Search Results (3,675)

The Ice, Cloud, and Land Elevation 2 (ICESat-2) mission uses a micropulse photon-counting lidar system for mapping, which provides technical support for capturing forest parameters and carbon stocks over large areas. However, the current algorithm is greatly affected by the slope, and the extraction of the forest canopy height in the area with steep terrain is poor. In this paper, an improved algorithm was provided to reduce the influence of topography on canopy height estimation and obtain higher accuracy of forest canopy height. First, the improved clustering algorithm based on ordering points to identify the clustering structure (OPTICS) algorithm was developed and used to remove the noisy photons, and then the photon points were divided into canopy photons and ground photons based on mean filtering and smooth filtering, and the pseudo-signal photons were removed according to the distance between the two photons. Finally, the photon points were classified and interpolated again to obtain the canopy height. The results show that the improved algorithm was more effective in estimating ground elevation and canopy height, and the result was better in areas with less noise. The root mean square error (RMSE) values of the ground elevation estimates are within the range of 1.15 m for daytime data and 0.67 m for nighttime data. The estimated RMSE values for vegetation height ranged from 3.83 m to 2.29 m. The improved algorithm can provide a good basis for forest height estimation, and its DEM and CHM accuracy improved by 36.48% and 55.93%, respectively. Full article

Soil salinisation is a critical problem in northern China’s arid and semi-arid irrigated regions, posing a substantial impediment to the sustainable advancement of agriculture in these areas. This research utilises the Donghaixin Irrigation District, located on the southern bank of the Yellow River in Inner Mongolia, as a case study. This study examines the spatial distribution and determinants of soil salinisation through macro-environmental variables and micro-ion composition, integrating regression models and groundwater ion characteristics to elucidate the patterns and causes of soil salinisation systematically. The findings demonstrate that soil salinisation in the study region displays notable spatial clustering, with surface water-irrigated regions exhibiting greater salinisation levels than groundwater-irrigated areas. More than 80% of the land exhibits moderate salinity, predominantly characterised by the ions Cl⁻, HCO₃⁻, and SO₄²⁻. The hierarchy of ion concentration variation with escalating soil salinity is as follows: Na⁺ > K⁺ > SO₄²⁻ > Cl⁻ > Mg²⁺ > HCO₃⁻ + CO₃²⁻ > Ca²⁺. The susceptibility of ions to soil salinisation is ordered as follows: Ca²⁺ > Na⁺ > HCO₃⁻ + CO₃²⁻ > Mg²⁺ > K⁺ > Cl⁻ > SO₄²⁻. In contrast to the ordinary least squares (OLS) model, the geographic weighted regression (GWR) model more effectively elucidates the geographical variability of salinity, evidenced by an adjusted R² of 0.68, particularly in high-salinity regions, where it more precisely captures the trend of observed values. Ecological driving elements such as organic matter (OM), pH, groundwater depth (GD), total dissolved solids (TDS), digital elevation model (DEM), normalised difference vegetation index (NDVI), soil moisture (SM), and potential evapotranspiration (PET) govern the distribution of salinisation. In contrast, anthropogenic activities affect the extent of salinisation variation. Piper’s trilinear diagram demonstrates that Na cations mainly characterise groundwater and soil water chemistry. In areas irrigated by surface water, the concentration of SO₄²⁻ is substantially elevated and significantly affected by agricultural practises; conversely, in groundwater-irrigated regions, Cl⁻ and HCO₃⁻ are more concentrated, primarily driven by evaporation and ion exchange mechanisms. Full article

This study integrates morphometric analysis, remote sensing, and GIS with the analytical hierarchical process (AHP) to identify high potential groundwater recharge areas in Wadi Abadi, Egyptian Eastern Desert, supporting sustainable water resource management. Groundwater recharge primarily comes from rainfall and Nile River water, particularly for Quaternary aquifers. The analysis focused on the Quaternary and Nubian Sandstone aquifers, evaluating 16 influencing parameters, including elevation, slope, rainfall, lithology, soil type, and land use/land cover (LULC). The drainage network was derived from a 30 m-resolution Digital Elevation Model (DEM). ArcGIS 10.8 was used to classify the basin into 13 sub-basins, with layers reclassified and weighted using a raster calculator. The groundwater potential map revealed that 24.95% and 29.87% of the area fall into very low and moderate potential categories, respectively, while low, high, and very high potential zones account for 18.62%, 17.65%, and 8.91%. Data from 41 observation wells were used to verify the potential groundwater resources. In this study, the ROC curve was applied to assess the accuracy of the GWPZ models generated through different methods. The validation results indicated that approximately 87% of the wells corresponded accurately with the designated zones on the GWPZ map, confirming its reliability. Over-pumping in the southwest has significantly lowered water levels in the Quaternary aquifer. This study provides a systematic approach for identifying groundwater recharge zones, offering insights that can support resource allocation, well placement, and aquifer sustainability in arid regions. This study also underscores the importance of recharge assessment for shallow aquifers, even in hyper-arid environments. Full article

Geological hazards in densely vegetated mountainous regions are challenging to detect due to terrain concealment and the limitations of traditional visualization methods. This study introduces the LiDAR image highlighting algorithm (LIHA), a novel approach for enhancing micro-topographical features in digital elevation models (DEMs) derived from airborne LiDAR data. By analogizing terrain profiles to non-stationary spectral signals, LIHA applies locally estimated scatterplot smoothing (Loess smoothing), wavelet decomposition, and high-frequency component amplification to emphasize subtle features such as landslide boundaries, cracks, and gullies. The algorithm was validated using the Mengu landslide case study, where edge detection analysis revealed a 20-fold increase in identified micro-topographical features (from 1907 to 37,452) after enhancement. Quantitative evaluation demonstrated LIHA’s effectiveness in improving both human interpretation and automated detection accuracy. The results highlight LIHA’s potential to advance early geological hazard identification and mitigation, particularly when integrated with machine learning for future applications. This work bridges signal processing and geospatial analysis, offering a reproducible framework for high-precision terrain feature extraction in complex environments. Full article

Glacier meltwater influences streamflow and various activities in the western US. The Wind River Range (WRR) in Wyoming, which contains the largest glacial mass in the Rocky Mountains of the conterminous US, has been retreating since the Little Ice Age. This study examines long-term changes in WRR glaciers (>0.2 km²) over 1968–2019 and investigates their relationship with climatic and topographic factors. Using USGS topographic maps, satellite imagery, DEM datasets, and GPS surveys, we analyzed glacier area and surface elevation changes. Our results show a 19.2 ± 0.9% glacier area reduction from 1972 to 2019, with a 10.6 ± 0.3% decline from 2000–2019. Glacier thinning was most pronounced between 2000 and 2019 at −0.58 ± 0.11 m y⁻¹, with lower-elevation glaciers thinning faster. Small, south-facing glaciers retreated more rapidly, while slope effects were mixed. Increasing spring temperatures and a shift toward more spring precipitation falling as rain has likely exacerbated glacier loss since 2000. Such accelerated melting has significant implications for water availability and ecosystem health if warming continues, affecting agricultural, industrial, and recreational water use. Understanding these trends is key for future water resource management and ecosystem sustainability in the region. Full article

The seepage of groundwater in loose soil causes the migration of fine particles within the soil, which can significantly contribute to slope instability and trigger a series of geological issues, such as soil erosion, landslides, and debris flow. This study employed a coupled computational fluid dynamics and discrete element method (CFD-DEM) to investigate the migration process of soil particles under groundwater seepage. It elucidated the effects of key factors, including particle size ratio, particle quantity, and weight, on the migration behavior of fine particles within porous media. The results indicated that when the particle size ratio was less than or equal to 5, over 90% of fine particles accumulated on the surface of the medium. Additionally, an increase in the weight or quantity of fine particles intensified their accumulation. However, when the particle size ratio exceeded five, it became the dominant factor affecting displacement. Under the same weight conditions, the larger the particle size ratio, the longer the particle migration distance. Compared to a particle size ratio of 3, the accumulation percentages of fine particles with a particle size ratio of 20 increased by 26.88% and 31.46% in the middle and tail sections, respectively. Full article

In this paper, we deal with continuous multi-utility representations for closed preorders. We introduce the definition of a net-compact topology, which generalizes the concept of a sequentially compact topology. Indeed, a sequentially compact and first countable topological space is net-compact. First, we show that if every closed preorder on a net-compact Hausdorff topological space has a continuous multi-utility representation, then the topology is normal. Second, we prove that every closed preorder on a normal and net-compact Hausdorff topological space admits a continuous multi-utility representation. Full article

The aboveground biomass (AGB) of forests reflects the productivity and carbon-storage capacity of the forest ecosystem. Although AGB estimation techniques have become increasingly sophisticated, the relationships between AGB, spatial distribution, and growth stages still require further exploration. In this study, the Picea schrenkiana (Picea schrenkiana var. tianschanica) forest area in the Kashi River Basin of the Ili River Valley in the western Tianshan Mountains was selected as the research area. Based on forest resources inventory data, Gaofen-1 (GF-1), Gaofen-6 (GF-6), Gaofen-3 (GF-3) Polarimetric Synthetic Aperture Radar (PolSAR), and DEM data, we classified the Picea schrenkiana forests in the study area into three cases: the Whole Forest without vertical zonation and stand age, Vertical Zonality Classification without considering stand age, and Stand-Age Classification without considering vertical zonality. Then, for each case, we used eXtreme Gradient Boosting (XGBoost), Back Propagation Neural Network (BPNN), and Residual Networks (ResNet), respectively, to estimate the AGB of forests in the study area. The results show that: (1) The integration of multi-source remote-sensing data and the ResNet can effectively improve the remote-sensing estimation accuracy of the AGB of Picea schrenkiana. (2) Furthermore, classification by vertical zonality and stand ages can reduce the problems of low-value overestimation and high-value underestimation to a certain extent. Full article

Existing methods for calculating terrain entropy in grid digital elevation models (DEMs) often face computational anomalies in specific topographies within small windows. To address this issue, an improved method was developed based on the Euclidean distance approach. This method was inspired by Claramunt’s technique of weighting information entropy by the average distance between points with the same value and different values. Specifically, vectors were formed between grid points and categorized by value consistency and relative positions. Those formed between points of different values were classified by the value of the starting point as well as parallel and adjacent relationships. This comprehensive grouping strategy was integrated into distance calculations, becoming a new probability operator that accurately reflects terrain spatial characteristics. Experimental verification confirms that the method proposed aligns with the fundamental concept of entropy, yielding a regression equation of $y=0.011\ln x+0.463$ with a coefficient of determination of 94.73%, a reliability of 44.015, and a measurement ability of 0.757. For the mixed iterative images with gradually increasing spatial disorder, their entropy values should follow a logarithmic trend. Therefore, a logarithmic function is used for fitting. A determination coefficient greater than 50% indicates that the method adheres to the original definition of entropy and is effective in capturing the increasing spatial disorder of the grid DEM. A lower reliability value suggests smoother data computation between the two iterations. A lower measurement ability value indicates slower convergence for grid DEMs with gradually increasing spatial disorder. The improved method was also tested on simulated and real DEMs, and the results showed a strong correlation between calculated terrain entropy values and terrain complexity. By effectively capturing spatial information changes, this approach overcomes the shortcoming of computational anomalies and demonstrates high reliability in terrain entropy calculation in grid DEMs. Full article

Fluidized bed reactors (FBRs) are integral to various industries due to their exceptional capability in facilitating efficient gas–solid interactions, resulting in superior mixing and heat and mass transfer. This research delves into the impact of temperature on fluidization dynamics, particularly focusing on the collisional properties of particles within the bed. The investigation builds upon foundational research, notably Geldart’s classification of fluidization regimes and recent advancements in high-temperature experimental techniques, such as High-Temperature Endoscopic-Laser particle image velocimetry/digital image analysis. To explore these temperature effects, a coupled Discrete Element Method and Computational Fluid Dynamics (cfd–dem) model was employed. This approach enables a detailed examination of gas–particle and particle–particle interactions under varying temperature conditions. The simulations in this study explore the friction coefficient, as well as changes in both tangential and normal restitution coefficients, which affect the fluidization behavior. These changes were systematically analyzed to determine their influence on minimum fluidization velocity and bubble formation. The numerical results are compared with experimental data from high-temperature fluidization studies, highlighting the necessity of incorporating inter-particle forces to fully capture the observed phenomena. The findings underscore the critical role of particle collisional properties in high-temperature fluidization and suggest the potential increasing role of inter-particle forces. Overall, this paper provides new insights into the complex dynamics of fluidized beds at elevated temperatures, emphasizing the need for further experimental–numerical research to enhance the reliability and understanding of these systems in industrial applications. Full article

The Interferometric Synthetic Aperture Radar (InSAR) has significantly advanced in its usage for analyzing surface information such as displacement or elevation. In this study, we evaluated a digital elevation model (DEM) constructed using X-band KOMPSAT-5 interferometric datasets provided by the Korea Aerospace Research Institute (KARI). The 28-day revisit cycle of KOMPSAT-5 poses challenges in maintaining interferometric correlation. To address this, four KOMPSAT-5 images were employed in a multi-baseline interferometric approach to mitigate temporal decorrelation effects. Despite the slightly longer temporal baselines, the analysis revealed sufficient coherence (>0.8) in three interferograms. The height of ambiguity ranged from 59 to 74 m, which is a moderate height of sensitivity to extract topography over the study area of San Francisco in the USA. Unfortunately, only ascending acquisition mode datasets were available for this study. The derived DEM was validated against three reference datasets: Copernicus GLO-30 DEM, ICESat-2, and GEDI altimetry. A high coefficient of determination (R² > 0.9) demonstrates the feasibility of the interferometric application of KOMPSAT-5. Full article

The shape of particles is a critical determinant that significantly influences the accuracy of discrete element simulations. To reduce the discrepancies between the discrete element model of wheat seeds and the actual particle shapes, and to enhance the accuracy of Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) coupling simulations in gas–solid two-phase flow studies, We employed laser scanning and inverse modeling techniques to develop a three-dimensional (3D) reconstruction of the wheat seed. Subsequently, we employed Rocky DEM simulation software to develop a polyhedron model and an Angle of Repose (AOR) test model. The interval range of material parameters was determined through a series of physical experiments and subsequently employed to delineate the high and low levels of parameters for the simulation tests. The simulation parameters were calibrated using data from AOR simulation tests. The Plackett–Burman test, Steepest-Ascent test, and Box–Behnken test were conducted sequentially to determine the optimal parameter configuration. A test bench for wheat gas-assisted seeding was constructed, and a semi-resolved CFD-DEM coupling simulation model was developed to perform comparative analysis. The results demonstrated that the optimal parameters were as follows: the static friction coefficient of wheat seed was 0.15, the dynamic friction coefficient of wheat seed was 0.11694, and the dynamic friction coefficient between wheat seed and resin was 0.0797. In this scenario, the relative error of AOR was 2.3% and the maximum relative error of ejection velocity observed was 4.1%. The reliability of the polyhedron model and its calibration parameters was rigorously validated, thereby providing a robust reference for studies on gas–solid two-phase flows. Full article

This investigation endeavors to demarcate the boundaries of small- and medium-sized river catchments within the Caspian Sea drainage basin, with a specific focus on the Northeastern Caucasus, Azerbaijan, and Iran regions. A multi-faceted approach was employed, incorporating various remote sensing methods to select key areas, including the catchments of the Sunzha, Sulak, Ulluchay, Karachay, Atachay, Haraz, and Gorgan rivers. Subsequently, geoinformation systems (GISs) and topographic maps were utilized to determine the morphometric characteristics of these catchments, accompanied by an assessment of the accuracy of remote sensing data. The aim of this study is to evaluate the accuracy and suitability of digital elevation models (DEMs) with a spatial resolution of 30 m per pixel (including ASTER DEM, ALOS DEM, NASADEM, Copernicus 30 m DEM, and SRTM 30 m DEM) and 90 m per pixel (Copernicus 90 m DEM and SRTM 90 m DEM) for delineating small- and medium-sized Caspian Sea basin river catchments. For the DEMs that successfully and accurately delineated watershed boundaries, the morphometric characteristics of the river basins were calculated. This research has yielded novel findings regarding the morphometric characteristics (area, perimeter, ruggedness of the catchment line (roundness coefficient), maximum height, minimum height, average height of the river basin, maximum slope of the surface, average slope of the surface, length of the main watercourse, basin shape parameter (catchment elongation coefficient), shape coefficient, length of the river basin, average river basin slope, and average width of the basin) of individual mountainous small- and medium-sized rivers in the Northeastern Caucasus, Azerbaijan, and Iran, with the catchments of the aforementioned rivers serving as exemplars. The practical significance of these results lies in the fact that such detailed morphometric characteristics of catchments have been obtained for the first time, and their boundaries have been clarified (burned out according to various DEMs), which can serve as a basis for decision-making processes and contribute to the development of operational environmental monitoring of the state of rivers and their catchments. Full article

The study explores the impact of floods, phenomena amplified by climate change and human activities, on the natural and anthropogenic environment, focusing on the analysis of a section of the Cigher River in the Crișul Alb basin in western Romania. The research aims to identify areas vulnerable to flooding under different discharge scenarios, assess the impact on agricultural lands, and propose a reproducible methodology based on the integration of GIS technologies, hydraulic modeling in HEC-RAS, and the use of LiDAR data. The methodology includes hydrological analysis, processing of the Digital Elevation Model (DEM), delineation of geometries, hydraulic simulation for four discharge scenarios (S1–S4), and evaluation of the flood impact on agricultural and non-agricultural lands. Evaluated parameters, such as water velocity and flow section areas, highlighted an increased flood risk under maximum discharge conditions. The results show that scenario S4, with a discharge of 60 m³/s, causes extensive flooding, affecting 871 hectares of land with various uses. The conclusions emphasize the importance of using modern technologies for risk management, protecting vulnerable areas, and reducing economic and ecological losses. The proposed methodology is also applicable to other river basins, representing a useful model for developing sustainable strategies for flood prevention and management. Full article

Gyratory crushers are fundamental machines in aggregate production and mineral processing. Discrete Element Method (DEM) simulations offer detailed insights into the performance of these machines and serve as a powerful tool for their design and analysis. However, these simulations are computationally intensive due to the large number of particles involved and the need to account for particle breakage. This study aims to investigate the effect of particle shape and size distribution on the performance of a DEM model of a gyratory crusher. The selected study case corresponds to a primary gyratory crusher operating in a copper processing industry. As particle shapes, spheres and polyhedrons are used with a particle replacement scheme. This study utilizes two different size distributions, with variations also applied to the minimum particle size. The results are analyzed in terms of the impact of these factors on the power draw, mass flow, and product size distribution for each of the combinations explained. The findings demonstrate that particle shape primarily influences the product size distribution, whereas variations in particle size distribution have a pronounced effect on power draw, mass flow rate, and product size distribution. Based on the results, recommendations are provided regarding the selection of the minimum particle size. It is concluded that the minimum particle size should not exceed a third of the closed-side setting to ensure accurate and reliable simulation outcomes. Full article