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26 pages, 3030 KiB  
Article
Predicting Landslide Susceptibility Using Cost Function in Low-Relief Areas: A Case Study of the Urban Municipality of Attecoube (Abidjan, Ivory Coast)
by Frédéric Lorng Gnagne, Serge Schmitz, Hélène Boyossoro Kouadio, Aurélia Hubert-Ferrari, Jean Biémi and Alain Demoulin
Earth 2025, 6(3), 84; https://doi.org/10.3390/earth6030084 (registering DOI) - 1 Aug 2025
Abstract
Landslides are among the most hazardous natural phenomena affecting Greater Abidjan, causing significant economic and social damage. Strategic planning supported by geographic information systems (GIS) can help mitigate potential losses and enhance disaster resilience. This study evaluates landslide susceptibility using logistic regression and [...] Read more.
Landslides are among the most hazardous natural phenomena affecting Greater Abidjan, causing significant economic and social damage. Strategic planning supported by geographic information systems (GIS) can help mitigate potential losses and enhance disaster resilience. This study evaluates landslide susceptibility using logistic regression and frequency ratio models. The analysis is based on a dataset comprising 54 mapped landslide scarps collected from June 2015 to July 2023, along with 16 thematic predictor variables, including altitude, slope, aspect, profile curvature, plan curvature, drainage area, distance to the drainage network, normalized difference vegetation index (NDVI), and an urban-related layer. A high-resolution (5-m) digital elevation model (DEM), derived from multiple data sources, supports the spatial analysis. The landslide inventory was randomly divided into two subsets: 80% for model calibration and 20% for validation. After optimization and statistical testing, the selected thematic layers were integrated to produce a susceptibility map. The results indicate that 6.3% (0.7 km2) of the study area is classified as very highly susceptible. The proportion of the sample (61.2%) in this class had a frequency ratio estimated to be 20.2. Among the predictive indicators, altitude, slope, SE, S, NW, and NDVI were found to have a positive impact on landslide occurrence. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), demonstrating strong predictive capability. These findings can support informed land-use planning and risk reduction strategies in urban areas. Furthermore, the prediction model should be communicated to and understood by local authorities to facilitate disaster management. The cost function was adopted as a novel approach to delineate hazardous zones. Considering the landslide inventory period, the increasing hazard due to climate change, and the intensification of human activities, a reasoned choice of sample size was made. This informed decision enabled the production of an updated prediction map. Optimal thresholds were then derived to classify areas into high- and low-susceptibility categories. The prediction map will be useful to planners in helping them make decisions and implement protective measures. Full article
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20 pages, 7673 KiB  
Article
Impact of Elevation and Hydrography Data on Modeled Flood Map Accuracy Using ARC and Curve2Flood
by Taylor James Miskin, L. Ricardo Rosas, Riley C. Hales, E. James Nelson, Michael L. Follum, Joseph L. Gutenson, Gustavious P. Williams and Norman L. Jones
Hydrology 2025, 12(8), 202; https://doi.org/10.3390/hydrology12080202 (registering DOI) - 1 Aug 2025
Abstract
This study assesses the accuracy of flood extent predictions in five U.S. watersheds. We generated flood maps for four return periods using various digital elevation models (DEMs)—FABDEM, SRTM, ALOS, and USGS 3DEP—and two versions of the GEOGLOWS River Forecast System (RFS) hydrography. These [...] Read more.
This study assesses the accuracy of flood extent predictions in five U.S. watersheds. We generated flood maps for four return periods using various digital elevation models (DEMs)—FABDEM, SRTM, ALOS, and USGS 3DEP—and two versions of the GEOGLOWS River Forecast System (RFS) hydrography. These comparisons are notable because they build on operational global hydrology models so subsequent work can develop global modeled flood products. Models were made using the Automated Rating Curve (ARC) and Curve2Flood tools. Accuracy was measured against USGS reference maps using the F-statistic. Our results show that flood map accuracy generally increased with higher return periods. The most consistent and reliable improvements in accuracy occurred when both the DEM and hydrography datasets were upgraded to higher-resolution sources. While DEM improvements generally had a greater impact, hydrography refinements were more important for lower return periods when flood extents were the smallest. Generally, DEM resolution improved accuracy metrics more as the return period increased and hydrography and bare earth DEMs mattered more as the return period decreased. There was a 38.9% increase in the mean F-statistic between the two principal pairings of interest (FABDEM-RFS2 and SRTM 30 m DEM-RFS1). FABDEM’s bare-earth representation combined with RFS2 sometimes outperformed higher-resolution non-bare-earth DEMs, suggesting that there remains a need for site-specific investigation. Using ARC and Curve2Flood with FABDEM and RFS2 is a suitable baseline combination for general flood extent application. Full article
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21 pages, 12325 KiB  
Article
Inspection of Damaged Composite Structures with Active Thermography and Digital Shearography
by João Queirós, Hernâni Lopes, Luís Mourão and Viriato dos Santos
J. Compos. Sci. 2025, 9(8), 398; https://doi.org/10.3390/jcs9080398 (registering DOI) - 1 Aug 2025
Abstract
This study comprehensively compares the performance of two non-destructive testing (NDT) techniques—active thermography (AT) and digital shearography (DS)—for identifying various damage types in composite structures. Three distinct composite specimens were inspected: a carbon-fiber-reinforced polymer (CFRP) plate with flat-bottom holes, an aluminum honeycomb core [...] Read more.
This study comprehensively compares the performance of two non-destructive testing (NDT) techniques—active thermography (AT) and digital shearography (DS)—for identifying various damage types in composite structures. Three distinct composite specimens were inspected: a carbon-fiber-reinforced polymer (CFRP) plate with flat-bottom holes, an aluminum honeycomb core sandwich plate with a circular skin-core disbond, and a CFRP plate with two low-energy impacts damage. The research highlights the significant role of post-processing methods in enhancing damage detectability. For AT, algorithms such as fast Fourier transform (FFT) for temperature phase extraction and principal component thermography (PCT) for identifying significant temperature components were employed, generally making anomalies brighter and easier to locate and size. For DS, a novel band-pass filtering approach applied to phase maps, followed by summing the filtered maps, remarkably improved the visualization and precision of damage-induced anomalies by suppressing background noise. Qualitative image-based comparisons revealed that DS consistently demonstrated superior performance. The sum of DS filtered phase maps provided more detailed and precise information regarding damage location and size compared to both pulsed thermography (PT) and lock-in thermography (LT) temperature phase and amplitude. Notably, DS effectively identified shallow flat-bottom holes and subtle imperfections that AT struggled to clearly resolve, and it provided a more comprehensive representation of the impacts damage location and extent. This enhanced capability of DS is attributed to the novel phase map filtering approach, which significantly improves damage identification compared to the thermogram post-processing methods used for AT. Full article
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21 pages, 3469 KiB  
Article
The Effects of Dietary Supplementation with 25-Hydroxyvitamin D3 on the Antioxidant Capacity and Inflammatory Responses of Pelteobagrus fulvidraco
by Yi Liu, Jiang Xie, Qingchao Shi, Quan Gong and Chuanjie Qin
Biology 2025, 14(8), 967; https://doi.org/10.3390/biology14080967 (registering DOI) - 1 Aug 2025
Abstract
Based on the limited hepatic hydroxylation efficiency of dietary VD3 in teleosts and the superior bioavailability of its metabolite, 25(OH)D3, this study investigated the regulatory mechanisms of dietary 25(OH)D3 supplementation in yellow catfish—an economically significant species lacking prior nutritional data on this metabolite. [...] Read more.
Based on the limited hepatic hydroxylation efficiency of dietary VD3 in teleosts and the superior bioavailability of its metabolite, 25(OH)D3, this study investigated the regulatory mechanisms of dietary 25(OH)D3 supplementation in yellow catfish—an economically significant species lacking prior nutritional data on this metabolite. A total of 360 fish were divided into three groups—control (basal diet), VD3 (2500 IU/kg VD3), and 25(OH)D3 (2500 IU/kg 25(OH)D3)—and fed for 8 weeks. Compared to the control, both supplemented groups showed elevated superoxide dismutase (SOD), total antioxidant capacity (T-AOC), catalase (CAT), and transforming growth factor-β (TGF-β) activities, alongside reduced malondialdehyde (MDA), interleukin-1β (IL-1β), and tumor necrosis factor-α (TNF-α) levels. The 25(OH)D3 group exhibited higher T-AOC and CAT activities and lower TNF-α than the VD3 group. Metabolomic and transcriptomic analyses identified 65 differentially expressed metabolites (DEMs) and 3515 differentially expressed genes (DEGs). Enrichment analysis indicated that the DEMs (e.g., indole compounds, organic acids, aldosterone, L-kynurenine) and DEGs (pgd, mthfr, nsdhl, nox5, prdx2, mpx, itih2, itih3, eprs1) that were highly and significantly expressed in the 25(OH)D3 group were primarily associated with antioxidant defense and inflammatory responses. Dietary 25(OH)D3 was more effective than VD3 in promoting antioxidant capacity and modulating inflammation in yellow catfish. Full article
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22 pages, 5619 KiB  
Article
Design and Experiment of Air-Suction Roller-Type Minituber Seed-Metering Device Based on CFD-DEM
by Jicheng Li, Haiqin Ma, Yuxuan Chen, Xiaoxin Zhu, Yu Qi, Qiang Gao and Jinqing Lyu
Agriculture 2025, 15(15), 1652; https://doi.org/10.3390/agriculture15151652 - 31 Jul 2025
Abstract
Aiming at the problems of the high multiple- and missed-seeding index and low operation efficiency of current mechanical potato seed-meters in minituber sowing, this study designed an air-suction roller-type minituber seed-metering device for minitubers (mass between 2 and 4 g) in accordance with [...] Read more.
Aiming at the problems of the high multiple- and missed-seeding index and low operation efficiency of current mechanical potato seed-meters in minituber sowing, this study designed an air-suction roller-type minituber seed-metering device for minitubers (mass between 2 and 4 g) in accordance with the agronomic standards for potato cultivation in the single-cropping area of northern China. An account of the device’s structure and operational principle was made, its working process was theoretically analysed, and the three main factors affecting the airflow suction were determined: the seed roller speed, the suction seeding hole diameter, and the air inlet negative pressure. This study adopted the fluid dynamics simulation method and determined that the ideal location of the air inlet was 30° for horizontal inclination and 60° for vertical inclination. Then, based on the CFD-DEM fluid-structure coupling simulation method, the impact of a range of factors on the functionality of the seed-metering device under different conditions was studied and verification tests were carried out. Design-Expert was used to analyse test results. The results showed that when the pressure at the air inlet was −7000 Pa, the speed of the seeding roller was 40.2 r·min−1, the suction seeding hole diameter was 10.37 mm, and the performance was optimal: the qualified index was 92.95%, the multiple-seeding index was 4.16%, and the missed-seeding index was 2.89%. The research results show that the seed-metering device developed under this scheme exhibited satisfactory seeding performance during operation and was able to meet the demands of minituber sowing. Full article
(This article belongs to the Section Agricultural Technology)
26 pages, 4289 KiB  
Article
A Voronoi–A* Fusion Algorithm with Adaptive Layering for Efficient UAV Path Planning in Complex Terrain
by Boyu Dong, Gong Zhang, Yan Yang, Peiyuan Yuan and Shuntong Lu
Drones 2025, 9(8), 542; https://doi.org/10.3390/drones9080542 (registering DOI) - 31 Jul 2025
Abstract
Unmanned Aerial Vehicles (UAVs) face significant challenges in global path planning within complex terrains, as traditional algorithms (e.g., A*, PSO, APF) struggle to balance computational efficiency, path optimality, and safety. This study proposes a Voronoi–A* fusion algorithm, combining Voronoi-vertex-based rapid trajectory generation with [...] Read more.
Unmanned Aerial Vehicles (UAVs) face significant challenges in global path planning within complex terrains, as traditional algorithms (e.g., A*, PSO, APF) struggle to balance computational efficiency, path optimality, and safety. This study proposes a Voronoi–A* fusion algorithm, combining Voronoi-vertex-based rapid trajectory generation with A* supplementary expansion for enhanced performance. First, an adaptive DEM layering strategy divides the terrain into horizontal planes based on obstacle density, reducing computational complexity while preserving 3D flexibility. The Voronoi vertices within each layer serve as a sparse waypoint network, with greedy heuristic prioritizing vertices that ensure safety margins, directional coherence, and goal proximity. For unresolved segments, A* performs localized searches to ensure complete connectivity. Finally, a line-segment interpolation search further optimizes the path to minimize both length and turning maneuvers. Simulations in mountainous environments demonstrate superior performance over traditional methods in terms of path planning success rates, path optimality, and computation. Our framework excels in real-time scenarios, such as disaster rescue and logistics, although it assumes static environments and trades slight path elongation for robustness. Future research should integrate dynamic obstacle avoidance and weather impact analysis to enhance adaptability in real-world conditions. Full article
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39 pages, 21783 KiB  
Article
Leveraging High-Frequency UAV–LiDAR Surveys to Monitor Earthflow Dynamics—The Baldiola Landslide Case Study
by Francesco Lelli, Marco Mulas, Vincenzo Critelli, Cecilia Fabbiani, Melissa Tondo, Marco Aleotti and Alessandro Corsini
Remote Sens. 2025, 17(15), 2657; https://doi.org/10.3390/rs17152657 (registering DOI) - 31 Jul 2025
Abstract
UAV platforms equipped with RTK positioning and LiDAR sensors are increasingly used for landslide monitoring, offering frequent, high-resolution surveys with broad spatial coverage. In this study, we applied high-frequency UAV-based monitoring to the active Baldiola earthflow (Northern Apennines, Italy), integrating 10 UAV–LiDAR and [...] Read more.
UAV platforms equipped with RTK positioning and LiDAR sensors are increasingly used for landslide monitoring, offering frequent, high-resolution surveys with broad spatial coverage. In this study, we applied high-frequency UAV-based monitoring to the active Baldiola earthflow (Northern Apennines, Italy), integrating 10 UAV–LiDAR and photogrammetric surveys, acquired at average intervals of 14 days over a four-month period. UAV-derived orthophotos and DEMs supported displacement analysis through homologous point tracking (HPT), with robotic total station measurements serving as ground-truth data for validation. DEMs were also used for multi-temporal DEM of Difference (DoD) analysis to assess elevation changes and identify depletion and accumulation patterns. Displacement trends derived from HPT showed strong agreement with RTS data in both horizontal (R2 = 0.98) and vertical (R2 = 0.94) components, with cumulative displacements ranging from 2 m to over 40 m between April and August 2024. DoD analysis further supported the interpretation of slope processes, revealing sector-specific reactivations and material redistribution. UAV-based monitoring provided accurate displacement measurements, operational flexibility, and spatially complete datasets, supporting its use as a reliable and scalable tool for landslide analysis. The results support its potential as a stand-alone solution for both monitoring and emergency response applications. Full article
18 pages, 3666 KiB  
Article
Integrating UAV and USV for Elaboration of High-Resolution Coastal Elevation Models
by Isabel López, Luis Bañón and José I. Pagán
J. Mar. Sci. Eng. 2025, 13(8), 1464; https://doi.org/10.3390/jmse13081464 - 30 Jul 2025
Abstract
Coastal erosion, exacerbated by climate change, poses a critical global threat to both the environment and human livelihoods. Acquiring accurate, high-resolution topo-bathymetric data is vital for understanding these dynamic environments, without underestimating the hydrodynamic and meteo-oceanographic conditions. However, traditional methods often present significant [...] Read more.
Coastal erosion, exacerbated by climate change, poses a critical global threat to both the environment and human livelihoods. Acquiring accurate, high-resolution topo-bathymetric data is vital for understanding these dynamic environments, without underestimating the hydrodynamic and meteo-oceanographic conditions. However, traditional methods often present significant challenges in achieving comprehensive, high-resolution topo-bathymetric coverage efficiently in shallow coastal zones, leading to a notable ”white ribbon” data gap. This study introduces a novel, integrated methodology combining unmanned aerial vehicles (UAVs) for terrestrial surveys, unmanned surface vehicles (USVs) for bathymetry, and the Global Navigation Satellite System (GNSS) for ground control and intertidal gap-filling. Through this technologically rigorous approach, a seamless Bathymetry-Topography Digital Surface Model for the Guardamar del Segura dune system (Spain) was successfully elaborated using a DJI Mini 2 UAV, Leica Zeno FLX100 GNSS, and Apache 3 USV. The method demonstrated a substantial time reduction of at least 50–75% for comparable high-resolution coverage, efficiently completing the 86.4 ha field campaign in approximately 4 h. This integrated approach offers an accessible and highly efficient solution for generating detailed coastal elevation models crucial for coastal management and research. Full article
(This article belongs to the Special Issue Monitoring Coastal Systems and Improving Climate Change Resilience)
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15 pages, 2006 KiB  
Article
Hydrological Responses to Territorial Spatial Change in the Xitiaoxi River Basin: A Simulation Study Using the SWAT Model Driven by China Meteorological Assimilation Driving Datasets
by Dongyan Kong, Huiguang Chen and Kongsen Wu
Water 2025, 17(15), 2267; https://doi.org/10.3390/w17152267 - 30 Jul 2025
Viewed by 93
Abstract
The use of the Soil and Water Assessment Tool (SWAT) model driven by China Meteorological Assimilation Driving Datasets (CMADS) for runoff simulation research is of great significance for regional flood prevention and control. Therefore, from the perspective of production-living-ecological space, this article combined [...] Read more.
The use of the Soil and Water Assessment Tool (SWAT) model driven by China Meteorological Assimilation Driving Datasets (CMADS) for runoff simulation research is of great significance for regional flood prevention and control. Therefore, from the perspective of production-living-ecological space, this article combined multi-source data such as DEM, soil texture and land use type, in order to construct scenarios of territorial spatial change (TSC) across distinct periods. Based on the CMADS-L40 data and the SWAT model, it simulated the runoff dynamics in the Xitiaoxi River Basin, and analyzed the hydrological response characteristics under different TSCs. The results showed that The SWAT model, driven by CMADS-L40 data, demonstrated robust performance in monthly runoff simulation. The coefficient of determination (R2), Nash–Sutcliffe efficiency coefficient (NSE), and the absolute value of percentage bias (|PBIAS|) during the calibration and validation period all met the accuracy requirements of the model, which validated the applicability of CMADS-L40 data and the SWAT model for runoff simulation at the watershed scale. Changes in territorial spatial patterns are closely correlated with runoff variation. Changes in agricultural production space and forest ecological space show statistically significant negative correlation with runoff change, while industrial production space change exhibits a significant positive correlation with runoff change. The expansion of production space, particularly industrial production space, leads to increased runoff, whereas the enlargement of agricultural production space and forest ecological space can reduce runoff. This article contributes to highlighting the role of land use policy in hydrological regulation, providing a scientific basis for optimizing territorial spatial planning to mitigate flood risks and protect water resources. Full article
(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction, 2nd Edition)
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25 pages, 9707 KiB  
Article
Mesoscale Mechanical Analysis of Concrete Based on a 3D Random Aggregate Model
by Shuaishuai Wei, Huan Zhang, Ding Wang, Xuchun Wang and Mengdi Cao
Coatings 2025, 15(8), 883; https://doi.org/10.3390/coatings15080883 - 29 Jul 2025
Viewed by 191
Abstract
The shape, size, and interfacial transition zone (ITZ) of aggregates significantly impact the nonlinear mechanical behavior of concrete. This study investigates concrete’s mechanical response and damage mechanisms by developing a three-dimensional, three-phase mesoscale model comprising coarse aggregates, mortar, and ITZ to explore the [...] Read more.
The shape, size, and interfacial transition zone (ITZ) of aggregates significantly impact the nonlinear mechanical behavior of concrete. This study investigates concrete’s mechanical response and damage mechanisms by developing a three-dimensional, three-phase mesoscale model comprising coarse aggregates, mortar, and ITZ to explore the compressive performance of concrete. A method for simulating the random distribution of aggregates based on three-dimensional grid partitioning is proposed, where the value of each grid point represents the maximum aggregate radius that can be accommodated if the point serves as the aggregate center. Aggregates are generated by randomly selecting grid points that meet specific conditions, avoiding overlapping distributions and significantly improving computational efficiency as the generation progresses. This model effectively enhances the precision and efficiency of aggregate distribution and provides a reliable tool for studying the random distribution characteristics of aggregates in concrete. Additionally, an efficient discrete element model (DEM) was established based on this mesoscale model to simulate the compressive behavior of concrete, including failure modes and stress–strain curves. The effects of aggregate shape and maximum aggregate size on the uniaxial compressive failure behavior of concrete specimens were investigated. Aggregate shape has a particular influence on the compressive strength of concrete, and the compressive strength decreases with an increase in maximum aggregate size. Combined with existing experimental results, the proposed mesoscale model demonstrates high reliability in analyzing the compressive performance of concrete, providing valuable insights for further research on the mechanical properties of concrete. Full article
(This article belongs to the Special Issue Advances in Pavement Materials and Civil Engineering)
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24 pages, 4396 KiB  
Article
Study of the Characteristics of a Co-Seismic Displacement Field Based on High-Resolution Stereo Imagery: A Case Study of the 2024 MS7.1 Wushi Earthquake, Xinjiang
by Chenyu Ma, Zhanyu Wei, Li Qian, Tao Li, Chenglong Li, Xi Xi, Yating Deng and Shuang Geng
Remote Sens. 2025, 17(15), 2625; https://doi.org/10.3390/rs17152625 - 29 Jul 2025
Viewed by 175
Abstract
The precise characterization of surface rupture zones and associated co-seismic displacement fields from large earthquakes provides critical insights into seismic rupture mechanisms, earthquake dynamics, and hazard assessments. Stereo-photogrammetric digital elevation models (DEMs), produced from high-resolution satellite stereo imagery, offer reliable global datasets that [...] Read more.
The precise characterization of surface rupture zones and associated co-seismic displacement fields from large earthquakes provides critical insights into seismic rupture mechanisms, earthquake dynamics, and hazard assessments. Stereo-photogrammetric digital elevation models (DEMs), produced from high-resolution satellite stereo imagery, offer reliable global datasets that are suitable for the detailed extraction and quantification of vertical co-seismic displacements. In this study, we utilized pre- and post-event WorldView-2 stereo images of the 2024 Ms7.1 Wushi earthquake in Xinjiang to generate DEMs with a spatial resolution of 0.5 m and corresponding terrain point clouds with an average density of approximately 4 points/m2. Subsequently, we applied the Iterative Closest Point (ICP) algorithm to perform differencing analysis on these datasets. Special care was taken to reduce influences from terrain changes such as vegetation growth and anthropogenic structures. Ultimately, by maintaining sufficient spatial detail, we obtained a three-dimensional co-seismic displacement field with a resolution of 15 m within grid cells measuring 30 m near the fault trace. The results indicate a clear vertical displacement distribution pattern along the causative sinistral–thrust fault, exhibiting alternating uplift and subsidence zones that follow a characteristic “high-in-center and low-at-ends” profile, along with localized peak displacement clusters. Vertical displacements range from approximately 0.2 to 1.4 m, with a maximum displacement of ~1.46 m located in the piedmont region north of the Qialemati River, near the transition between alluvial fan deposits and bedrock. Horizontal displacement components in the east-west and north-south directions are negligible, consistent with focal mechanism solutions and surface rupture observations from field investigations. The successful extraction of this high-resolution vertical displacement field validates the efficacy of satellite-based high-resolution stereo-imaging methods for overcoming the limitations of GNSS and InSAR techniques in characterizing near-field surface displacements associated with earthquake ruptures. Moreover, this dataset provides robust constraints for investigating fault-slip mechanisms within near-surface geological contexts. Full article
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19 pages, 8766 KiB  
Article
Fusion of Airborne, SLAM-Based, and iPhone LiDAR for Accurate Forest Road Mapping in Harvesting Areas
by Evangelia Siafali, Vasilis Polychronos and Petros A. Tsioras
Land 2025, 14(8), 1553; https://doi.org/10.3390/land14081553 - 28 Jul 2025
Viewed by 207
Abstract
This study examined the integraftion of airborne Light Detection and Ranging (LiDAR), Simultaneous Localization and Mapping (SLAM)-based handheld LiDAR, and iPhone LiDAR to inspect forest road networks following forest operations. The goal is to overcome the challenges posed by dense canopy cover and [...] Read more.
This study examined the integraftion of airborne Light Detection and Ranging (LiDAR), Simultaneous Localization and Mapping (SLAM)-based handheld LiDAR, and iPhone LiDAR to inspect forest road networks following forest operations. The goal is to overcome the challenges posed by dense canopy cover and ensure accurate and efficient data collection and mapping. Airborne data were collected using the DJI Matrice 300 RTK UAV equipped with a Zenmuse L2 LiDAR sensor, which achieved a high point density of 285 points/m2 at an altitude of 80 m. Ground-level data were collected using the BLK2GO handheld laser scanner (HPLS) with SLAM methods (LiDAR SLAM, Visual SLAM, Inertial Measurement Unit) and the iPhone 13 Pro Max LiDAR. Data processing included generating DEMs, DSMs, and True Digital Orthophotos (TDOMs) via DJI Terra, LiDAR360 V8, and Cyclone REGISTER 360 PLUS, with additional processing and merging using CloudCompare V2 and ArcGIS Pro 3.4.0. The pairwise comparison analysis between ALS data and each alternative method revealed notable differences in elevation, highlighting discrepancies between methods. ALS + iPhone demonstrated the smallest deviation from ALS (MAE = 0.011, RMSE = 0.011, RE = 0.003%) and HPLS the larger deviation from ALS (MAE = 0.507, RMSE = 0.542, RE = 0.123%). The findings highlight the potential of fusing point clouds from diverse platforms to enhance forest road mapping accuracy. However, the selection of technology should consider trade-offs among accuracy, cost, and operational constraints. Mobile LiDAR solutions, particularly the iPhone, offer promising low-cost alternatives for certain applications. Future research should explore real-time fusion workflows and strategies to improve the cost-effectiveness and scalability of multisensor approaches for forest road monitoring. Full article
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16 pages, 4347 KiB  
Technical Note
Combining TanDEM-X Interferometry and GEDI Space LiDAR for Estimation of Forest Biomass Change in Tanzania
by Svein Solberg, Belachew Gizachew, Laura Innice Duncanson and Paromita Basak
Remote Sens. 2025, 17(15), 2623; https://doi.org/10.3390/rs17152623 - 28 Jul 2025
Viewed by 319
Abstract
The background for this study is the limitations of the conventional approach of using deforestation area multiplied by biomass densities or emission factors. We demonstrated how TanDEM-X and GEDI data can be combined to estimate forest Above Ground Biomass (AGB) change at the [...] Read more.
The background for this study is the limitations of the conventional approach of using deforestation area multiplied by biomass densities or emission factors. We demonstrated how TanDEM-X and GEDI data can be combined to estimate forest Above Ground Biomass (AGB) change at the national scale for Tanzania. The results can be further recalculated to estimate CO2 emissions and removals from the forest. We used repeated short wavelength, InSAR DEMs from TanDEM-X to derive changes in forest canopy height and combined this with GEDI data to convert such height changes to AGB changes. We estimated AGB change during 2012–2019 to be −2.96 ± 2.44 MT per year. This result cannot be validated, because the true value is unknown. However, we corroborated the results by comparing with other approaches, other datasets, and the results of other studies. In conclusion, TanDEM-X and GEDI can be combined to derive reliable temporal change in AGB at large scales such as a country. An important advantage of the method is that it is not required to have a representative field inventory plot network nor a full coverage DTM. A limitation for applying this method now is the lack of frequent and systematic InSAR elevation data. Full article
(This article belongs to the Section Biogeosciences Remote Sensing)
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28 pages, 5315 KiB  
Article
Integrated Transcriptome and Metabolome Analysis Provides Insights into the Low-Temperature Response in Sweet Potato (Ipomoea batatas L.)
by Zhenlei Liu, Jiaquan Pan, Sitong Liu, Zitong Yang, Huan Zhang, Tao Yu and Shaozhen He
Genes 2025, 16(8), 899; https://doi.org/10.3390/genes16080899 - 28 Jul 2025
Viewed by 238
Abstract
Background/Objectives: Sweet potato is a tropical and subtropical crop and its growth and yield are susceptible to low-temperature stress. However, the molecular mechanisms underlying the low temperature stress of sweetpotato are unknown. Methods: In this work, combined transcriptome and metabolism analysis was employed [...] Read more.
Background/Objectives: Sweet potato is a tropical and subtropical crop and its growth and yield are susceptible to low-temperature stress. However, the molecular mechanisms underlying the low temperature stress of sweetpotato are unknown. Methods: In this work, combined transcriptome and metabolism analysis was employed to investigate the low-temperature responses of two sweet potato cultivars, namely, the low-temperature-resistant cultivar “X33” and the low-temperature-sensitive cultivar “W7”. Results: The differentially expressed metabolites (DEMs) of X33 at different time stages clustered in five profiles, while they clustered in four profiles of W7 with significant differences. Differentially expressed genes (DEGs) in X33 and W7 at different time points clustered in five profiles. More DEGs exhibited continuous or persistent positive responses to low-temperature stress in X33 than in W7. There were 1918 continuously upregulated genes and 6410 persistent upregulated genes in X33, whereas 1781 and 5804 were found in W7, respectively. Core genes involved in Ca2+ signaling, MAPK cascades, the reactive oxygen species (ROS) signaling pathway, and transcription factor families (including bHLH, NAC, and WRKY) may play significant roles in response to low temperature in sweet potato. Thirty-one common differentially expressed metabolites (DEMs) were identified in the two cultivars in response to low temperature. The KEGG analysis of these common DEMs mainly belonged to isoquinoline alkaloid biosynthesis, phosphonate and phosphinate metabolism, flavonoid biosynthesis, cysteine and methionine metabolism, glycine, serine, and threonine metabolism, ABC transporters, and glycerophospholipid metabolism. Five DEMs with identified Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were selected for correlation analysis. KEGG enrichment analysis showed that the carbohydrate metabolism, phenylpropanoid metabolism, and glutathione metabolism pathways were significantly enriched and played vital roles in low-temperature resistance in sweet potato. Conclusions: These findings contribute to a deeper understanding of the molecular mechanisms underlying plant cold tolerance and offer targets for molecular breeding efforts to enhance low-temperature resistance. Full article
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18 pages, 3997 KiB  
Article
Simulation of Dynamic Particle Trapping and Accumulation in HGMS Based on FEM-CFD-DEM Coupling Approach
by Xiaoming Wang, Yonghui Hu, Yefei Hao, Zhengchang Shen, Guodong Liang and Ming Zhang
Processes 2025, 13(8), 2391; https://doi.org/10.3390/pr13082391 - 28 Jul 2025
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Abstract
High-gradient magnetic separation (HGMS) is a conventional and effective method for processing weak magnetic materials. A multi-field dynamic coupling simulation method integrating the Finite Element Method (FEM), Computational Fluid Dynamics (CFD), and the Discrete Element Method (DEM) was employed to investigate the separation [...] Read more.
High-gradient magnetic separation (HGMS) is a conventional and effective method for processing weak magnetic materials. A multi-field dynamic coupling simulation method integrating the Finite Element Method (FEM), Computational Fluid Dynamics (CFD), and the Discrete Element Method (DEM) was employed to investigate the separation behavior in HGMS. The dynamic deposition process of magnetic particles under the interactions of magnetic fields, fluid flow fields, and particle–particle forces was simulated using a two-way fluid–solid coupling algorithm based on the FEM-CFD-DEM coupling approach. Experimental results demonstrated that the particle deposition profiles predicted by the double-wire medium model were in good agreement with the measured data. The research findings indicated that the separation process could be divided into three distinct stages—the adsorption stage, the closure stage, and the clogging stage—each characterized by unique dynamic behaviors and pressure-drop evolution patterns. Additionally, the effects of key parameters such as the feeding velocity and medium filling ratio on the separation process were analyzed, providing theoretical foundations and technical support for the optimization of HGMS processes and the enhancement of separation efficiency. Full article
(This article belongs to the Special Issue Mineral Processing Equipments and Cross-Disciplinary Approaches)
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