Search Results (13)

Unmanned aerial vehicles (UAVs) significantly shape the evolution of 5G and 6G technologies in India, particularly in reconfiguring communication networks. Through their deployment as base stations or relays, these aerial vehicles substantially enhance communication performance and extend network coverage in areas characterized by high demand and challenging topographies. Accurate modelling of the UAV-to-ground channel is imperative for gaining valuable insights into UAV-assisted communication systems, particularly within India’s rapidly expanding metropolitan cities and their diverse topographical complexities. This study proposes an approach to model low-altitude channels in urban areas, offering specific scenarios and tailored solutions to facilitate radio frequency (RF) planning for Indian metropolitan cities. The proposed model leverages the International Telecommunication Union recommendation (ITU-R) for city mapping and utilizes frequency ranges from 1.8 to 6 GHz and altitudes up to 500 m to comprehensively model both line-of-sight (LoS) and non-line-of-sight (NLoS) communications. It employs the uniform theory of diffraction to calculate the additional path loss for non-line-of-sight (NLoS) communication for both vertical and horizontal polarizations. The normal distribution for additional shadowing loss is discerned from simulation results. This study outlined the approach to derive a comprehensive statistical channel model based on the elevation angle and evaluate model parameters at various frequencies and altitudes for both vertical and horizontal polarization. The model was subsequently compared with existing models for validation, showing close alignment. The ease of implementation and practical application of this proposed model render it an invaluable tool for planning and simulating mobile networks in urban areas, thus facilitating the seamless integration of advanced communication technologies in India. Full article

Soil Organic Carbon (SOC) is a crucial indicator of ecosystem health and soil quality. Machine learning (ML) models that predict soil quality based on environmental parameters are becoming more prevalent. However, studies have yet to examine how well each ML technique performs when predicting and mapping SOC, particularly at high spatial resolutions. Model predictors include topographic variables generated from SRTM DEM; vegetation and soil indices derived from Landsat satellite images predict SOC for the Lakhimpur district of the upper Brahmaputra Valley of Assam, India. Four ML models, Random Forest (RF), Cubist, Extreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM), were utilized to predict SOC for the top layer of soil (0–15 cm) at a 30 m resolution. The results showed that the descriptive statistics of the calibration and validation sets were close enough to the total set data and calibration dataset, representing the complete samples. The measured SOC content varied from 0.10 to 1.85%. The RF model’s performance was optimal in the calibration and validation sets (R²c = 0.966, RMSE_c = 0.159%, R²v = 0.418, RMSE_v = 0.377%). The SVM model, on the other hand, had the next-lowest accuracy, explaining 47% of the variation (R²c = 0.471, RMSEc = 0.293, R²v = 0.081, RMSEv = 0.452), while the Cubist model fared the poorest in both the calibration and validation sets. The most-critical variable in the RF model for predicting SOC was elevation, followed by MAT and MRVBF. The essential variables for the Cubist model were slope, TRI, MAT, and Band4. AP and LS were the most-essential factors in the XGBoost and SVM models. The predicted OC ranged from 0.44 to 1.35%, 0.031 to 1.61%, 0.035 to 1.71%, and 0.47 to 1.36% in the RF, Cubist, XGBoost, and SVM models, respectively. Compared with different ML models, RF was optimal (high accuracy and low uncertainty) for predicting SOC in the investigated region. According to the present modeling results, SOC may be determined simply and accurately. In general, the high-resolution maps might be helpful for decision-makers, stakeholders, and applicants in sericultural management practices towards precision sericulture. Full article

Atomic force microscopy (AFM) provides a platform for high-resolution topographical imaging and the mechanical characterization of a wide range of samples, including live cells, proteins, and other biomolecules. AFM is also instrumental for measuring interaction forces and binding kinetics for protein–protein or receptor–ligand interactions on live cells at a single-molecule level. However, performing force measurements and high-resolution imaging with AFM and data analytics are time-consuming and require special skill sets and continuous human supervision. Recently, researchers have explored the applications of artificial intelligence (AI) and deep learning (DL) in the bioimaging field. However, the applications of AI to AFM operations for live-cell characterization are little-known. In this work, we implemented a DL framework to perform automatic sample selection based on the cell shape for AFM probe navigation during AFM biomechanical mapping. We also established a closed-loop scanner trajectory control for measuring multiple cell samples at high speed for automated navigation. With this, we achieved a $60\times$ speed-up in AFM navigation and reduced the time involved in searching for the particular cell shape in a large sample. Our innovation directly applies to many bio-AFM applications with AI-guided intelligent automation through image data analysis together with smart navigation. Full article

An accurate estimation of soil electrical conductivity (EC) using hyperspectral techniques is of great significance for understanding the spatial distribution of solutes and soil salinization. Although spectral transformation has been widely used in data pre-processing, the performance of different pre-processing techniques (or combination methods) on different models of the same data set is still ambiguous. Moreover, extremely randomized trees (ERT) and light gradient boosting machine (LightGBM) models are new learning algorithms with good generalization performance (soil moisture and above-ground biomass), but are less studied in estimating soil salinity in the visible and near-infrared spectra. In this study, 130 soil EC data, soil measured hyperspectral data, topographic factors, conventional salinity indices such as Salinity Index 1, and two-band (2D) salinity indices such as ratio indices, were introduced. The five spectral pre-processing methods of standard normal variate (SNV), standard normal variate and detrend (SNV-DT), inverse (1/OR) (OR is original spectrum), inverse-log (Log(1/OR) and fractional order derivative (FOD) (range 0–2, with intervals of 0.25) were performed. A gradient boosting machine (GBM) was used to select sensitive spectral parameters. Models (extreme gradient boosting (XGBoost), LightGBM, random forest (RF), ERT, classification and regression tree (CART), and ridge regression (RR)) were used for inversion soil EC and model validation. The results reveal that the two-dimensional correlation coefficient highlighted EC more effectively than the one-dimensional. Under SNV and the second order derivative, the two-dimensional correlation coefficient increased by 0.286 and 0.258 compared to the one-dimension, respectively. The 13 characteristic factors of slope, NDI, SI-T, RI, profile curvature, DOA, plane curvature, SI (conventional), elevation, Int2, aspect, S1 and TWI provided 90% of the cumulative importance for EC using GBM. Among the six machine models, the ERT model performed the best for simulation (R² = 0.98) and validation (R² = 0.96). The ERT model showed the best performance among the EC estimation models from the reference data. The kriging map based on the ERT simulation showed a close relationship with the measured data. Our study selected the effective pre-processing methods (SNV and the 2 order derivative) using one- and two-dimensional correlation, 13 important factors and the ERT model for EC hyperspectral inversion. This provides a theoretical support for the quantitative monitoring of soil salinization on a larger scale using remote sensing techniques. Full article

The decline in biodiversity in Mediterranean-type ecosystems (MTEs) and other shrublands underscores the importance of understanding the trends in species loss through consistent vegetation mapping over broad spatial and temporal ranges, which is increasingly accomplished with optical remote sensing (imaging spectroscopy). Airborne missions planned by the National Aeronautics and Space Administration (NASA) and other groups (e.g., US National Ecological Observatory Network, NEON) are essential for improving high-quality maps of vegetation and plant species. These surveys require robust and efficient ground calibration/validation data; however, barriers to ground-data collection exist, such as steep terrain, which is a common feature of Mediterranean-type ecosystems. We developed and tested a method for rapidly collecting ground-truth data for shrubland plant communities across steep topographic gradients in southern California. Our method utilizes semi-aerial photos taken with a high-resolution digital camera mounted on a telescoping pole to capture groundcover, and a point-intercept image-classification program (Photogrid) that allows efficient sub-sampling of field images to derive vegetation percent-cover estimates while reducing human bias. Here, we assessed the quality of data collection using the image-based method compared to a traditional point-intercept ground survey and performed time trials to compare the efficiency of various survey efforts. The results showed no significant difference in estimates of percent cover and Simpson’s diversity derived from the point-intercept and those derived using the image-based method; however, there was lower correspondence in estimates of species richness and evenness. The image-based method was overall more efficient than the point-intercept surveys, reducing the total survey time by 13 to 46 min per plot depending on sampling effort. The difference in survey time between the two methods became increasingly greater when the vegetation height was above 1 m. Due to the high correspondence between estimates of species percent cover derived from the image-based compared to the point-intercept method, we recommend this type of survey for the verification of remote-sensing datasets featuring percent cover of individual species or closely related plant groups, for use in classifying UAS imagery, and especially for use in MTEs that have steep, rugged terrain and other situations such as tall, dense-growing shrubs where traditional field methods are dangerous or burdensome. Full article

Marine terraces are geomorphic markers largely used to estimate past sea-level positions and surface deformation rates in studies focused on climate and tectonic processes worldwide. This paper aims to investigate the role of tectonic processes in the late Quaternary evolution of the coastal landscape of the broader Neapolis area by assessing long-term vertical deformation rates. To document and estimate coastal uplift, marine terraces are used in conjunction with Optically Stimulated Luminescence (OSL) dating and correlation to late Quaternary eustatic sea-level variations. The study area is located in SE Peloponnese in a tectonically active region. Geodynamic processes in the area are related to the active subduction of the African lithosphere beneath the Eurasian plate. A series of 10 well preserved uplifted marine terraces with inner edges ranging in elevation from 8 ± 2 m to 192 ± 2 m above m.s.l. have been documented, indicating a significant coastal uplift of the study area. Marine terraces have been identified and mapped using topographic maps (at a scale of 1:5000), aerial photographs, and a 2 m resolution Digital Elevation Model (DEM), supported by extensive field observations. OSL dating of selected samples from two of the terraces allowed us to correlate them with late Pleistocene Marine Isotope Stage (MIS) sea-level highstands and to estimate the long-term uplift rate. Based on the findings of the above approach, a long-term uplift rate of 0.36 ± 0.11 mm a⁻¹ over the last 401 ± 10 ka has been suggested for the study area. The spatially uniform uplift of the broader Neapolis area is driven by the active subduction of the African lithosphere beneath the Eurasian plate since the study area is situated very close (~90 km) to the active margin of the Hellenic subduction zone. Full article

In the coming years, Italy will need to take on a great challenge concerning the digitization of its archaeological and architectural heritage, one of the richest and most problematic in the world. The aim is to improve the knowledge, conservation, enhancement and accessibility of cultural assets and to make them a resource for national and local development. In this process, the next generation of 3D survey methods (laser scanning and photogrammetry), in combination with diagnostic techniques (spectroscopy analyses) and GIS/BIM (Geographic Information System/Building Information Modeling) solutions, represent a valid support. This work, part of a broader intervention launched by the Municipality of Reggio Calabria for the requalification of some archaeological sites located within its urban and metropolitan area, is focused on the study case of Motta S. Agata. The ancient settlement is located 8 km from Reggio C. in a hilly area difficult to reach and preserves numerous structures in a state of ruin. Among these, two interesting medieval churches are proposed for examination: the church of San Nicola, characterized by five hypogeal funeral crypts, and the chapel of San Basilio, which preserves the traces of a wall painting. A multi-methodological approach including close-range photogrammetry, laser scanning and chemical and thermal analyses was adopted in order to fulfill different tasks: creating a topographic model of the hillfort, mapping the archaeological evidence, digitizing and returning 3D models of the churches, characterizing materials through chemical analyses and monitoring the surfaces with thermal imaging. These combined applications have contributed to reaching the planned goals, i.e., study, conservation, diagnostics, preparation for restoration interventions, development of digital media and dissemination. In this way, a type of interactive museum (made up of virtual tours and informative digital models) has been made available in order to improve the site’s accessibility and inclusivity as well as to test the effect of digitization in attracting tourists and local people toward a place located outside of the usual tourist circuits. Full article

Topographic products are important for mission operations and scientific research in lunar exploration. In a lunar rover mission, high-resolution digital elevation models are typically generated at waypoints by photogrammetry methods based on rover stereo images acquired by stereo cameras. In case stereo images are not available, the stereo-photogrammetric method will not be applicable. Alternatively, photometric stereo method can recover topographic information with pixel-level resolution from three or more images, which are acquired by one camera under the same viewing geometry with different illumination conditions. In this research, we extend the concept of photometric stereo to photogrammetric-photometric stereo by incorporating collinearity equations into imaging irradiance model. The proposed photogrammetric-photometric stereo algorithm for surface construction involves three steps. First, the terrain normal vector in object space is derived from collinearity equations, and image irradiance equation for close-range topographic mapping is determined. Second, based on image irradiance equations of multiple images, the height gradients in image space can be solved. Finally, the height map is reconstructed through global least-squares surface reconstruction with spectral regularization. Experiments were carried out using simulated lunar rover images and actual lunar rover images acquired by Yutu-2 rover of Chang’e-4 mission. The results indicate that the proposed method achieves high-resolution and high-precision surface reconstruction, and outperforms the traditional photometric stereo methods. The proposed method is valuable for ground-based lunar surface reconstruction and can be applicable to surface reconstruction of Earth and other planets. Full article

Gravity survey is one of the passive geophysical techniques commonly used to delineate geological formations, especially in determining basement rock and the overlying deposit. Geologically, the study area is made up of thick quaternary alluvium deposited on top of the older basement rock. The Muda River basin constitutes, approximately, of more than 300 m of thick quaternary alluvium overlying the unknown basement rock type. Previous studies, including drilling and geo-electrical resistivity surveys, were conducted in the area but none of them managed to conclusively determine the basement rock type and depth precisely. Hence, a regional gravity survey was conducted to determine the thickness of the quaternary sediments prior to assessing the sustainability of the Muda River basin. Gravity readings were made at 347 gravity stations spaced at 3–5 km intervals using Scintrex CG-3 covering an area and a perimeter of 9000 km² and 730 km, respectively. The gravity data were then conventionally reduced for drift, free air, latitude, Bouguer, and terrain corrections. These data were then consequently analyzed to generate Bouguer, regional and total horizontal derivative (THD) anomaly maps for qualitative and quantitative interpretations. The Bouguer gravity anomaly map shows low gravity values in the north-eastern part of the study area interpreted as representing the Main Range granitic body, while relatively higher gravity values observed in the south-western part are interpreted as representing sedimentary rocks of Semanggol and Mahang formations. Patterns observed in the THD anomaly and Euler deconvolution maps closely resembled the presence of structural features such as fault lineaments dominantly trending along NW-SE and NE-SW like the trends of topographic lineaments in the study area. Based on power spectral analysis of the gravity data, the average depth of shallow body, representing alluvium, and deep body, representing underlying rock formations, are 0.5 km and 1.2 km, respectively. The thickness of Quaternary sediment and the depth of sedimentary formation can be more precisely estimated by other geophysical techniques such as the seismic reflection survey. Full article

Recent results within the framework of the collaborative project The Complete Geophysical Survey of the Valley of the Kings (VOK) (Luxor, Egypt) are reported in this article. In October 2018, a team of geomatics and geophysics researchers coordinated by the Polytechnic University of Turin worked side by side in the VOK. Topographic measurements in support of geophysical surveys and the achievement of a very large-scale 3D map of the Eastern VOK were the two main objectives of the geomatics campaign. Innovative 3D metric technologies and methods, based on terrestrial laser scanning (both static and mobile) and close-range photogrammetry were employed by the Geomatics team. The geophysical campaign focused on the acquisition of Electrical Resistivity Tomography (ERT), Ground Penetrating Radar (GPR) and high spatial density Geomagnetic (GM) data. ERT new data around KV62, both inverted in 2D sections and added to the previous ones to perform a new global 3D inversion, confirm the previous results showing both conductive and resistive anomalies that have to be explained. GPR timeslices showed some interesting features in the area in front of the KV2 entrance where GM gradient map also presents localized anomalies. In the area SSW of the KV2 the GM gradient maps evidenced also a large semicircular anomaly which, up to now, has no explanation. The potentialities of using magnetic techniques as a complement to other non-invasive techniques in the search for structures of archeological significance have been explored. The application of modern and innovative methods of 3D metric survey enabled to achieve a complete 3D mapping of what is currently visible in the valley. The integration of 2D/3D mapping data concerning visible elements and hypothetical anomalies, together with the recovering in the same global reference system of underground documentation pertaining to the Theban Mapping Project, prefigure the enhancement of multi-temporal site representation. This strategy enables the fruition development of the already discovered archaeological heritage, using modern criteria of valorization and conservation. Full article

Evaluating the installation potential of ground source heat pump (GSHP) systems based on the hydrogeological condition of an area is important for the installation and sustainable use of the system. This work is the first to have compared the distributions of heat exchange rate in the Sendai Plain and Aizu Basin (Japan) in terms of topographical and hydrogeological conditions. A regional groundwater flow and heat transport model was constructed for the Sendai Plain. Suitability assessment was conducted for an identical closed-loop system by preparing the distribution maps of heat exchange rate for space heating for the plain and basin. For both locations, the upstream area showed a higher heat exchange rate than the downstream area. Multiple regression analysis was conducted using heat exchange rate as a response variable. Average groundwater flow velocity and average subsurface temperature were considered as explanatory variables. The heat exchange rate for the plain, whose Péclet number ranged from 3.5 × 10⁻³–7.3 × 10⁻², was affected by groundwater flow velocity and subsurface temperature. The exchange rate for the basin, whose Péclet number ranged from 8.5 × 10⁻²–5.8 × 10⁻¹, was affected by groundwater flow velocity. Inland basins are likely to be more suitable for GSHP system installation utilizing groundwater flow than coastal plains in terms of inclination of slope. This study showed that multiple regression analysis can reveal factors affecting the heat exchange rate as well as the degree to which they affect it. Full article

The Sentinel-1 mission provides frequent coverage of global land areas and is hence able to monitor surface water dynamics at a fine spatial resolution better than any other Synthetic Aperture Radar (SAR) mission before. However, SAR data acquired by Sentinel-1 also suffer from terrain effects when being used for mapping surface water, just as other SAR data do. Terrain indices derived from Digital Elevation Models (DEMs) are easy but effective approaches to reduce this kind of interference, considering the close relationship between surface water movement and topography. This study compares two popular terrain indices, namely the Multi-resolution Valley Bottom Flatness (MrVBF) and the Height Above Nearest Drainage (HAND), toward their performance on assisting surface water mapping using Sentinel-1 SAR data. Four study sites with different terrain characteristics were selected to cover a very wide range of topographic conditions. For two of these sites that are floodplain dominated, both normal and flooded scenarios were examined. MrVBF and HAND values for the whole study areas, as well as statistics of these values within water areas were compared. The sensitivity of applying different thresholds for MrVBF and HAND to mask out terrain effect was investigated by adopting quantity disagreement and allocation disagreement as the accuracy indicators. It was found that both indices help improve water mapping, reducing the total disagreement by as much as 1.6%. The HAND index performs slightly better in most of the study cases, with less sensitivity to thresholding. MrVBF classifies low-lying areas with more details, which sometimes makes it more effective in eliminating false water bodies in rugged terrain. It is therefore recommended to use HAND for large scale or global scale water mapping. However, for water detection in complex terrain areas, MrVBF also performs very well. Full article

We demonstrate the efficacy of a commercial portable 2D laser scanner (operating at a wavelength close to 1,000 nm) deployed from a fixed-wing aircraft for measuring the sea surface topography and wave profiles over coastal waters. The LiDAR instrumentation enabled simultaneous measurements of the 2D laser scanner with two independent inertial navigation units, and also simultaneous measurements with a more advanced 2D laser scanner (operating at a wavelength near 1,500 nm). The latter scanner is used routinely for accurately measuring terrestrial topography and was used as a benchmark in this study. We present examples of sea surface topography and wave profiles based on low altitude surveys (< ~300 m) over coastal waters in the vicinity of Cape de Couedic, Kangaroo Island, South Australia and over the surf zone adjacent to the mouth of the Murray River, South Australia. Relative wave heights in the former survey are shown to be consistent with relative wave heights observed from a waverider buoy located near Cape de Couedic during the LiDAR survey. The sea surface topography of waves in the surf zone was successfully mapped with both laser scanners resolving relative wave height variations and fine structure of the sea surface to within approximately 10 cm. A topographic map of the sea surface referenced to the airborne sensor frame transforms to an accurate altimetry map which may be used with airborne electromagnetic instrumentation to provide an averaged altimetry covering a portion of the larger electromagnetic footprint. This averaged altimetry is deemed to be significantly more reliable as a measurement of altimetry than spot measurements using a nadir-looking laser altimeter and would therefore improve upon the use of airborne electromagnetic methods for bathymetric mapping in surf-zone waters. The aperture range of the scanner does not necessarily determine the swath. We observed that instead, the maximum swath at a given altitude was limited by the angle of incidence of the laser at the water surface. Full article