Search Results (23)

The detection of seafloor signal photons in various topographies is challenging. Previous research has divided photons into clusters based solely on their density, which is closely related to the settings of the empirical parameters. Inappropriate parameters may mistakenly identify the water column noise photons as seafloor photons. To overcome these limitations, this study introduces a novel slope iterative adaptive filter (SIAF) method that innovatively integrates ICESat-2 ATL03 photon data with Sentinel-2-derived topographic slopes. Inspired by satellite-derived bathymetry, we extracted topographic slopes from multispectral images as auxiliary information to guide the photon extraction. The initial slope estimation was derived from the multispectral images, and the optimal slope direction was determined iteratively, using the detected signal photons in each step. The average and maximum overall accuracies of SIAF were 93.43% and 95.7%, respectively. The validation of the extraction results with sonar data indicated that the SIAF achieved an average root mean square error (RMSE) of 0.49 m. Crucially, the SIAF resolves critical shortcomings of prior techniques: (1) it avoids the isotropic assumption of density-based methods, (2) it mitigates AVEBM’s vulnerability to noise in steep-slope regions, and (3) it enables robust automation without manual parameter tuning. Consequently, SIAF proved to be an efficient approach for the automatic mapping of water depths in shallow-water zones. Full article

Tropical forests provide essential ecosystem services, playing a critical role in climate regulation, biodiversity conservation, and regional hydrological cycles while also supporting livelihoods. However, they are increasingly threatened by deforestation and land-use change. Accurate land cover (LC) mapping is vital to monitor these changes, but mapping tropical forests is challenging due to complex spatial patterns, spectral similarities, and frequent cloud cover. This study aims to improve LC classification accuracy in such a heterogeneous tropical forest region in Southeast Asia, namely Kulen, Cambodia, which is characterized by natural forests, regrowth forests, and agricultural lands including cashew plantations and croplands, using Sentinel-2 imagery, recursive feature elimination (RFE), and Random Forest. We generated 65 variables of spectral bands, indices, bi-seasonal differences, and topographic data from Sentinel-2 Level-2A and Shuttle Radar Topography Mission datasets. These variables were extracted from 1000 random points per 12 LC classes from reference polygons based on observed GPS points, Uncrewed Aerial Vehicle imagery, and high-resolution satellite data. The random forest models were optimized through correlation-based filtering and recursive feature elimination with hyperparameter tuning to improve classification accuracy, validated via confusion matrices and comparisons with global and national-scale products. Our results highlight the significant role of topographic variables such as elevation and slope, along with red-edge spectral bands and spectral indices related to tillage, leaf water content, greenness, chlorophyll, and tasseled cap transformation for tropical land cover mapping. The integration of bi-seasonal datasets improved classification accuracy, particularly for challenging classes like semi-evergreen and deciduous forests. Furthermore, correlation-based filtering and recursive feature elimination reduced the variable set from 65 to 19, improving model efficiency without sacrificing accuracy. Combining these variable selection methods with hyperparameter tuning optimized the classification, providing a more reliable LC product that outperforms existing LC products and proves valuable for deforestation monitoring, forest management, biodiversity conservation, and land use studies. Full article

This article delves into the advancements in indoor navigation in metro stations and describes the development and implementation of algorithms for the automatic generation of navigation guidance. The LIFT project at the Warsaw University of Technology serves as a practical example, showcasing a system designed to cater to people with special needs. This article presents a rule-based algorithm that generates navigation directions based on a trade-off between landmark references and spatial references in relation to the user’s location. The research uses a spatial data model consisting of three interconnected layers: the transport network, the room topology, and the building topography. The algorithm uses these data in subsequent stages. A defined set of rules generates redundant navigation directions for all potential decision points and then, subsequent rules filter and generalise them. To discuss the details of how the algorithm works, an example route is described in this study and the consequences of applying the selected rules are analysed. Next, a few problems that arose during the testing of the algorithm at Warsaw Metro stations are presented with proposed solutions. The results of the study made it possible to develop a mobile application, which is planned to be available to users by the end of 2024. Full article

(1) Background: The electroencephalogram (EEG) is frequently corrupted by ocular artifacts such as saccades and blinks. Methods for correcting these artifacts include independent component analysis (ICA) and recursive-least-squares (RLS) adaptive filtering (-AF). Here, we introduce a new method, AFFiNE, that applies Bayesian adaptive regression spline (BARS) fitting to the adaptive filter’s reference noise input to address the known limitations of both ICA and RLS-AF, and then compare the performance of all three methods. (2) Methods: Artifact-corrected P300 morphologies, topographies, and measurements were compared between the three methods, and to known truth conditions, where possible, using real and simulated blink-corrupted event-related potential (ERP) datasets. (3) Results: In both simulated and real datasets, AFFiNE was successful at removing the blink artifact while preserving the underlying P300 signal in all situations where RLS-AF failed. Compared to ICA, AFFiNE resulted in either a practically or an observably comparable error. (4) Conclusions: AFFiNE is an ocular artifact correction technique that is implementable in online analyses; it can adapt to being non-stationarity and is independent of channel density and recording duration. AFFiNE can be utilized for the removal of blink artifacts in situations where ICA may not be practically or theoretically useful. Full article

Understanding the process underlying species coexistence is crucial in ecology. This challenge is relevant in tree communities inhabiting contrasting abiotic conditions, such as lowland floodplain and shallow hillslope karstic systems. We examined the influence of topographic variables and spatial factors on the structure of tree communities in the karstic system in Calakmul, Mexico. We measured 7050 trees (diameter at breast height ≥ 3 cm) in 152 circular plots and generated seven topographic variables from a digital elevation model. We employed redundancy analysis and variance partitioning to test the effects of environmental and spatial factors on tree communities. In addition, we used the null Raup–Crick model to uncover the relative importance of the deterministic and stochastic processes driving community assembly. Our study revealed significant floristic distinction between seasonally flooded and upland forests. The topographic wetness index (TWI) contribution to explaining the floristic differentiation in the studied tree assemblages was greater than that of the other topography-related variables. The explanatory power of the environmental and spatial factors varied slightly between datasets. The null model indicated a predominant influence of deterministic over stochastic processes. Our findings reaffirm the role of seasonal flooding as an abiotic filter. Additionally, the TWI can serve to identify flood-prone conditions within shallow depressions. The preservation of adjacent seasonally flooded and upland forests is relevant for the maintenance of tree diversity in the karst of the Yucatan Peninsula, since flooding drives the distribution of species. Full article

The importance of incorporating hyaluronic acid (HA) as a cosmetic ingredient in skin care formulations emerged lately because the amount of HA naturally found in the epidermis decreases with age, and when applied to the skin through cosmetic products, it confers hydration and reduces the appearance of wrinkles. Currently, the diversity of cosmetic products for mature skin and the use of various and innovative active ingredients supporting their anti-ageing effect represent ample proof that the cosmetic industry is currently relying on these actives. The main objective of this study was the development of an anti-ageing formulation, incorporating HA and different other active ingredients. The developed formulation contains a novel complex of natural waxes, with an essential role in the restoration of the skin’s hydro–lipid barrier, in combination with innovative active ingredients—like low-molecular hyaluronic acid (LMW-HA), sodium hyaluronate (NaHA), ectoin, gold, and an anti-ageing botanical complex—contributing to optimal skin hydration specifically designed to reduce the visible signs of ageing. An important objective was represented by the skin compatibility and topography assessment after 28 days (D28) of regular application of the developed cream. Stability testing, physicochemical characteristics, and microbiological control, including efficacy testing of the used preservative (challenge test) were performed for the cosmetic formulation. In silico approaches were applied to demonstrate the safety of cosmetic-related substances and the risk assessment of the cosmetic formulation. Safety and instrumental evaluation were performed to demonstrate the skin tolerance—the compatibility and the efficacy, respectively—of the developed anti-ageing cream. As result, quality control of the developed cosmetic formulation evidenced an appropriate cosmetic preparation with desirable aspect and adequate physicochemical characteristics. The concentrations of restricted ingredients like preservatives and UV filters were in accordance with those recommended by the Regulation (EC) No. 1223/2009 and so were considered to be safe. Additionally, according to the margin of safety (MoS) calculation, cosmetic ingredients incorporated in the developed formulation could be considered safe. The developed formulation was very well tolerated, and wrinkle depth and length in the periorbital area were significantly reduced after 28-day cosmetic treatment. Subjects’ assessment questionnaires revealed self-perceived benefits referring to the cosmetic qualities and efficacy of the anti-ageing cream. This study confirmed the skin tolerance and efficacy of the new complex anti-ageing cream incorporating HA, microencapsulated sodium hyaluronate, ectoin, and a botanical extract. The formulated cosmetic product could serve as a daily care for mature skin to alleviate the effects of skin ageing. Full article

In this study, we present the feasibility of using gravity measurements made with a small inertial navigation system (INS) during in situ experiments, and also mounted on an unmanned aerial vehicle (UAV), to recover local gravity field variations. The INS operated is the SPATIAL one developed by Advanced Navigation, which has three-axis accelerometers. When the temperature bias is corrected, these types of INS are powerful enough to present the periodic signal corresponding to the solid Earth tides. There is also a clear correlation with the data measured at different altitudes by a CG5 gravimeter. However, these data were recorded on static points, so we also studied the INS in a moving platform on a UAV. Because there are a lot of vibrations recorded by the INS (wind, motor, on-board computer), the GPS and accelerometric data need to be filtered extensively. Once the data are corrected so they do not show thermal bias and low-pass filtered, we take the second derivative of the altitude (GPS) data to find the radial accelerometry of the drone and compare it to the radial accelerometry measured directly by the INS, in order to isolate the accelerometric signal that is related to the area that is being studied and the altitude. With a high enough precision, this method could be used to obtain the gravity variations due to the topography and density variations in the ground. Full article

To understand the activity of gravity waves (GWs) over the Tibetan Plateau (TP) is of great significance for improving global climate models. Considering that the lower stratosphere is the main level of GWs activity, this paper first established a 14-year 2° × 2° longitude–latitude monthly mean GWs model in the lower stratosphere (18~20 km) of the TP by combining post-processed dry temperature profiles provided by the multi-Global Navigation Satellite System (GNSS) radio occultation (RO) missions: The Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) and the Meteorological Operational (METOP) series polar-orbiting meteorological satellites (METOP-A, METOP-B, and METOP-C) from August 2006 to September 2020. Based on this model, this paper analyzed the characteristics of GWs activity around TP and the effects of topography, background wind, and zonal wind on GWs activity and summarized the general process of topographic wave excitation and upward propagation around TP. The spatial distribution of the lower stratospheric GW Ep is highly correlated with the spatial distribution of background wind and the topography of TP during GWs excitation. The GW Ep is obviously filtered by the zero-speed wind. The change in GW Ep is strongly correlated with the change in topography. These phenomena indicate that the GWs of TP are mainly topographic waves. Moreover, the lower stratospheric GW Ep of TP shows that periodic changes are mainly affected by the periodic background wind, and the GW Ep value is larger in February and smaller in August. The large GW Ep in the lower stratosphere of TP is not only related to the GWs strongly generated by the interaction between the strong background wind and the large elevation or large topographic changes but also related to the strong zonal westerly winds that promote the propagation of GWs upward. Multivariable linear regression models were used to reconstruct the lower stratospheric GW Ep over TP based on the background wind and the zonal wind and a goodness of fit of 81.1% was achieved. It indicates that the GW Ep is dominated by the topographic wave over TP in the lower stratosphere and the background wind has a greater influence on the GWs than the zonal wind. Full article

Time-series interferometric synthetic aperture radar (TS-InSAR) is often affected by tropospheric artifacts caused by temporal and spatial variability in the atmospheric refractive index. Conventional temporal and spatial filtering cannot effectively distinguish topography-related stratified delays, leading to biased estimates of the deformation phases. Here, we propose a TS-InSAR atmospheric delay correction method based on ERA-5; the robustness and accuracy of ERA-5 data under the influence of different atmospheric delays were explored. Notably, (1) wet delay was the main factor affecting tropospheric delay within the interferogram; the higher spatial and temporal resolution of ERA-5 can capture the wet delay signal better than MERRA-2. (2) The proposed method can mitigate the atmospheric delay component in the interferogram; the average standard deviation (STD) reduction for the Radarsat-2 and Sentinel-1A interferograms were 19.68 and 14.75%, respectively. (3) Compared to the empirical linear model, the correlation between the stratified delays estimated by the two methods reached 0.73. We applied this method for the first time to a ground subsidence study in the Yuxi Basin and successfully detected three subsidence centers. We analyzed and discussed ground deformation causes based on rainfall and fault zones. Finally, we verified the accuracy of the proposed method by using leveling monitoring data. Full article

Vegetation phenology changes are able to reveal climate-change-associated ecosystem feedback mechanisms. In this study, Qinghai–Tibet Plateau (QTP) alpine vegetation phenological information was extracted from the normalised difference vegetation index of the MOD13Q1 product collected from 2001 to 2020 using TIMESAT3.3 and S-G filtering and threshold dynamics methods. An analysis of data from the start of growth (SOG) and end of growth (EOG) seasons using a Theil–Sen median slope trend and partial correlation analyses revealed spatial and temporal variations in vegetation phenology related to climate change and topography, including: (1) significant spatial variation, gradually increasing southeast-to-northwest SOG delays and northeast-to-southwest EOG delays, with significant variations across vegetation types; (2) significant altitude-associated variations in the meadow, steppe, and shrub alpine vegetation types with high-altitude boundaries of 2400 m, 2800 m, and 2600 m, respectively, with delayed and earlier SOG and EOG below and above each boundary, respectively; and (3) spatial variations in relationships between vegetation phenology changes and climatic factors, where SOG negatively and EOG positively correlated with temperature and precipitation. The mean temperature in the 30 days before SOG and mean total precipitation in the 30 days before EOG were significantly correlated with SOG and EOG timing both negatively and positively, respectively. These results provide guidance for the monitoring of the alpine vegetation phenology on the QTP. Full article

Marine sediment transport is closely related to seafloor topography, material transport, marine engineering safety, etc. With a developed time-series vector observation device, the sediment capture and transport process can be observed. The structure of the capture tube and the internal filter screen can significantly affect the flow field during the actual observation, further influencing the sediment transport observation and particle capture process. This paper presents a numerical model for investigating the effect of device structure on seawater flow to study the processes of marine sediment transport observation and sediment particle capture. The model is based on the solution of both porous media and the Realizable k-ε turbulence in Fluent software. The flow velocity distribution inside and outside the capture tube with different screen pore sizes (0.300, 0.150, and 0.075 mm) is analyzed. To enhance the reliability of the numerical simulation, the simulation calculation results are compared with the test results and have good coincidence. Finally, by analyzing the motion law of sediment in the capture tube, the accurate capture of sediment particles is achieved, and the optimal capture efficiency of the sediment trap is obtained. Full article

With an increasing demand for accurate and reliable estimates of sea surface heights (SSH) from coastal and marine applications, approaches based on GNSS positioning have become favored, to bridge the gap between tide gauge (TG) and altimetry measurements in the coastal zone, and to complement offshore altimetry data. This study developed a complete methodology for jointly deriving and validating shipborne GNSS-determined SSH, using a geoid model and realistic dynamic topography estimates. An approach that combines the properties of hydrodynamic models and TG data was developed to obtain the latter. Tide gauge data allow estimating the spatiotemporal bias of a hydrodynamic model and, thus, linking it to the used vertical datums (e.g., a novel geoid-based Baltic Sea Chart Datum 2000). However, TG data may be erroneous and represent different conditions than offshore locations. The qualities of spatiotemporal bias are, hence, used to constrain TG data errors. Furthermore, a rigid system of four GNSS antennas was used to ensure SSH accuracy. Besides eliminating the vessel’s attitude effect on measurement data, the rigid system also provides a means for internal validation, suggesting a 4.1 cm height determination accuracy in terms of standard deviation. The methodology also involves eliminating the effect of sea state conditions via a low-pass filter and empirical estimation of vessel sailing-related corrections, such as the squat effect. The different data validation (e.g., examination of residual values and intersection analyses) results, ranging from 1.8 cm to 5.5 cm in terms of standard deviation, indicate an SSH determination accuracy of around 5 cm. Full article

Human activities have caused a significant change in the function and services that ecosystems have provided to society since historical times. In mountainous landscapes, the regulation of services such as water quality or erosion control has been impacted by land use and land cover (LULC) changes, especially the loss and fragmentation of forest patches. In this work, we develop a Remote Sensing (RS)-based modelling approach to identify areas for the implementation of nature-based solutions (NBS) (i.e., natural forest conservation and restoration) that allow reducing the vulnerability of aquatic ecosystems to siltation in mountainous regions. We used time series Landsat 5TM, 7ETM+, 8OLI and Sentinel 2A/2B MSI (S2) imagery to map forest dynamics and wetland distribution in Picos de Europa National Park (Cantabrian Mountains, northern Spain). We fed RS-based models with detailed in situ information based on photo-interpretation and fieldwork completed from 2017 to 2021. We estimated a forest cover increase rate of 2 ha/year comparing current and past LULC maps against external validation data. We applied this forest gain to a scenario generator model to derive a 30-year future LULC map that defines the potential forest extent for the study area in 2049. We then modelled the distribution of wetlands to identify the areas with the greatest potential for moisture accumulation. We used an S2 mosaic and topography-derived data such as the slope and topographic wetness index (TWI), which indicate terrain water accumulation. Overall accuracy scores reached values of 86% for LULC classification and 61% for wetland mapping. At the same time, we obtained the potential erosion using the NetMap software to identify potential sediment production, transport and deposition areas. Finally, forest dynamics, wetland distribution and potential erosion were combined in a multi-criteria analysis aiming to reduce the amount of sediment reaching selected wetlands. We achieved this by identifying the most suitable locations for the conservation and restoration of natural forests on slopes and in riparian areas, which may reduce the risk of soil erosion and maximise sediment filtering, respectively. The results show a network pattern for forest management that would allow for controlling erosion effects across space and time at three levels: one, by reducing the load that originates upslope in the absence of forest cover; two, by intersecting runoff at watercourses related to sediment transport; and three, by a lack of former barriers, by trapping erosion near to the receiving wetland systems, main river axes and contributing streams. In conclusion, the proposed methodology, which could be transferred to other mountain regions, allows to optimise investment for erosion prevention and wetland conservation by using only very specific areas of the landscape for habitat management (e.g., for NBS implementation). Full article

Migration is an important step in seismic data processing for oil and gas exploration. The accuracy of migration directly affects the accuracy of subsequent oil and gas reservoir characterization. Reverse-time migration is one of the most accurate migration methods at present. Multi-wave and multicomponent seismic data contain more P- and S-wave information. Making full use of multi-wave and multicomponent seismic data can offer more information about underground structure and lithology, as well as improve the accuracy of seismic exploration. Elastic reverse-time migration (ERTM) has no dip restriction and can be applied to image multi-wave and multicomponent seismic data in complex structural areas and some special lithology structures. However, the surface topography of complex regions has an influence on wavefield and seriously degrades the quality of ERTM’s migration results. We developed a new ERTM method to migrate multi-wave and multicomponent seismic data in the region with complex surface topography. We first fill the layers between the highest and lowest undulating surface with near-surface elastic parameters in a complex topography model to obtain a new model with a horizontal surface. This allows the finite difference (FD) method based on the regular rectangular grid to be used to numerically solve elastic wave equations in the model with complex topography. The decoupled wave equations are used to generate source P- and S-waves and receiver P- and S-waves to reduce crosstalk artefacts in ERTM. A topography-related filter is further used to remove the influence of surface topography on migration results. The scalar imaging condition is also applied to generate PP and PS migration images. Some numerical examples with different complex topographies demonstrate that our proposed ERTM method can remove the influence of complex topography on ERTM’s images and effectively generate high-quality ERTM images. Full article

Generating spatiotemporally continuous land surface temperature (LST) data is in great demand for hydrology, meteorology, ecology, environmental studies, etc. However, the thermal infrared (TIR)-based LST measurements are prone to cloud contamination with missing pixels. To repair the missing pixels, a new XGBoost-based linking approach for reconstructing daytime and nighttime Moderate Resolution Imaging Spectroradiometer (MODIS) LST measurements was introduced. The instantaneous solar radiation and two soil-related predictors from China Data Assimilation System (CLDAS) 0.0625°/1-h data were selected as the linking variables to depict the relationship with instantaneous MODIS LST data. Other land surface properties, including two vegetation indices, the water index, the surface albedo, and topographic parameters, were also used as the predictor variables. The XGBoost method was used to fit an LST linking model by the training datasets from clear-sky pixels and was then applied to the MODIS Aqua-Terra LSTs during summer time (June to August) in 2017 and 2018 across China. The recovered LST data was further rectified with the Savitzky–Golay (SG) filtering method. The results showed the distribution of the reconstructed LSTs present a reasonable pattern for different land-cover types and topography. The evaluation results using in situ longwave radiation measurements showed the RMSE varies from 3.91 K to 5.53 K for the cloud-free pixels and from 4.42 K to 4.97 K for the cloud-covered pixels. In addition, the reconstructed LST products correlated well with CLDAS LST data with similar LST spatial patterns. The variable importance analysis revealed that the two soil-related predictors and the elevation variable are key parameters due to their great contribution to the XGBoost model performance. Full article