly significant negative correlation with elasticity and hardness (r = −0.90, r = −0.71) of noodles, indicating that DC can be used to predict noodle qualities. This study is instructive for achieving automatic control of mixing process during noodles production.