Observation Angle Research Articles

Space-resolved line shape model for sputtered atoms of finite-size targets

High-resolution emission spectroscopy provides valuable information on the physical sputtering process during plasma-wall interaction. Up to now, analyzing the observed spectral lines during sputtering did not account for the finite size of the targets. It becomes crucial if the size of the target becomes comparable with the distance the sputtered atoms travel before emitting the photons. So, for example, the generally used standard emission model based on an infinite target or the point source approximation breaks for observations using two lines of sight: parallel and perpendicular to the normal of the target. It is impossible to achieve consistent results for energy and angular distribution of sputtered atoms. The new space-resolved emission model for finite-size targets developed in this work removes this gap. It incorporates the space-velocity transformation for the distribution function and includes the finite lifetime of excited states. The model was validated using emission spectra of sputtered atoms from a polycrystalline tungsten sample bombarded by monoenergetic Ar+ with kinetic energies of 100 eV to 140 eV at normal incidence in the linear plasma device PSI-2. Using the new model enables the simultaneous fitting of the line shapes of sputtered tungsten for both observation angles. The optimization process is performed using the standard Thompson distribution by separating the energy-dependent parameter and the angular distribution.

A multimessenger model for neutron star–black hole mergers

ABSTRACT We present a semi-analytic model for predicting kilonova light curves from the mergers of neutron stars with black holes (NSBH). The model is integrated into the mosfit platform, and can generate light curves from input binary properties and nuclear equation-of-state considerations, or incorporate measurements from gravitational wave (GW) detectors to perform multimessenger parameter estimation. The rapid framework enables the generation of NSBH kilonova distributions from binary populations, light curve predictions from GW data, and statistically meaningful comparisons with an equivalent binary neutron star (BNS) model in mosfit. We investigate a sample of kilonova candidates associated with cosmological short gamma-ray bursts, and demonstrate that they are broadly consistent with being driven by NSBH systems, though most have limited data. We also perform fits to the very well sampled GW170817, and show that the inability of an NSBH merger to produce lanthanide-poor ejecta results in a significant underestimate of the early (≲2 d) optical emission. Our model indicates that NSBH-driven kilonovae may peak up to a week after merger at optical wavelengths for some observer angles. This demonstrates the need for early coverage of emergent kilonovae in cases where the GW signal is either ambiguous or absent; they likely cannot be distinguished from BNS mergers by the light curves alone from ∼2 d after the merger. We also discuss the detectability of our model kilonovae with the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST).

Acoustic characterization of an installed elliptical jet

This work demonstrates a preliminary acoustic characterization of an installed elliptical jet with an aspect ratio of 2. This configuration is compared against the nominal axisymmetric installed jet case of equivalent diameter. A baseline case for the elliptical and axisymmetric nozzle geometries are obtained in the uninstalled configuration. For all cases, the acoustic Mach number is varied between 0.4 and 1.0, the azimuthal observer angle between 0° and 90°, and the axial distance from the jet exit to the observer between 0 and 30 nozzle equivalent diameters. The latter of these is an analogue for polar angle variation by keeping the radial distance from the jet to the observer constant. A flat metal plate is used for the installed case, creating a jet–plate interaction mimicking that of an aircraft engine’s exhaust and its wing. Using the same variations as the free jet, parameters such as plate height, trailing-edge distance and, for the elliptical jet, nozzle exit rotation angle are investigated to give a broad characterization of the installed elliptical jet and enable direct comparison to the axisymmetric jet case. The key comparison metric for this work is the overall sound pressure level and polar directivity of the acoustic fields.

Student Learning Behavior Recognition Incorporating Data Augmentation with Learning Feature Representation in Smart Classrooms.

A robust and scientifically grounded teaching evaluation system holds significant importance in modern education, serving as a crucial metric that reflects the quality of classroom instruction. However, current methodologies within smart classroom environments have distinct limitations. These include accommodating a substantial student population, grappling with object detection challenges due to obstructions, and encountering accuracy issues in recognition stemming from varying observation angles. To address these limitations, this paper proposes an innovative data augmentation approach designed to detect distinct student behaviors by leveraging focused behavioral attributes. The primary objective is to alleviate the pedagogical workload. The process begins with assembling a concise dataset tailored for discerning student learning behaviors, followed by the application of data augmentation techniques to significantly expand its size. Additionally, the architectural prowess of the Extended-efficient Layer Aggregation Networks (E-ELAN) is harnessed to effectively extract a diverse array of learning behavior features. Of particular note is the integration of the Channel-wise Attention Module (CBAM) focal mechanism into the feature detection network. This integration plays a pivotal role, enhancing the network's ability to detect key cues relevant to student learning behaviors and thereby heightening feature identification precision. The culmination of this methodological journey involves the classification of the extracted features through a dual-pronged conduit: the Feature Pyramid Network (FPN) and the Path Aggregation Network (PAN). Empirical evidence vividly demonstrates the potency of the proposed methodology, yielding a mean average precision (mAP) of 96.7%. This achievement surpasses comparable methodologies by a substantial margin of at least 11.9%, conclusively highlighting the method's superior recognition capabilities. This research has an important impact on the field of teaching evaluation system, which helps to reduce the burden of educators on the one hand, and makes teaching evaluation more objective and accurate on the other hand.

Shadow of rotating and twisting charged black holes with cloud of strings and quintessence

Testing gravity theories is an important and interesting issue in relativistic astrophysics using astrophysical observations. In recent years, Event horizon telescope collaboration provided valuable data from shadow of supermassive black holes located at the center of the galaxies Milky Way and Meissner 87, which may help to get information about the spacetime around the black holes. In this work, first, we consider rotating black hole solution for charged black hole with the NUT charge in the presence of clouds of strings, and study the event horizon properties of spacetime around rotating twisting and charged black holes in the cloud of strings and quintessential fields. The null geodesics of the spacetime is derived and the shadow case, radius of the shadow of the black and its distortion, due to the effects of the black hole spin, also analyzed. It is obtained that gravitational effects of black hole charge and quintessential field compensate each other and the rotating black hole’s shadow can be circular. We obtain constraints on charge and spin parameters of supermassive black holes Sgr hbox {A}^* and hbox {M87}^* using observational data from their shadow (size and observational angle) for various values of the NUT charge, cloud of strings and quintessential field parameters. Moreover, we also investigate gravitational capture cross-section for electromagnetic waves and emission rate of the black hole radiation energy through Hawking evaporation.

Scattering and Diffraction Evaluated by Physical Optics Surface Current on a Truncated Cylindrical Conductive Cap

In this study physical optics (PO) surface current is obtained by using the Malyughinetz solution to get the scattered field expression for a truncated cylindrical conductive cap satisfying the related boundary conditions given throughout this paper. This is done by using the inverse edge point method for the transformation from the Malyughinetz solution for the wave diffraction by a half plane to the wave diffraction by a truncated conductive cylinder. This transformation method can be used to examine the diffraction and scattering phenomena for curved surfaces having discontinuities as dealt with in this work. Total scattered field comprising the incident and scattered fields is plotted with respect to the observation angle for some parameters of the problem. The obtained results are examined numerically for the same parameters.

Improving the Estimation of Canopy Fluorescence Escape Probability in the Near-Infrared Band by Accounting for Soil Reflectance

Solar-induced chlorophyll fluorescence (SIF) has been found to be a useful indicator of vegetation’s gross primary productivity (GPP). However, the directional SIF observations obtained from a canopy only represent a portion of the total fluorescence emitted by all the leaf photosystems because of scattering and reabsorption effects inside the leaves and canopy. Hence, it is crucial to downscale the SIF from canopy level to leaf level by modeling fluorescence escape probability (fesc) for improved comprehension of the relationship between SIF and GPP. Most methods for estimating fesc rely on the assumption of a “black soil background,” ignoring soil reflectance and the effect of scattering between soils and leaves, which creates significant uncertainties for sparse canopies. In this study, we added a correction factor considering soil reflectance, which was modeled using the Gaussian process regression algorithm, to the semi-empirical NIRv/FAPAR model and obtained the improved fesc model accounting for soil reflectance (called the fesc_GPR-SR model), which is suitable for near-infrared SIF downscaling. The evaluation results using two simulation datasets from the Soil–Canopy–Observation of Photosynthesis and the Energy Balance (SCOPE) model and the Discrete Anisotropic Radiative Transfer (DART) model showed that the fesc_GPR-SR model outperformed the NIRv/FAPAR model, especially for sparse vegetation, with higher accuracy for estimating fesc (R2 = 0.954 and RMSE = 0.012 for SCOPE simulations; R2 = 0.982 and RMSE = 0.026 for DART simulations) compared with the NIRv/FAPAR model (R2 = 0.866 and RMSE = 0.100 for SCOPE simulations; R2 = 0.984 and RMSE = 0.070 for DART simulations). The evaluation results using in situ observation data from multi-species canopies also suggested that the leaf-level SIF calculated by the fesc_GPR-SR model tracked better with photosynthetic active radiation absorbed by green components (APARgreen) for sparse vegetation (R2 = 0.937, RMSE = 0.656 mW/m2/nm) compared with the NIRv/FAPAR model (R2 = 0.921, RMSE = 0.904 mW/m2/nm). The leaf-level SIF calculated by the fesc_GPR-SR model was less sensitive to observation angles and differences in canopy structure among multiple species. These results emphasize the significance of accounting for soil reflectance in the estimation of fesc and demonstrate that the fesc_GPR-SR model can contribute to further exploring the physiological mechanism between SIF and GPP.

Optical interference coatings for coloured building integrated photovoltaic modules: Predicting and optimising visual properties and efficiency

The presented work is focusing on optical interference coatings on the back side of the front glass for crystalline silicon-based photovoltaic modules. We present results on how such coatings can be designed to obtain desired visual properties combined with a limited loss in power conversion efficiency. This colouring technology may therefore be very attractive for building integrated photovoltaics. Coating design parameters such as number of layers, design wavelength, layer thicknesses, and layer refractive indices affect both the visual appearance parameters and the efficiency. Important colour parameters are lightness, chroma, and hue, and we demonstrate how these colour parameters are influenced by the design parameters of the optical interference coating.Using optical interference coatings to create colours results in colours that are dependent on the observation angle. We have introduced a new parameter for quantification of angular colour dependence. Our results show that the angular colour dependence can be reduced by increasing the refractive indices of the interference coating.For many building projects it may be highly desired to combine high power conversion efficiency with certain visual properties. The results from our work also indicate some of the possibilities and challenges in this regard.

A UAV Path Planning Method for Building Surface Information Acquisition Utilizing Opposition-Based Learning Artificial Bee Colony Algorithm

To obtain more building surface information with fewer images, an unmanned aerial vehicle (UAV) path planning method utilizing an opposition-based learning artificial bee colony (OABC) algorithm is proposed. To evaluate the obtained information, a target information entropy ratio model based on observation angles is proposed, considering the observation angle constraints under two conditions: whether there is an obstacle around the target or not. To efficiently find the optimal observation angles, half of the population that is lower-quality generates bit points through opposition-based learning. The algorithm searches for better individuals near the bit points when generating new solutions. Furthermore, to prevent individuals from observing targets repeatedly from similar angles, the concept of individual abandonment probability is proposed. The algorithm can adaptively abandon similar solutions based on the relative position between the individual and the population. To verify the effectiveness of the proposed method, information acquisition experiments were conducted on real residential buildings, and the results of 3D reconstruction were analyzed. The experiment results show that while model accuracy is comparable to that of the comparison method, the number of images obtained is reduced to one-fourth of the comparison method. The operation time is significantly reduced, and 3D reconstruction efficiency is remarkably improved.

The contribution of faint Lyman-αemitters to extended Lyman-αhalos constrained by MUSE clustering measurements

Recent detections of extended Lyman-αhalos around Lyαemitters (LAEs) have been reported on a regular basis, but their origin is still under investigation. Simulation studies predict that the outer regions of the extended halos contain a major contribution from the Lyαemission of faint, individually undetected LAEs. To address this matter from an observational angle, we used halo occupation distribution (HOD) modeling to reproduce the clustering of a spectroscopic sample of 1265 LAEs at 3 < z < 5 from the MUSE-Wide survey. We integrated the Lyαluminosity function to estimate the background surface brightness due to discrete faint LAEs. We then extended the HOD statistics inwards towards small separations and computed the factor by which the measured Lyαsurface brightness is enhanced by undetected close physical neighbors. We considered various clustering scenarios for the undetected sources and compared the corresponding radial profiles. This enhancement factor from LAE clustering depends strongly on the spectral bandwidth Δvover which the Lyαemission is integrated and this value can amount to ≈20 − 40 for small values of Δv(around 200 − 400 km s−1) as achieved by recent studies utilizing integral-field spectrographic data. The resulting inferred Lyαsurface brightness of faint LAEs ranges between (0.4 − 2)×1020 erg s−1 cm−2 arcsec−2, with a very slow radial decline outwards. Our results suggest that the outer regions of observed Lyαhalos (R ≳ 50 pkpc) could indeed contain a strong component from external (but physically associated) LAEs, and may even be dominated by them. It is only for a relatively shallow faint-end slope of the Lyαluminosity function that this contribution from clustered LAEs would be rendered insignificant. We also confirm that the observed emission from the inner regions (R ≤ 20 − 30 pkpc) is too bright to be substantially affected by clustering. We compare our findings with predicted profiles from simulations and find good overall agreement. We outline possible future measurements to further constrain the impact of discrete undetected LAEs on observed extended Lyαhalos.

Direct sampling method to inverse wave-number-dependent source problems: determination of the support of a stationary source

This paper is concerned with a direct sampling method for imaging the support of a frequency-dependent source term embedded in a homogeneous and isotropic medium. The source term is given by the Fourier transform of a time-dependent source whose radiating period in the time domain is known. The time-dependent source is supposed to be stationary in the sense that its compact support does not vary along the time variable. Via a multi-frequency direct sampling method, we show that the smallest strip containing the source support and perpendicular to the observation direction can be recovered from far-field patterns at a fixed observation angle. With multiple but discrete observation directions, the shape of the so-called Θ-convex hull of the source support can be recovered. We even extend the proposed algorithm to the case of near-field data in three dimensions. The frequency-domain analysis performed here can be used to handle inverse time-dependent source problems. Our algorithm has low computational overhead and is robust against noise. Numerical experiments in both two and three dimensions have proved our theoretical findings.

The influence of a strong local atmospheric disturbance on the resonant structure of the near field of a low-frequency loop antenna located in the Earth's ionosphere

Numerical calculations were carried out of the time dependence of the near electric field strength of an ionospheric loop antenna in the frequency range 1...10 kHz under the influence of a strong local disturbance floating in the atmosphere. A disturbance model in the form of a point source of energy was used. It is shown that as the disturbance region approaches frame antenna, the frequency and spatial resonant structure of the field strength changes qualitatively. Resonance near the lower hybrid frequency practically disappears, and resonance at small observation angles relative to the direction of the local geomagnetic field transforms into transverse resonance.

Rubber Tree Recognition Based on UAV RGB Multi-Angle Imagery and Deep Learning

The rubber tree (Hevea brasiliensis) is an important tree species for the production of natural latex, which is an essential raw material for varieties of industrial and non-industrial products. Rapid and accurate identification of the number of rubber trees not only plays an important role in predicting biomass and yield but also is beneficial to estimating carbon sinks and promoting the sustainable development of rubber plantations. However, the existing recognition methods based on canopy characteristic segmentation are not suitable for detecting individual rubber trees due to their high canopy coverage and similar crown structure. Fortunately, rubber trees have a defoliation period of about 40 days, which makes their trunks clearly visible in high-resolution RGB images. Therefore, this study employed an unmanned aerial vehicle (UAV) equipped with an RGB camera to acquire high-resolution images of rubber plantations from three observation angles (−90°, −60°, 45°) and two flight directions (SN: perpendicular to the rubber planting row, and WE: parallel to rubber planting rows) during the deciduous period. Four convolutional neural networks (multi-scale attention network, MAnet; Unet++; Unet; pyramid scene parsing network, PSPnet) were utilized to explore observation angles and directions beneficial for rubber tree trunk identification and counting. The results indicate that Unet++ achieved the best recognition accuracy (precision = 0.979, recall = 0.919, F-measure = 94.7%) with an observation angle of −60° and flight mode of SN among the four deep learning algorithms. This research provides a new idea for tree trunk identification by multi-angle observation of forests in specific phenological periods.

Shadow Geometry of Kerr Naked Singularities

Direct imaging of supermassive black holes (SMBHs) at event horizon-scale resolutions, as recently done by the Event Horizon Telescope, allows for testing alternative models to SMBHs such as Kerr naked singularities (KNSs). We demonstrate that the KNS shadow can be closed, open, or vanishing, depending on the spins and observational inclination angles. We study the critical parameters where the KNS shadow opens a gap, a distinctive phenomenon that does not happen with the black hole shadow. We show that the KNS shadow can only be closed for dimensionless spin a ≲ 1.18 and vanishing for a ≳ 1.18 for certain ranges of inclination angles. We further analyze the effective angular momentum of photon orbits to demonstrate the fundamental connections between light geodesics and the KNS shadow geometry. We also perform numerical general relativistic ray-tracing calculations, which reproduce the analytical topological change in the KNS shadow, and illustrate other observational features within the shadow due to the lack of an event horizon. By comparing the geometric features of the KNS shadow with black hole shadow observations, the topological change in the shadow of KNSs can be used to test the cosmic censorship hypothesis and KNSs as alternative models to SMBHs.

A Novel 3D ArcSAR Sensing System Applied to Unmanned Ground Vehicles

Microwave radar has advantages in detection accuracy and robustness, and it is an area of active research in unmanned ground vehicles. However, the existing conventional automotive corner radar, which employs real-aperture antenna arrays, has limitations in terms of observable angle and azimuthal resolution. This paper proposes a novel 3D ArcSAR method to address this issue, which combines rotational synthetic aperture radar (SAR) and direction estimation algorithms. The method aims to reconstruct 3D images of 360° scenes and offers distinctive advantages in both azimuthal and altitudinal sensing. Nevertheless, due to the unique structural characteristics of vehicle SAR, it is limited to receiving only a single snapshot signal for 3D sensing. We propose a resolution algorithm based on ArcSAR and the iterative adaptive approach (IAA) to resolve the limitation. Furthermore, the errors in altitude angle estimation of the proposed algorithm and conventional algorithms are analyzed under various conditions, including different target spacing and signal-to-noise ratio (SNR). Finally, we design and implement a prototype of the 3D ArcSAR sensing system, which utilizes a millimeter-wave MIMO radar system and a rotating scanning mechanical system. The experimental results obtained from this prototype effectively validate the effectiveness of the proposed method.

Leveraging Landsat-8/-9 underfly observations to evaluate consistency in reflectance products over aquatic environments

With an identical design and build, the Operational Land Imager-2 (OLI2) aboard Landsat-9 (L9) complements OLI observations by reducing the global revisit rate of Landsat to 8 days. This study takes advantage of near-coincident OLI2 and OLI observations obtained on 11–17 November 2021 to assess the relative quality of the standard United States Geological Survey (USGS) top-of-atmosphere (TOA) reflectance (ρt) and atmospherically corrected reflectance (aquatic reflectance; ρwAR) products over bodies of water. The TOA assessment was carried out for all the visible bands, including the panchromatic band, as well as the near-infrared (NIR) and shortwave infrared (SWIR) bands, whereas ρwAR products were analyzed in the 443, 482, 561, and 655 nm bands. The overlapping areas of OLI-OLI2 ρw product pairs were further analyzed for the rigor in corrections for the viewing geometry implemented in selected atmospheric correction (AC) processors, including SeaDAS, ACOLITE, and POLYMER, with products denoted as ρwAR, ρwac, and ρwpol, respectively. Overall, we found the OLI2-OLI ρt products to be consistent within 0.4% in the visible-near-infrared (VNIR) bands except in the green band (561 nm), where OLI2 records ∼0.8% larger values than OLI. The two SWIR bands (1610 and 2200 nm) were also found to agree within ∼2.2% and 2.1%, respectively, with OLI2 being lower in magnitude. The median differences in the standard ρw (ρwAR) were estimated to be ∼2.4%, 1.5%, 2.3%, and 2.5% in the 443, 482, 561, and 655 nm bands, respectively, which are well within the accepted differences in cross-mission data merging schemes. Further, we show that OLI2's signal-to-noise ratio (SNR) is 7–30% higher than that of OLI in all the bands, likely due to its 14-bit digitization rate, as compared to OLI's 12-bit digitization rate. Our self-consistency assessment of the AC processors for handling the differences in the view zenith angles (ΔVZA) and relative azimuth angles (ΔRAA) of OLI2 and OLI observations suggests that, overall, the processors account for the Sun-sensor geometry differently at different spectral bands. These differences (inconsistencies) amount to average median absolute percentage differences (MAPD) in ρw from 0.3 to 5.3% (e.g., ∆ρwAR443nmΔVZAΔRAA=ρwAR,OLI443+6.310−ρwAR,OLI2443+3.9−13<0.5%).More specifically, we found that SeaDAS provides the most optimal corrections for the angular variability as a function of VZA, ρwac are most consistent for different ranges of RAAs, and POLYMER performs best in the 443 nm band. We surmise that future (and other existing) AC methods should be tested with Landsat-8/-9 underfly imagery to quantify their performance for tackling the variability in imaging geometry and minimize associated uncertainties. With several missions planned for launch by the end of this decade, it is further emphasized that post-launch tandem maneuvers are essential to creating harmonized multi-mission data products and, therefore, similar operations should be considered and extended to ensure a broad range of environmental conditions are captured for comprehensive cross-mission analyses.

Joint Power and Bandwidth Allocation with RCS Fluctuation Characteristic for Space Target Tracking

Reasonable allocation of space-based radar resources is a crucial aspect of improving the accuracy of space multi-target tracking and enhancing spatial awareness. The conventional resource allocation algorithm fails to exploit the high dynamic radar cross-section (RCS) characteristics, resulting in poor tracking robustness, tracking divergence, or even loss of tracking. However, the RCS of space targets fluctuates considerably in actual tracking scenarios, which cannot be disregarded for space target tracking tasks. To address this issue, we propose an adaptive allocation method that considers the dynamic RCS fluctuation characteristic for space-based radar tracking assignments. The proposed method exploits the predictable orbital information of space target to calculate the real-time observation angle of radar, and then obtains the multi-target dynamic RCS through the target RCS dataset. By combining the obtained RCS sequence, radar power, and bandwidth, an optimal model for radar tracking accuracy is established based on the multi-target posterior Cramér–Rao lower bound (PCRLB) to evaluate the tracking performance. By resolving the aforementioned multivariance optimization problem, we eventually acquire the results of power and bandwidth pre-allocation for tracking multiple space targets. Simulation results validate that, compared with the traditional methods, the proposed joint dynamic RCS power and bandwidth allocation (JRPBA) method can achieve superior tracking accuracy and minimize instances of missed tracking.

Impacts of clumping effect on canopy reflectance using 3D radiative transfer modeling

The product of leaf area index (LAI) and clumping index (CI) quantifies the effective leaf abundance and distribution across the landscape, and therefore, governs the radiation absorption, evapotranspiration, and carbon assimilation processes in the terrestrial ecosystems. Previous studies were mainly focused on developing inversion methods applicable to large scale for retrieving LAI and CI from multi-angular satellite observations. However, a few studies focused on quantifying the sensitivity of canopy bidirectional reflectance distribution function (BRDF) to changes in CI in a forward manner, hampering an accurate understanding of the relationship between CI and BRDF. In this study, we simulated how BRDF responds to changes in CI in Qinghai spruce (Picea crassifolia) forests based on a 3D radiative transfer model LESS and ground-measured data. We found that the LESS model effectively simulated the hot-spot, roof, and bowl-edge characteristics of the canopy BRDF by changing the sun-sensor geometry. We constructed forest scenes with variable CI (ranging from 0.4 to 0.8) to investigate the clumping effect on BRDF with different solar and observation angles. The red band bidirectional reflectance factor (BRF) showed higher sensitivity to changes in CI than that in the near-infrared (NIR) band. Canopy BRFs in the red band along the principal plane and cross principal planes measured in different seasons showed consistent sensitivity to changes in CI, suggesting that the red band BRF is helpful for CI inversion for forests with different levels of foliage clumping. In the NIR band, canopy BRFs along the principal plane measured in growing seasons [with solar zenith angle (SZA) &amp;lt;40°] and the cross principal plane measured in non-growing seasons (with SZA &amp;gt;40°) were sensitive to changes in CI in highly clumped forests (with CI ranging from 0.4 to 0.6). However, canopy BRF in the NIR band showed low sensitivity to changes in CI in highly clumped forests (CI &amp;lt;0.6), especially along the cross principal plane when SZA was approximately 10°. The simulated BRFs in the red and NIR bands showed relatively low sensitivity to changes in SZAs at a VZA of 40° and 0°, respectively. We highly recommend including the red band BRF for CI retrievals, and using a VZA of 40° in the red band and 0° in the NIR band may help reduce the CI estimation uncertainty caused by changes in SZA. This research provides a new perspective for understanding the sensitivity of multi-angular satellite data to changes in canopy structural characteristics of vegetation in global ecosystem studies and may help improve CI estimations using the multiangular optical remote sensing data.

Visibility Evaluation and Suitability Analysis of Fire Lookout Towers in Mediterranean Region, Southwest Anatolia/Türkiye

The effectiveness of fire towers in combating forest fires relies on their appropriate observation angles, enabling a swift and efficient response to fire incidents. The purpose of this study is to examine the effectiveness of 49 fire towers located within the Antalya Forestry Regional Directorate, situated in the Mediterranean basin—a region prone to frequent forest fires. The assessment encompasses the visibility of the entire study area, including forested regions, as well as the visibility of 2504 forest fires recorded by the towers between 2008 and 2021. Furthermore, the evaluation considers the objectives based on Forest Management Directorates and conducts a location suitability analysis for the six towers with the lowest visibility. We utilized the Viewshed Tool in the ArcGIS application and employed the Best–Worst approach. Two scenarios were devised, considering smoke height at 0 m or 100 m, to determine the visibility of fire lookout towers. In Scenario I, assuming a smoke height of 100 m, only three towers exhibited visibility above 70%. However, in Scenario II, assuming a smoke height of 0 m, no towers achieved visibility above 70%. Scenario I indicated that only two towers possessed a view of more than 70% of the forested region, while Scenario II suggested that no towers met this criterion. For the visibility of forest fires, Scenario I identified seven towers capable of observing more than 70%, whereas Scenario II indicated that no towers possessed such capability. In the tower suitability analysis, the visibility rates varied from 41.18% to 1016.67%. Based on the evaluation results, the current visibility capacities of the 49 fire towers proved insufficient for effective preventive measures.

Ultrahigh-efficient material informatics inverse design of thermal metamaterials for visible-infrared-compatible camouflage

Multispectral camouflage technologies, especially in the most frequently-used visible and infrared (VIS-IR) bands, are in increasing demand for the ever-growing multispectral detection technologies. Nevertheless, the efficient design of proper materials and structures for VIS-IR camouflage is still challenging because of the stringent requirement for selective spectra in a large VIS-IR wavelength range and the increasing demand for flexible color and infrared signal adaptivity. Here, a material-informatics-based inverse design framework is proposed to efficiently design multilayer germanium (Ge) and zinc sulfide (ZnS) metamaterials by evaluating only ~1% of the total candidates. The designed metamaterials exhibit excellent color matching and infrared camouflage performance from different observation angles and temperatures through both simulations and infrared experiments. The present material informatics inverse design framework is highly efficient and can be applied to other multi-objective optimization problems beyond multispectral camouflage.