Search Results (31)

This study focuses on surface wind analysis at the small regional airport in Svidnik, used primarily for pilot training under daytime VFR conditions. Due to the complex local terrain and lack of prior meteorological data, an automatic weather station was installed, collecting over 208,000 wind measurements over a two-year period at ten-minute intervals. The dataset was processed using hierarchical filtering and statistical selection, and visualized via wind rose diagrams. The results confirmed a dominant southeastern wind component, supporting the current runway orientation (01/19). However, a less frequent easterly wind direction was identified as a safety concern, causing turbulence near the runway due to terrain and vegetation. This is particularly critical for trainee pilots during final approach and landing. Statistical analysis showed that easterly winds, though less common, appear year-round with a peak in summer. Pearson correlation and linear regression confirmed a significant relationship between the number of easterly wind days and their measurement frequency. Daytime winds were stronger than nighttime, justifying the focus on daylight data. The study provides practical recommendations for training flight safety and highlights the value of localized wind monitoring at small airports. The presented methodology offers a framework for improving operational awareness and reducing risk in complex environments. Full article

The present study aims to characterize complex geological structures and significant mineralization using remote sensing and aeromagnetic studies. Structural lineaments play a crucial role in the localization and concentration of mineral deposits. For the first time over the study district, a combination of aeromagnetic data, Landsat 9, ASTER, and PRISMA hyperspectral data was utilized to enhance the characterization of both lithological units and structural features. Advanced image processing techniques, including false color composites, principal component analysis (PCA), independent component analysis (ICA), and SMACC, were applied to the remote sensing datasets. These methods enabled effective discrimination between Phanerozoic rock formations and the complex basement units, which comprise the island arc assemblage, Dokhan volcanics, and late-orogenic granites. The local and deep magnetic sources were separated using Gaussian filters. The Neoproterozoic basement rocks were estimated using the radial average power spectrum technique and the Euler deconvolution technique (ED). According to the RAPS technique, the average depths to shallow and deep magnetic sources are approximately 0.4 km and 1.6 km, respectively. The obtained ED contacts range in depth from 0.081 to 1.5 km. The research area revealed massive structural lineaments, particularly in the northeast and northwest sides, where a dense concentration of these lineaments was identified. The locations with the highest densities are thought to signify more fracturization in the rocks that are thought to be connected to mineralization. According to the automatic lineament extraction methods and rose diagram, NW-SE, NNE-SSW, and N-S are the major structural directions. These trends were confirmed and visually represented through textural analysis and drainage pattern control. The lithological mapping results were validated through field observations and petrographic analysis. This integrated approach has proven highly effective, showcasing significant potential for both detailed structural analysis and accurate lithological discrimination, which may be related to further mineralization exploration. Full article

The roughness of the Earth’s surface dictates the nature of air flow across it. Detailed meteorological data that are necessary to access the aerodynamic roughness ($z_0$) are not widely collected and, as such, the geometry of a surface can be used to estimate $z_0$. Here, we present a novel formulation, and the corresponding computer code, to compute $z_0$ based on the Lettau (1969) geometric approach. The new code produces a mean $z_0$, as well as a histogram of all $z_0$ values for each individual roughness element (e.g., 10 s of thousand for the 1000 × 1000 grids) discretized using watersheds, as well as directional $z_0$ diagrams, which can be matches with the wind rose for the location. The formulation includes two parameters that may optionally be applied to smooth the surface before calculating $z_0$. By calculating $z_0$ as a function of these two parameters, we demonstrate the sensitivity of the $z_0$ value to these parameter choices. Since a large portion of the Earth’s surface is snow covered during some parts of the year, and the roughness of the snow surface varies over the snow season and over space, we apply the code to three snow surface datasets. Each surface is during a different phases of the snowpack. Each surface is evaluated at two resolutions). These surfaces are: fresh snow accumulation (1 m² at 1 and 10 mm), peak accumulation (1 km² at 1 and 10 m) and ablation sun cups (25 m² at 5 and 50 mm). Full article

The Indian Ocean Rim (IOR) is a crucial hub for global commerce, possessing key maritime corridors and competitive markets for China and the United States. Assessing the evolving positions of China and the United States in regional trade provides critical insights into their economic competition. This study quantitatively investigated their changing positions in the IOR trade networks from 1992 to 2020 through an interdisciplinary approach combining the Fisher optimal segmentation, chord-diagram visualization, and five weighted centrality indicators, including two advanced metrics derived from physical current flow theory. The results reveal a significant shift in their trade positions in the IOR trade networks across four phases (1992–2002, 2003–2008, 2009–2014, and 2015–2020); in particular, the United States occupied a dominant position in the IOR trade networks until 2008, after which China rose to the central trading position, as reflected in its top ranking across four weighted indicators (excluding weighted authority centrality). In machinery and transport equipment (SITC7), China also surpassed the United States in 2008 and further consolidated its supremacy, driven by its strong manufacturing capabilities and the growing demand from the IOR countries. Meanwhile, the United States experienced a noticeable decline but maintained substantial influence as a key importer. This research develops a quantitative framework that integrates the temporal segmentation with weighted centrality indicators to provide insights into the dynamics and structural changes of trade networks across sectors and regions. Full article

This study investigates the effectiveness of natural wind-driven ventilation systems in enhancing thermal comfort and energy efficiency within the context of Central European climates, specifically Vienna. By addressing the unique challenges posed by cultural heritage buildings, such as the Praterateliers’ Pavilions, this research highlights the role of sustainable ventilation strategies in mitigating urban overheating, which is exacerbated by climate change. A novel focus is placed on integrating windcatchers with passive systems like earth tubes and solar ventilation to reduce reliance on mechanical cooling and achieve lower carbon emissions while adhering to heritage preservation regulations. Using DesignBuilder simulations and future climate data (2020–2030), this research evaluates the thermal performance of key zones within the Praterateliers under different operational scenarios. The selected analysis period (May to September) captures the peak thermal stress conditions in Vienna, with wind rose diagrams and temperature characteristics providing insights into the ventilation potential during these months. The quantitative results demonstrate that cross-ventilation, combined with windcatchers and subterranean air exchange systems, improved thermal comfort metrics—such as predicted mean vote indices—by up to 30%, particularly in windward and leeward zones. These findings underscore the viability of non-invasive natural ventilation systems in achieving optimal thermal conditions, demonstrating an innovative yet preservation-friendly approach to sustainable architecture. This research not only advances the application of passive cooling strategies in heritage buildings but also provides scalable solutions for addressing urban overheating in modern constructions. Full article

The compressive sensing (CS) framework offers a cost-effective alternative to dense alias-free sampling. Designing seismic layouts based on the CS technique imposes the use of specific sampling patterns in addition to the logistical and geophysical requirements. We propose a two-step design process for generating CS-based schemes suitable for seismic applications. During the first step, uniform random sampling is used to generate a random scheme, which is supported theoretically by the restricted isometry property. Following that, designated samples are added to the random scheme to control the maximum distance between adjacent sources (or receivers). The null space property theoretically justifies the additional samples of the second step. Our sampling method generates sampling patterns with a CS theoretical background, controlled distance between adjacent samples, and a flexible number of active and omitted samples. The robustness of two-step sampling schemes for reallocated samples is investigated and CS reconstruction tests are performed. In addition, using this approach, a CS-based 3D seismic survey is designed, and the distributions of traces in fold maps and rose diagrams are analyzed. It is shown that the two-step scheme is suitable for CS-based seismic surveys and field applications. Full article

In contrast to intensive management practices focused on wood production, plantations designed to safeguard fragile environments prioritize the sustainable fulfillment of ecological functions. To assess the potential for Chinese pine (Pinus tabuliformis Carr.) plantations in the Loess Hilly Region to effectively serve their ecological protection role over the long term, we selected nine indices representing biological stability, resistance stability, and functional stability. Employing a novel unit circle method, we evaluated the total stability (sum of the three stability components) of 44 plantation plots in Huanglong Mountain. We also explored the connections between total stability and standing spatial structure parameters to offer insights for promptly enhancing stability through thinning. The findings revealed that 79.5% of Chinese pine plantations exhibited moderate total stability, with 20.5% demonstrating good stability. Most plots displayed a random distribution pattern, moderate size differentiation, low species spatial mixing, and high stand crowding. Among the correlations analyzed, mingling exhibited the highest coefficient, followed by differentiation, while the uniform angle index showed the weakest correlation, and crowding displayed an insignificant correlation. While the presence of good functional stability contributed to the moderate total stability, addressing inadequate biological and resistance stability necessitates thinning measures. This study identifies spatial structure types negatively linked to total stability, offering targeted management insights for enhancing the stability of Chinese pine plantations. The stability assessment methodology and indicators presented in this study can serve as a valuable reference for similar plantations with comparable functions and planting conditions. Full article

In this paper, based on integer-order Hindmarsh–Rose (HR) neurons under an electric field, the fractional-order model is constructed, and the nonlinear term is decomposed by the Adomian decomposition method, and the numerical solution of the system is obtained. The firing behavior of the neuron model is analyzed by using a phase diagram, interspike interval (ISI) bifurcation diagram, sample entropy (SE) complexity, and largest Lyapunov exponent (LLE). Based on the sliding mode control theory, a chaos synchronization controller of the system is designed. Matlab simulation results show that the controller is realizable and effective, and also has the characteristic of fast response, which provides a reference for the control and application of a memristor neural network system. Full article

In this quick study, we estimated the Weibull distribution’s parameters using wind data collected between March 2017 and January 2018 using a twelve-meter mast meteorological station on the grounds of the National Energy Research Center in Khartoum. In order to quantify these descriptors, we relied on analytical and stochastic methods, subsequently enabling specialists from researchers, engineers, decision-makers, and policymakers to apprehend the wind characteristics in the vicinity. Hence, the computed scale and shape parameters were provided, in which the Firefly algorithm (FA) resulted in the most accuracy in terms of the coefficient of determination, which equaled 0.999, which we considered logical due to the observed nonlinearity in the wind speed numbers. On the contrary, the energy pattern factor method had the worst prediction capability depending on several goodness-of-fit metrics. This concise work is unique because it is the first to use data from Sudan to forecast local wind speeds using artificial intelligence algorithms, particularly the FA technique, which is widely used in solar photovoltaic modeling. Additionally, since classic estimating approaches act differently spatially, evaluating their efficacy becomes innovative, which was accomplished here. On a similar note, a weighted-average wind speed was found to equal $4.98 \mathrm{m}/\mathrm{s}$ and the FA average wind speed was $3.73 \mathrm{m}/\mathrm{s}$, while the rose diagram indicated that most winds with potential energy equivalent to $3 \mathrm{m}/\mathrm{s}$ or more blow from the north. Full article

Visualisation techniques have been one of the best data processing and analysis methods in recent decades, and they have assisted in data understanding efforts in various fields. Visualisation techniques for low-dimensional data are well developed and applied in multiple sectors; however, multidimensional data visualisation techniques still present some limitations, such as inaccurate data comparison and perception, exaggerated visual differences, label occlusion, and overlap. This study addresses the pros and cons and proposes a novel graphical drawing method, the multidimensional rose chart. It adopts the design idea of the Nightingale rose chart, but overcomes relevant limitations. The main challenges of this area include the incomplete presentation of multidimensional data, the neglect of the linkage of multiple attributes, the inefficient use of space, and the lack of simplicity of the interface. Contributions include enriching the representations of multidimensional data through the use of colour shades, area, and height sizes to represent values; straightforward data attribute comparisons via graph nesting; and detailed attributes showing the use of specific value labels. To verify the preliminary validity of this method, we imported COVID-19 data into experiments and further compared the final layouts with traditional methods, such as the line chart, bar chart, tree, parallel coordinate chart, and Nightingale rose chart, as well as their structures, functionalities, clear advantages, and disadvantages. The experimental results show that multidimensional rose diagrams perform effectively in presenting multidimensional data when comparing other graph drawing methods in our case, and the outcomes match existing works’ conclusions in related COVID-19 research sectors. This work has the potential to provide a suitable supplemental approach to the multidimensional data analysis. Full article

Ground-level ozone (O₃) is a significant source of air pollution, mainly in most urban areas across the globe. Ground-level O₃ is not emitted directly into the atmosphere. It results from photo-chemical reactions between precursors and is influenced by weather factors such as temperature. This study investigated the spatial and temporal analysis of ground-level ozone and analyzed the significant anthropogenic precursors and the weather parameters associated with ground-level ozone during daytime and nighttime at three cities in peninsular Malaysia, namely, Kuala Terengganu, Perai, and Seremban from 2016 to 2020. Secondary data were acquired from the Department of Environment (DOE), Malaysia, including hourly data of O₃ with trace gases and weather parameters. The secondary data were analyzed using temporal analysis such as descriptive statistics, box plot, and diurnal plot as well as spatial analysis such as contour plot and wind rose diagram. Spearman correlation was used to identify the association of O₃ with its precursors and weather parameters. The results show that a higher concentration of O₃ during the weekend due to “ozone weekend effects” was pronounced, however, a slightly significant effect was observed in Perai. The two monsoonal seasons in Malaysia had a minimal effect on the study areas except for Kuala Terengganu due to the geographical location. The diurnal pattern of O₃ concentration indicates bimodal peaks of O₃ precursors during the peak traffic hours in the morning and evening with the highest intensity of O₃ precursors detected in Perai. Spearman correlation analysis determined that the variations in O₃ concentrations during day and nighttime generally coincide with the influence of nitrogen oxides (NO) and temperature. Lower NO concentration will increase the amount of O₃ concentration and an increasing amount of O₃ concentration is influenced by the higher temperature of its surroundings. Two predictive models, i.e., linear (multiple linear regression) and nonlinear models (artificial neural network) were developed and evaluated to predict the next day and nighttime O₃ levels. ANN resulted in better prediction for all areas with better prediction identified for daytime O₃ levels. Full article

The “natural GMS laboratory” (granulometry-morphometry-situmetry) is located within the Variscan Basement in SE Germany (Fichtelgebirge Mts.), which is uplifted relative to its Permo-Mesozoic foreland along a deep-seated lineamentary fault zone. This transitional study area is crossed by straight to low drainage systems in the basement, turning meandering channel systems into high sinuosity when entering the foreland. Due to its good geological coverage, the entire region is subjected to an advanced-level terrain analysis and completed with a sedimentological study focusing on the GMS tool. Unlike many applications in the past, the three components of the GMS tool that are of almost equal value ought to be used in combination and not as stand-alone procedures so as to be integrated into other near-surface geoscientific methods, e.g., sediment petrography. The strong points of granulometry of coarse-grained/gravel-sized sediments are its extension into the smaller sand and clay grain size intervals using the sorting, mean and/or median values for an environmental analysis. Morphometry can be linked to the compositional geosciences, e.g., mineralogy and geochemistry. The grain shape is intimately connected with the lithology, providing options from triaxial measuring of the lithoclast to the digital image analysis. It is a favorable tool to supplement the provenance of lithoclasts. Situmetry is the key element of hydrodynamic research and directly builds upon its sister methods. Its applications and numerical approaches are useful for the identification and quantification of physical land-forming processes. It is the fan sharpness and the orientation of lithoclasts relative to the direction of the talweg and in relation cross-sectional valley features that integrate the GMS tool into geological and geomorphological mapping, both of which result in a digital terrain model. Horizontal rose diagrams are useful for the upper reaches of drainage systems, be they of alluvial or non-alluvial types, and vertical ones for alluvial channels in the distal and proximal foreland where stacked patterns of depositional terraces are of widespread occurrence. In general, the GMS tool can be applied to sedimentological, geomorphological, petrographic and tectonic objects in basements and foreland basins; in applied geosciences, it is suitable for the identification of mineral resources and of areas vulnerable to geohazards, and in genetic geosciences for the discrimination of supergene chemical and physical depositional and land-forming processes. Full article

Currently, climate change and population growth have a significant impact on human beings. Furthermore, these factors are generating a great need for energy to sustain present-day pace of life. For this reason, this research aims to determine the wind potential of the city of Chachapoyas, through the study of wind direction and speed using a wind rose. Data were obtained from the Metrological Station located on the University Campus of the National University Toribio Rodríguez de Mendoza (UNTRM) for developing this diagram. The mentioned station had 15% of missing data, therefore a quality control of the data and multiple imputations was carried out to fill in any missing data. The results obtained show that the winds in this area are mostly weak (from 0 to 3 m/s) with an East-Northeast (ENE) and Northeast (NE) direction for both the studied period and for each year of the period. It has also been determined that there is a difference between the wet and dry seasons in terms of wind frequency. Finally, we conclude that, in the city of Chachapoyas, it is possible to generate wind energy by using low-power vertical axis wind turbines. Full article

Fault systems are characteristically one of the main factors controlling massive sulfide mineralization. The main objective of this study was to investigate the relationship between fault systems and host lithology with massive sulfide copper mineralization in the Sahlabad area, South Khorasan province, east of Iran. Subsequently, the rose diagram analysis, Fry analysis, lineament factor (LF) map analysis and multifractal technique were implemented for geological and geophysical data. Airborne geophysical analysis (aeromagnetometric data) was executed to determine the presence of intrusive and extrusive masses associated with structural systems. Accordingly, the relationship between the formation boundaries and the fault system was understood. Results indicate that the NW-SE fault systems are controlling the lithology of the host rock for copper mineralization in the Sahlabad area. Hence, the NW-SE fault systems are consistent with the main trend of lithological units related to massive sulfide copper mineralization in the area. Additionally, the distance of copper deposits, mines and indices in the Sahlabad area with fault systems was calculated and interpreted. Fieldwork results confirm that the NW-SE fault systems are entirely matched with several massive sulfide copper mineralizations in the area. This study demonstrates that the fusion of lineament factor (LF) map analysis and multifractal technique is a valuable and inexpensive approach for exploring massive sulfide mineralization in metallogenic provinces. Full article

Globalization now applies to almost all aspects of life, and it also applies to the world of science. Internationalisation and interdisciplinarity are fundamental determinants of modern research and education. The foremost factor of functioning in the international world of science is the mobility of students and scientists. Considering this context, the objective of this study was to analyse the staff mobility for teaching under the Erasmus+ programme at the Wrocław University of Environmental and Life Sciences (UPWr). The research took into account the mobility of staff for teaching (STA) within the period of the academic years from 2009/2010 to 2020/2021. The methodological approach applied in this study is based on the concept of mobility network analysis and mobility flows. The geo-visualization was prepared with the use of a spider diagram. Using this approach, the connections between spatial locations and domains of scientific activity were analysed. The results show that the mobility flow at UPWr rose significantly after the authorities of the university decided to increase the funding for STA, and eventually was slowed down by the outbreak of the COVID-19 pandemic. Moreover, the findings in the geographical aspect show that there were two main regions of destination, which were the Iberian Peninsula and the closest neighbouring countries, where the predominant institutions could be observed. The most mobile group of teachers were the ones representing environment sciences. The STA flow is not reflected in the students’ mobility flow. COVID-19 has enhanced the virtual component of learning, resulting in the strengthening of the blended mobility model. Full article