Surface Reflectance Research Articles

Thrust Model and Trajectory Design of an Interplanetary CubeSat with a Hybrid Propulsion System

This paper analyzes the performance of an interplanetary CubeSat equipped with a hybrid propulsion system (HPS), which combines two different types of thrusters in the same deep space vehicle, in a heliocentric transfer between two assigned (Keplerian) orbits. More precisely, the propulsion system of the CubeSat considered in this work consists of a combination of a (low-performance) photonic solar sail and a more conventional solar electric thruster. In particular, the characteristics of the solar electric thruster are modeled using a recent mathematical approach that describes the performance of the miniaturized engine that will be installed on board the proposed ESA’s M-ARGO CubeSat. The latter will hopefully be the first interplanetary CubeSat to complete a heliocentric transfer towards a near-Earth asteroid using its own propulsion system. In order to simplify the design of the CubeSat attitude control subsystem, we assume that the orientation of the photonic solar sail is kept Sun-facing, i.e., the sail reference plane is perpendicular to the Sun-CubeSat line. That specific condition can be obtained, passively, by using an appropriate design of the shape of the sail reflective surface. The performance of an HPS-based CubeSat is analyzed by optimizing the transfer trajectory in a three-dimensional heliocentric transfer between two closed orbits of given characteristics. In particular, the CubeSat transfer towards the near-Earth asteroid 99942 Apophis is studied in detail.

Enhancing 3D Models with Spectral Imaging for Surface Reflectivity.

The increasing demand for accurate and detailed 3D modeling in fields such as cultural heritage preservation, industrial inspection, and scientific research necessitates advanced techniques to enhance model quality. This paper addresses this necessity by incorporating spectral imaging data to improve the surface detail and reflectivity of 3D models. The methodology integrates spectral imaging with traditional 3D modeling processes, offering a novel approach to capturing fine textures and subtle surface variations. The experimental results of this paper underscore the advantages of incorporating spectral imaging data in the creation of 3D models, particularly in terms of enhancing surface detail and reflectivity. The achieved experimental results demonstrate that 3D models generated with spectral imaging data exhibit significant improvements in surface detail and accuracy, particularly for objects with intricate surface patterns. These findings highlight the potential of spectral imaging in enhancing 3D model quality. This approach offers significant advancements in 3D modeling, contributing to more precise and reliable representations of complex surfaces.

NIR-ViS-UV broadband absorption in ultrathin electrochemically-grown, graded index nanoporous platinum films.

Nanoporous platinum broadband absorber has attracted interest in thermosensorics and IR photodetection due to its unique properties. In this work we report the physical mechanism underlying broadband absorption in electrochemically-grown, nanoporous Pt films by analyzing NIR-ViS-UV spectral ellipsometry data of nanoporous Pt films in dependence on the Pt film thickness (27, 35, 38, 48nm). For the two thinner films a single layer model with a graded optical index Pt surface layer was used. For the two thicker films a two-layer optical model with a constant optical index Pt substrate layer and a graded optical index Pt surface layer was used. The graded optical index of the Pt surface layer reduces surface reflectivity and the constant optical index Pt substrate layer supports multiple reflections in the Pt film. Finally, we relate the thickness dependent optical index with the nanostructure of the nanoporous Pt film, which can be controlled in the electrochemical growth process. We observed that while in the transverse plane the multilayer exhibits graded refractive index, in the top horizontal planes the multilayer assembly exhibits discontinuous refractive index values due to the distribution of platinum crystal islands in air, which allows a metamaterial behavior of the whole system.

HIGH-RESOLUTION SATELLITE ESTIMATION OF SNOW COVER FOR FLOOD ANALYSIS IN EAST KAZAKHSTAN REGION

The increasing frequency of extreme weather events linked to climate change has made flood forecasting an important issue, particularly in mountainous regions where snowmelt is a major driver of seasonal flooding. This study explores the application of snow cover estimation techniques to assess snowmelt dynamics and their potential impact on flood risks in the Ulba and Uba basins in East Kazakhstan. To achieve this, high-resolution multispectral satellite imagery from the Sentinel-2 Surface Reflectance dataset is used, focusing on images collected between March and October for the years 2021 to 2024. The images are processed in Google Earth engine platform with strict filtering based on spatial intersection with the basins and cloud cover pixels percentage, ensuring high-quality data for snow cover analysis. The study utilizes multiple remote sensing indices for snow cover estimation. The normalized difference snow index is calculated using the green and shortwave infrared bands to detect snow-covered pixels. Fractional snow-covered area is derived from the NDSI using the 'FRA6T' relationship, offering a more nuanced estimate of snow distribution across the basins. Additionally, a near-infrared to shortwave infrared ratio threshold is employed to minimize confusion between snow and water, improving the detection of snow cover, particularly in regions near water bodies or during melt periods. The resulting snow cover maps and fSCA estimates provide a detailed picture of snow distribution and melt dynamics, contributing to the assessment of snowmelt’s role in flood risk development. The obtained insights can assist in refining flood forecasting models, improving early warning systems, and supporting informed water resource management in vulnerable regions.

FLOOD RISK MAPPING IN THE IRTYSH RIVER BASIN USING SATELLITE DATA

Floods are among the most frequent and devastating natural disasters, causing significant economic damage and loss of life worldwide. Effective flood risk management relies on accurate modeling techniques that can predict vulnerable areas and assess potential impacts. In this study, flood dynamics are simulated in the Irtysh River Basin near Ust-Kamenogorsk, a city in East Kazakhstan prone to seasonal flooding using high-resolution satellite imagery and digital elevation data. The primary objective is to visually model flood risks based on terrain characteristics. The study utilizes imagery sourced from the Mapbox platform, which combines data from MODIS, Landsat 7, Maxar, and the Google Earth Engine, providing access to Sentinel-2 surface reflectance imagery at 10-meter resolution. Elevation data from the Copernicus global digital elevation model, with a 30-meter resolution, is used to simulate flood progression. The flood simulation involves calculating flood depth relative to the terrain’s elevation, allowing for a pixel-by-pixel determination of submerged areas. Each simulation incrementally increases water levels to generate a sequence of images, showcasing the progression of flooding over time. The study describes hydraulic soil characteristics usage, and focuses on visualizing flood risk based on terrain data and water level changes. The simulation results indicate that flooding initially impacts riverbanks as water flow starts from the northwest of the city with critical infrastructure becoming vulnerable once water levels exceed 2 meters from the lowest elevation point. These findings highlight the potential of high-resolution satellite imagery and terrain data for flood risk assessment and improving urban flood preparedness. The results provide valuable insights into flood progression enabling more informed decision-making for disaster mitigation.

Cost-Effective High Gain Wideband Antenna with Dual Partially Reflective Surface for 5G-mmWave Application

This research presents the performance improvement of the of rectangular patch microstrip antenna. The purpose is to increase gain and bandwidth with design on the PRS (Partially Reflective Surface) dual layer technique. There is a developing the low-cost substrate-based antennas suitable for 5G millimeter-wave. The prototype antenna achieves a maximum gain of 11.8 dBi at a frequency of 25.5 GHz. The gain increases by 6 dB throughout its operational frequency range, with an OBW (Overlap bandwidth) of 20.9%, covering frequencies from 24.0 GHz to 29.9 GHz. The performance achieved results indicate that the prototype antenna can be effectively utilized for 5G millimeter-wave communication applications in Thailand.

Surface Coloring and Plasmonic Information Encryption at 50000 dpi Enabled by Direct Femtosecond Laser Printing.

Femtosecond (fs) laser pulses drive matter into a highly nonequilibrium state, allowing precise sculpturing of irradiated surface sites with sophisticated nanomorphologies. Here, we used fs-laser patterning to create diverse plasmonic morphologies on the top Au layer of the metal-insulator-metal sandwich. Mutual action of laser-driven thermomechanical effects and ultrafast solid-to-liquid transition allows control of the morphology resulting in pronounced surface reflectivity modulation, i.e., in a structural color effect. This enables template-free high-resolution color printing at a superior lateral resolution up to 50000 dots per inch and facile tunability of the color tone and saturation. Moreover, precise control over the orientation of the printed nanostructures within subwavelength lattices allows modulation of their local plasmonic response encrypting the optical information within the colorful images. The hidden information can be unveiled using a facile cross-polarized optical visualization scheme, rendering the proposed method with extra modalities combining high resolution information encryption, coloring, and security labeling.

Retrieval of pseudo-BRDF-adjusted surface reflectance at 440 nm from the Geostationary Environmental Monitoring Spectrometer (GEMS)

Abstract. In satellite remote sensing applications, enhancing the precision of level 2 (L2) algorithms relies heavily on the accurate estimation of the surface reflectance across the ultraviolet (UV) to visible (VIS) spectrum. However, the mutual dependence between the L2 algorithms and the surface reflectance retrieval poses challenges, necessitating an alternative approach. To address this issue, many satellite algorithms generate Lambertian-equivalent reflectivity (LER) products as a priori surface reflectance data; however, this often results in an underestimation of these data. This study is the first to assess the applicability of background surface reflectance (BSR), derived using a semi-empirical bidirectional reflectance distribution function (BRDF) model, in an operational environmental satellite algorithm. This study pioneered the application of the BRDF model to hyperspectral satellite data at 440 nm, aiming to provide more realistic preliminary surface reflectance data. In this study, the Geostationary Environment Monitoring Spectrometer (GEMS) data were used, and a comparative analysis of the GEMS BSR and GEMS LER retrieved in this study revealed an improvement in the relative root mean squared error (rRMSE) accuracy of 3 %. Additionally, a time series analysis across diverse land types indicated a greater stability exhibited by the BSR than by the LER. For further validation, the BSR was compared with other LER databases using ground-truth data, yielding superior simulation performance. These findings present a promising avenue for enhancing the accuracy of surface reflectance retrieval from hyperspectral satellite data, thereby advancing the practical applications of satellite remote sensing algorithms.

A far ultraviolet-C light technology is effective for decontamination of items in proximity to sinks and is enhanced by a far UV-C reflective surface.

Dispersal of gram-negative bacilli from sink drains has been implicated as a source of transmission in multiple outbreaks. In an acute care hospital, we assessed how often patient care supplies and other frequently touched items were within 1 meter of sink drains. We tested the efficacy of a ceiling-mounted far ultraviolet-C (UV-C) light technology for decontamination of sink bowls and surfaces near sinks with and without a wall-mounted film that reflects far UV-C light. Of 190 sinks assessed, 55 (29%) had patient care supplies or other frequently touched items within 1 meter of the drain. The far UV-C technology reduced Pseudomonas aeruginosa, Enterobacter cloacae and Candida auris on steel disk carriers by ≥1.5 log10 colony-forming units (CFU) in 45 minutes. On inoculated real-world items, ≥1.9 log10 CFU reductions in P. aeruginosa were achieved on sites in line with the light source versus 0.4-1.8 log10 CFU reductions on shaded surfaces. The addition of the reflective surface significantly enhanced efficacy in shaded sites (P < 0.01). In a hospital setting, patient care supplies and other frequently touched items were often in proximity to sinks. The far UV-C light technology could potentially be useful for sink decontamination in high-risk areas.

An Investigation of Globe Temperature in Street Canyons: A Scaled Model Study Implementing Cool Materials

The measurement of globe temperature (GT) is essential for investigating pedestrian thermal comfort in street canyons. The globe thermometer is the most common instrument used to measure GT; however, its application in scale models has not been thoroughly investigated to date. Therefore, this study explicitly investigates globe thermometer measurements in scale models and analyzes the need for customization of the globe thermometer for more reliable measurements. Scaling down with respect to the size of the globe thermometer and the effect of solar orientation/envelope materials are investigated in this study. The initial experiments were carried out in an outdoor setting using a typical street canyon model (scale 1:100) with an east-west street orientation. The results of the experiment are presented to compare a low solar reflectance street canyon (albedo of 0.4) and a high solar reflectance canyon (albedo of 0.6) in terms of surface temperatures, heat flux, and globe temperature. It is observed that although the wall and road surface temperatures are lower for the high solar reflectance canyon compared to those for the low solar reflectance canyon, the GT (measured at pedestrian height) is higher in a high reflectance canyon during the daytime, which could be due to the combined effect of direct radiation and short-wave reflection. However, for the hours after sunset, a reverse effect is observed, i.e., the GT becomes lower (up to 0.8 °C) in the case of a high reflectance canyon compared to that for the low reflectance canyon. Furthermore, the study emphasizes the impact of solar reflectance of canyon surfaces on GT values, due to the view factors that the globe thermometer on those surfaces.

CGH calculation algorithm for expressing reflection on a curved mirror surface

Rendering techniques are important in computer-generated holograms (CGHs) for expressing various types of holo-realistic 3D images. Rendering techniques such as hidden surface removal and reflection by a planar mirror have been proposed thus far, but reflection on a curved mirror surface has yet to be achieved. In this study, we propose a calculation algorithm that can express the reflection of the surrounding environment on a mirror surface defined as a Bézier surface. The results of optical experiments demonstrate that the proposed algorithm enables reflection on such a mirror surface and that the calculation can be accelerated by using a graphics processing unit (GPU).

Bridging the Gap to 6G: Leveraging the Synergy of Standardization and Adaptability

The field of wireless network and communication technology is evolving from generation to generation from 1G to 6G as of now till expected to be deployed and used by 2030. It is to succeed in 5G and bring significant improvements in terms of connectivity, speed, and size in next-generation communication technology. 6G aims to deal with the rising need for more rapid information speed, low latency, and wider network coverage. This intelligent communication is proposed to meet these demands and enable new services and applications. This review paper highlights the key enablers and challenges involved in implementing intelligent communication beyond 5G. The paper identifies the research gaps for incorporating beyond 5G communication networks and outlines the possible 6G key objectives from a flexibility standpoint. It reviews infrastructure deployment, network densification, spectrum capacity and network energy efficiency in predecessors to 6G. This paper emphasizes the need for standardization and adaptation of research areas to revolutionize 6G wireless communication, focusing on areas like, ultra massive MIMO, Terahertz Communications, Cell-Free Communications, Intelligent Reflecting Surface, Visible Light Communication, Internet of Things, Big Data management, Artificial Intelligence, and network connectivity techniques.

3D printed degradable hydrogel evaporator for high-efficiency, environmental-friendly solar alkaline-water evaporation

Solar evaporation is a simple, cost-effective method for producing clean water that does not require complex infrastructure and fossil energy. Although there have been significant advances in hydrogel solar evaporators, their widespread applications are still hampered by challenges related to customizing the structures to optimize solar evaporation rates and managing the pollution associated with waste hydrogel evaporators. To address these issues, we construct a customizable in structure, highly efficient and degradable interfacial solar evaporator using three-dimensional (3D) printing technique. The complex 3D microstructures can significantly enhance sunlight absorption through multiple surface reflections and anti-reflection effects, which can achieve customized evaporation performance. The optimized tree-shaped hydrogel evaporators can achieve a high evaporation rate of 2.41 kg m–2 h−1 under 1 sun. Importantly, the hydrogel evaporators exhibit degradation properties in alkaline liquids. These components can be integrated into the environment, reducing their impact on the environment and achieving sustainable utilization, offering a promising solution for alkaline wastewater purification and demonstrating the potential of environmental-friendly solar evaporator technology.

Silicon surface texturing via TBAB-SDS composite additives enhanced copper-assisted chemical etching

Uneven etching and low fabrication efficiency impede the large-scale applications of copper-assisted chemical etching (Cu-ACE) for texturing light-trapping structures on the surface of silicon wafers. To address this, a composite additive composed of tetrabutylammonium bromide (TBAB) and sodium dodecyl sulfate (SDS) was introduced into the Cu-ACE system. The results indicated that TBAB accelerated the etching rate and improved the texturing uniformity, while SDS enlarged the size of the formed structures and enhanced their ultraviolet light absorption efficiency. The prepared inverted pyramid structure reduced the reflectivity of the silicon wafer surface to 3.8 %, thus exhibiting efficient light-trapping capabilities. The etching evolution under various TBAB concentrations and different HF/H2O2 ratios was studied by characterizing the surface contact angle and copper deposition morphology. The results indicated that electrostatic attraction between TBAB and dangling bonds on the silicon wafer surface enhanced material transfer at the reaction interface and changed the electron distribution around dangling bonds, thus facilitating the catalytic metal attack on these bonds. The copper ion reactivity was decreased due to complexation between the dissociated alkyl sulfate ions of SDS and copper ions, which favored the deposition of larger copper nanoparticles during etching, thereby increasing the size of structures. This research offers valuable insights to enable the large-scale applications of Cu-ACE.

Steering the Site Distance of Atomic Cu−Cu Pairs by First‐Shell Halogen Coordination Boosts CO2‐to‐C2 Selectivity

AbstractElectrocatalytic reduction of CO2 into C2 products of high economic value provides a promising strategy to realize resourceful CO2 utilization. Rational design and construct dual sites to realize the CO protonation and C−C coupling to unravel their structure‐performance correlation is of great significance in catalysing electrochemical CO2 reduction reactions. Herein, Cu−Cu dual sites with different site distance coordinated by halogen at the first‐shell are constructed and shows a higher intramolecular electron redispersion and coordination symmetry configurations. The long‐range Cu−Cu (Cu−I−Cu) dual sites show an enhanced Faraday efficiency of C2 products, up to 74.1 %, and excellent stability. In addition, the linear relationships that the long‐range Cu−Cu dual sites are accelerated to C2H4 generation and short‐range Cu−Cu (Cu−Cl−Cu) dual sites are beneficial for C2H5OH formation are disclosed. In situ electrochemical attenuated total reflection surface enhanced infrared absorption spectroscopy, in situ Raman and theoretical calculations manifest that long‐range Cu−Cu dual sites can weaken reaction energy barriers of CO hydrogenation and C−C coupling, as well as accelerating deoxygenation of *CH2CHO. This study uncovers the exploitation of site‐distance‐dependent electrochemical properties to steer the CO2 reduction pathway, as well as a potential generic tactic to target C2 synthesis by constructing the desired Cu−Cu dual sites.

Monitoring and assessment of spatiotemporal soil salinization in the Lake Urmia region

Soil salinization stands as a prominent global environmental challenge, necessitating enhanced assessment methodologies. This study is dedicated to refining soil salinity assessment in the Lake Urmia region of Iran, utilizing multi-year data spanning from 2015 to 2018. To achieve this objective, soil salinity was measured at 915 sampling points during the 2015–2018 timeframe. Simultaneously, remote sensing data were derived from surface reflectance data over the same study period. Four distinct scenarios were considered such as a newly developed spectral index (Scenario I), the newly developed index combined with other salt-based spectral indices from the literature (Scenario II), indirect spectral indices based on vegetation and soil characteristics (Scenario III), and the amalgamation of both direct and indirect spectral indices (Scenario IV). Linear Regression (LR), Support Vector Machine (SVM), and Random Forest (RF) were employed to assess soil salinity. The measured data divided to 75% of the data as the calibration dataset, while the remaining 25% constituted the validation dataset. The findings revealed a correlation between soil salinity and spectral indices from the literature, with a range of -0.53 to 0.51, while the newly developed spectral index exhibited a stronger correlation (r = 0.59). Furthermore, RF yielded superior results when using the newly developed spectral index (Scenario I). Overall, SVM emerged as the most effective model (ME = -9.678, R2 = 0.751, and RPIQ = 1.78) when integrating direct and indirect spectral indices (Scenario IV). This study demonstrates the efficacy of combining machine learning techniques with a blend of newly developed and existing spectral indices from the literature for the monitoring of soil salinity, particularly in arid and semi-arid regions.

Pixel-wise Phase Map Fusion Technique for High Dynamic Range 3-D Shape Measurement

Abstract Digital fringe projection technologies have been extensively applied in 3-D shape measurements. However, it is still limited to achieve accurate 3-D reconstruction of high reflective surfaces. To circumvent this problem, we propose a complete framework to realize pixel-by-pixel phase post-compensation of overexposed points, including the construction of hardware system and the guidelines of algorithm design. First, a virtual binocular vision system is established. Second, based on the fundamentals of projective and spatial transformation, three robust algorithms with low computational complexity are devised to generate a fused phase map that overcomes the information loss due to overexposure. Furthermore, experiments are conducted to evaluate the performance of the proposed method. Qualitative experiment results show that the presented technique achieve a similar surface coverage compared with the other two mainstream methods, but is superior to them in terms of measurement efficiency (13 images vs. 144 images, 13 images vs. 32 images). Quantitative experimentation further verifies the feasibility of our method in precise 3-D measurement, with sphere diameter errors of 0.0367mm and 0.0361mm, spherical centroid distance error of 0.0269mm, and plane distance error of 0.0186mm.

A lightweight parallel attention residual network for tile defect recognition

In modern industrial production, permanent magnet motors are an indispensable part of industrial manufacturing. The quality of the magnetic tiles directly affects the working performance of the permanent magnet motors, making the detection of defects on the surface of magnetic tiles critically important. However, due to the small size of defects on the tile image and the reflectivity of the defective surface, the details of image characteristics are not prominently acquired.These problems bring a lot of difficulties for the recognition of magnetic tile defects. In this paper, a magnetic tile defect detection method is proposed for the probAlems of unclear image features and small defects. First, the image is processed using linear variation to enhance the image detail features. Then, by introducing the inverted bottleneck block structure in MobileNetV2, the Attention Parallel Residual Convolution Block (APR) is proposed, and the Lightweight Parallel Attention Residual Network (LPAR-Net) is built. In APR Block, 7 × 7 convolution is introduced so that the model can extract spatial features from a larger range, and weighted fusion of input images by residual structure. In addition, in this paper, CBAM is improved, split into two parts and inserted into APR Block. Finally, the mainstream image classification models and the LPAR-Net proposed in this paper are used for comparison, respectively. The experimental results show that the method achieves 93.63% accuracy on the adopted dataset, which is better than the existing mainstream image classification network models DenseNet, MobileNet, ConvNext and so on. In addition, this paper introduces a strip steel surface defect dataset and compares it with the above image classification model, which verifies that the detection method proposed in this paper still has strong recognition capability.

High-Resolution Sea Surface Target Detection Using Bi-Frequency High-Frequency Surface Wave Radar

The monitoring of the sea surface, whether it is the state of the sea or the position of targets (ships), is an up-to-date research topic. In order to determine localization parameters of ships, we propose a high-resolution algorithm for primary signal processing in high-frequency surface wave radar (HFSWR) which operates at two frequencies. The proposed algorithm is based on a high-resolution estimate of the range–Doppler (RD-HR) map formed at every antenna in the receive antenna array, which is an essential task, because the performance of the entire radar system depends on its estimation. We also propose a new focusing method allowing us to have only one RD-HR map in the detection process, which collects the information from both these carrier frequencies. The goal of the bi-frequency mode of operation is to improve the detectability of targets, because their signals are affected by different Bragg-line interference patterns at different frequencies, as seen on the RD-HR maps during the primary signal processing. Also, the effect of the sea (sea clutter) manifests itself in different ways at different frequencies. Some targets are masked (undetectable) at one frequency, but they become visible at another frequency. By exploiting this, we increase the probability of detection. The bi-frequency architecture (system model) for the localization of sea targets and the novel signal model are presented in this paper. The advantage of bi-frequency mode served as a motivation for testing the detectability of small boats, which is otherwise a very challenging task, primarily because such targets have a small radar reflective surface, they move quickly, and often change their direction. Based on experimentally obtained results, it can be observed that the probability of detection of small boats can also be significantly improved by using a bi-frequency architecture.

Three-dimensional evaluation of the responses of two species of flies (Diptera) to an indoor light trap

Abstract We used the Photonic Fence Monitoring Device (PFMD) to evaluate orientation by Musca domestica L. (Diptera: Muscidae), and Calliphora vicina Robineau-Desvoidy (Diptera: Calliphoridae) to the Zevo Flying Insect Trap Model 3. The PFMD’s dual cameras record infrared light (IR) reflected from a wavelength-specific fabric; insects do not reflect IR at the same wavelength and are tracked in 3 dimensions as moving objects. The plug-in trap emits ultraviolet and blue light from behind an opaque shield; attracted insects enter the space between the shield and the wall and are trapped on a sticky cartridge facing the wall. An experiment (N = 10) with replicates of approximately 40, 1- to 7-day-old mixed-sex flies of each species was conducted in a 6.1 m3 arena. Prior to turning the trap on, the fly movement was not directed toward the trap on the back wall of the arena, regardless of whether the overhead light was on or off. When the overhead light was off, the mean first catch of both species occurred within 5 min after the trap was turned on, and 33.1% and 41.8% of M. domestica and C. vicina, respectively, were caught. House flies flew toward the trap, many approaching from below, while C. vicina apparently walked or flew outside the field of view of the PFMD until they appeared on the vertical reflective surface, and then walked toward the trap from all directions. Our results show that the Zevo Trap attracts and catches flies, and that the PFMD can be used to track flying and walking flies.