Search Results (291)

Multi-angular remote sensing plays a critical role in the study domains of ecological monitoring, climate change, and energy balance. The successful retrieval of the surface Bidirectional Reflectance Distribution Function (BRDF) and albedo from multi-angular remote sensing observations for various applications relies on the sensitivity of an appropriate BRDF model to both the number and the sampling distribution of multi-angular observations. In this study, based on selected high-quality multi-angular datasets, we designed three representative angular sampling schemes to systematically analyze different illuminating–viewing configurations of the retrieval results in a kernel-driven BRDF model framework. We first proposed an angular information index (AII) by incorporating a weighting mechanism and information effectiveness to quantify the angular information content for the angular sampling distribution schemes. In accordance with the principle that observations on the principal plane (PP) provide the most representative anisotropic scattering features, the assigned weight gradually decreases from the PP towards the cross-principal plane (CPP). The information effectiveness is determined based on the cosine similarity between the observations, effectively reducing the information redundancy. With such a method, we assess the AII of the different sampling schemes and further analyze the impact of angular distribution on both BRDF inversion and the estimation of snow surface albedo, including White-Sky Albedo (WSA) and Black-Sky Albedo (BSA) based on the RossThick-LiSparseReciprocal-Snow (RTLSRS) BRDF model. The main conclusions are as follows: (1) The AII approach can serve as a robust indicator of the efficiency of different sampling schemes in BRDF retrieval, which indicates that the RTLSRS model can provide a robust inversion when the AII value exceeds a threshold of −2. (2) When the AII value reaches such a reliable level, different sampling schemes can reproduce the BRDF shapes of snow across different bands to somehow varying degrees. Specifically, observations with smaller view zenith angle (VZA) ranges can reconstruct a BRDF shape that amplifies the anisotropic effect of snow; in addition, the forward scattering tends to be more pronounced at larger solar zenith angles (SZAs), while the variations in BRDF shape reconstructed from off-PP observations depend on both wavelength and SZAs. (3) The relative differences in both BSA and WSA grow with increasing wavelength for all these sampling schemes, mostly within 5% for short bands but up to 30% for longer wavelengths. With this novel AII method to quantify the information contribution of multi-angular sampling distributions, this study offers valuable insights into several main multi-angular BRDF sampling strategies in satellite sensor missions, which relate to most of the fields of multi-angular remote sensing applications in engineering. Full article

This study presents a hybrid BRDF modeling framework combining a five-parameter physical model with a (20,20,20) Multilayer Perceptron (MLP) model network to address the critical challenge of accurate grazing-angle prediction for low-gloss black coatings (SB-3A, Z306, PNC). While the baseline parametric model achieves <5% RMSE at θ_i ≤ 60°, its inability to capture shadowing effects leads to >1.2 RMSE at 80° incidence. The proposed MLP model-enhanced solution reduces these high-angle errors to <0.012 RMSE while maintaining <5-min computational efficiency. Comprehensive validation shows the framework’s universality across materials with apparent anisotropy indices (ASI) of 0.465–30.26. The work demonstrates that neural networks can optimally compensate for missing physics in traditional models without sacrificing interpretability, offering immediate industrial value for aerospace coating analysis. Full article

Row crops are regarded as a transitional type between continuous and discrete vegetation. Previous studies idealized row crops as periodic hedgerows with rectangular cross-sections. However, these models relied on oversimplified assumptions, failing to capture the intrinsic heterogeneity of canopy or its dynamic evolution over the life cycle. In 2020, we proposed a row crop model with a gradual decrease in leaf area volume density (LAVD) from the center of the row to the edge, partially overcoming these limitations. Building on this previous model, this paper introduces the leaf shape factor proposed by Mõttus et al. into the model. Three control parameters, a leaf width control parameter (β), leaf length control parameter (ψ), and leaf azimuth control parameter (e), are proposed to regulate the spatial distribution of LAVD. Additionally, an empirical exponential function from Watanabe et al. is adopted to describe the leaf zenith angle distribution, enabling the realistic calculation of the G-function and Γ-function in conjunction with leaf azimuth distribution. The LAVD is formulated at three hierarchical scales: individual scale, row scale, and scene scale. The model delivers two key advancements: enabling pronounced spatial heterogeneity and high tunability of the LAVD, and accurately simulating row crops throughout the life cycle, which bridges the row structure and continuous stages of row crops. Radiative transfer simulations are conducted to derive the bidirectional reflectance distribution function (BRDF), which is validated against the discrete anisotropic radiative transfer (DART) model. Comparisons across three growth stages demonstrated good consistency. Furthermore, this paper investigates the sensitivity of the BRDF to three control parameters (β, ψ, and e). The results indicate that changes in three parameters significantly affect the reflectance in the darkspot direction, leading to a maximum error of 22.6%. In carrying out remote sensing applications such as parameter inversion and yield estimation for row crops, the new model is recommended for more accurate BRDF simulations. Full article

Reliable power generation from solar cells is critical for spacecraft operation. High-energy laser irradiation poses a significant threat, as it can potentially cause irreversible damage to solar cells, which is difficult to detect remotely using conventional techniques such as radar or optical imaging. Spectral detection offers a potential approach through unique “spectral fingerprints,” but the spectral characteristics of laser-damaged solar cells remain insufficiently documented. This study investigates the scattering spectral characteristics of triple-junction GaAs (Gallium Arsenide) solar cells subjected to nanosecond pulsed laser irradiation to establish spectral signatures for damage assessment. GaAs solar cells were irradiated at varying energy densities. Bidirectional Reflectance Distribution Function (BRDF) spectra (400–1200 nm) were measured. A thin-film interference model was used to simulate damage effects by varying layer thicknesses, thereby interpreting experimental results. The results demonstrate that as the laser energy density increases from 0.12 to 2.96 J/cm², the number of absorption peaks in the visible range (400–750 nm) decreases from three to zero, and the oscillation in the near-infrared range vanishes completely, indicating progressive damage to the GaInP (Gallium Indium Phosphide) and GaAs layers. This study provides a spectral-based approach for remote assessment of laser-induced damage to solar cells, which is crucial for satellite health monitoring. Full article

The successful launch of Korea Multipurpose Satellite-3/Advanced Earth Imaging Sensor System (KOMPSAT-3/AEISS) on 18 May 2012 allowed the Republic of Korea to meet the growing demand for high-resolution satellite imagery. However, like all satellite sensors, KOMPSAT-3/AEISS experienced temporal changes post-launch and thus requires ongoing evaluation and calibration. Although more than a decade has passed since launch, the KOMPSAT-3/AEISS mission and its multi-year data archive remain widely used. This study focused on the cross-calibration of KOMPSAT-3/AEISS with Sentinel-2A/Multispectral Instrument (MSI) by comparing the radiometric responses of the two satellite sensors under similar observation conditions, leveraging the linear relationship between Digital Numbers (DN) and top-of-atmosphere (TOA) radiance. Cross-calibration was performed using near-simultaneous satellite images of the same region, and the Spectral Band Adjustment Factor (SBAF) was calculated and applied to account for differences in spectral response functions (SRF). Additionally, Bidirectional Reflectance Distribution Function (BRDF) correction was applied using MODIS-based kernel models to minimize angular reflectance effects caused by differences in viewing and illumination geometry. This study aims to evaluate the radiometric consistency of KOMPSAT-3/AEISS relative to Sentinel-2A/MSI over Baotou scenes acquired in 2022–2023, derive band-specific calibration coefficients and compare them with prior results, and conduct a side-by-side comparison of cross-calibration and vicarious calibration. Furthermore, the cross-calibration yielded band-specific gains of 0.0196 (Blue), 0.0237 (Green), 0.0214 (Red), and 0.0136 (NIR). These findings offer valuable implications for Earth observation, environmental monitoring, and the planning and execution of future satellite missions. Full article

In recent years, unmanned aerial vehicle (UAV) quantitative remote sensing technology has demonstrated significant advantages in fields such as agricultural monitoring and ecological environment assessment. However, achieving the goal of quantification still faces major challenges due to the angle effect. This effect, caused by the bidirectional reflectance distribution function (BRDF) of surface targets, leads to significant spectral response variations at different observation angles, thereby affecting the inversion accuracy of physicochemical parameters, internal components, and three-dimensional structures of ground objects. This study systematically reviewed 48 relevant publications from 2000 to the present, retrieved from the Web of Science Core Collection through keyword combinations and screening criteria. The analysis revealed a significant increase in both the number of publications and citation frequency after 2017, with research spanning multiple disciplines such as remote sensing, agriculture, and environmental science. The paper comprehensively summarizes research progress on the angle effect in UAV quantitative remote sensing. Firstly, its underlying causes based on BRDF mechanisms and radiative transfer theory are explained. Secondly, multi-angle data acquisition techniques, processing methods, and their applications across various research fields are analyzed, considering the characteristics of UAV platforms and sensors. Finally, in view of the current challenges, such as insufficient fusion of multi-source data and poor model adaptability, it is proposed that in the future, methods such as deep learning algorithms and multi-platform collaborative observation need to be combined to promote theoretical innovation and engineering application in the research of the angle effect in UAV quantitative remote sensing. This paper provides a theoretical reference for improving the inversion accuracy of surface parameters and the development of UAV remote sensing technology. Full article

The NASA CERES project conducts an independent assessment of the calibration stability of MODIS and VIIRS reflective solar bands to ensure consistency in CERES-derived clouds and radiative flux products. The assessment includes the use of tropical deep convective cloud invariant targets (DCC-IT), identified using a simple brightness temperature threshold. For visible bands, the collective DCC pixel radiance probability density function (PDF) was negatively skewed. By tracking the bright inflection point, rather than the PDF mode, and applying an anisotropic adjustment suited for the brightest DCC radiances, the lowest trend standard errors were obtained within 0.26% for NPP-VIIRS and within 0.36% for NOAA20-VIIRS and Aqua-MODIS. A kernel density estimation function was used to infer the PDF, which avoided discretization noise caused by sparse sampling. The near 10° regional consistency of the anisotropic corrected PDF inflection point radiances validated the DCC-IT approach. For the shortwave infrared (SWIR) bands, the DCC radiance variability is dependent on the ice particle scattering and absorption and is band-specific. The DCC radiance varies regionally, diurnally, and seasonally; however, the inter-annual variability is much smaller. Empirical bidirectional reflectance distribution functions (BRDFs), constructed from multi-year records, were most effective in characterizing the anisotropic behavior. Due to the distinct land and ocean as well as regional radiance differences, land, ocean, and regional BRDFs were evaluated. The regional radiance variability was mitigated by normalizing the individual regional radiances to the tropical mean radiance. Because the DCC pixel radiances have a Gaussian distribution, the mean radiance was used to track the DCC response. The regional BRDF-adjusted DCC-IT mean radiance trend standard errors were within 0.38%, 0.46%, and 1% for NOAA20-VIIRS, NPP-VIIRS, and Aqua-MODIS, respectively. Full article

Traditional non-destructive measurement of surface roughness exploits complete data of bidirectional reflective distribution function (BRDF). The instrument is normally bulky and the process should be conducted off-line, hence it is time-consuming. If only a part of BRDF data can be sufficient to determine the surface roughness, both the measurement equipment and processing time can be significantly reduced. This paper proposes a compact device capable of detecting multiple angular intensities of reflective scattering with different incident angles from different spatial points of the target object at the same time. It is used to evaluate the surface roughness of a standard specimen with arithmetic mean roughness (Ra) values ranging from 0.13 µm to 2.1 µm. The case of measuring two spatial points of the specimen is used for illustrating the calibration procedure of the device and how the data were searched and processed to increase the reliability and robustness for evaluating the surface roughness with reduced data of BRDF. Similar methodologies can be applicable for other real-time detection methods based on the scattering process. Full article

Accurate light simulations using virtual plant models are essential for analyzing how plant structures influence the micro-light climate within canopies. Such simulations are increasingly important in applications including remote sensing, greenhouse optimization, and synthetic data generation for agricultural systems. However, many current models simplify leaf optical behavior by assuming purely diffuse reflectance, thereby neglecting the spectral and angular variability described by the bidirectional reflectance distribution function (BRDF). To address this limitation, the spectral BRDF of cucumber leaves was experimentally measured and corresponding Phong reflectance model parameters were determined for use in the GroIMP simulation environment. These parameters were optimized to replicate the angular and spectral reflectance distribution patterns and evaluated against a diffuse reflectance model. The Phong model successfully reproduced key features of the BRDF, particularly the increased diffuseness in the green and far-red spectral regions, although deviations in hemispherical reflectance emerged at high incidence angles. The resulting Phong parameters offer a practical method for incorporating wavelength- and direction-dependent reflectance into virtual plant simulations. These parameters can be adapted to other reflectance values of leaves with similar optical properties using hemispherical reflectance measurements, enabling more realistic light modeling in virtual canopies. Within a 30–60° incidence, the Phong BRDF reduced per-wavelength error relative to a diffuse baseline across all spectral regions. Full article

The harmonized multi-sensor satellite data assists users by providing seamless analysis-ready data with enhanced temporal resolution. The Harmonized Landsat Sentinel (HLS) product has gained popularity due to the seamless integration of Landsat OLI and Sentinel-2 MSI, achieving a temporal resolution of 2.8 to 3.5 days. However, applications that require monitoring intervals of less than three days or cloudy data can limit the usage of HLS data. Gaofen-1 (GF-1) Wide Field of View (WFV) data provides the capacity further to enhance the data availability by harmonization with HLS. In this study, GF-1/WFV data is harmonized with HLS by employing deep learning-based conditional Generative Adversarial Networks (cGANs). The harmonized WFV data with HLS provides an average temporal resolution of 1.5 days (ranging from 1.2 to 1.7 days), whereas the temporal resolution of HLS varies from 2.8 to 3.5 days. This enhanced temporal resolution will benefit applications that require frequent monitoring. Various processes are employed in HLS to achieve seamless products from the Operational Land Imager (OLI) and Multispectral Imager (MSI). This study applies 6S atmospheric correction to obtain GF-1/WFV surface reflectance data, employs MFC cloud masking, resamples the data to 30 m, and performs geographical correction using AROP relative to HLS data, to align preprocessing with HLS workflows. Harmonization is achieved without using BRDF normalization and bandpass adjustment like in the HLS workflows; instead, cGAN learns cross-sensor reflectance mapping by utilizing a U-Net generator and a patchGAN discriminator. The harmonized GF-1/WFV data were compared to the reference HLS data using various quality indices, including SSIM, MBE, and RMSD, across 126 cloud-free validation tiles covering various land covers and seasons. Band-wise scatter plots, histograms, and visual image color quality were compared. All these indices, including the Sobel filter, histograms, and visual comparisons, indicated that the proposed method has effectively reduced the spectral discrepancies between the GF-1/WFV and HLS data. Full article

This study developed an inertial measurement unit (IMU)-enhanced bidirectional reflectance distribution function (BRDF) imaging system to address angular errors in multi-angle polarimetric measurements. The system integrates IMU-based closed-loop feedback, motorized motion, and image calibration, achieving zenith angle error reduction of up to 1.2° and angular control precision of approximately 0.05°. With a modular and lightweight structure, it supports rapid deployment in field scenarios, while the 2000 mm rail span enables detection of large-scale targets and three-dimensional reconstruction beyond the capability of conventional tabletop devices. Experimental evaluations on six representative materials show that compared with mark-based reference angles, IMU feedback consistently improves polarimetric accuracy. Specifically, the degree of linear polarization (DoLP) mean deviations are reduced by about 5–12%, while standard deviation fluctuations are suppressed by 20–40%, enhancing measurement repeatability. For the angle of polarization (AoP), IMU feedback decreases mean errors by 10–45% and lowers standard deviations by 10–37%, ensuring greater spatial phase continuity even under high-reflection conditions. These results confirm that the proposed system not only eliminates systematic angular errors but also achieves robust stability in global measurements, providing a reliable technical foundation for material characterization, machine vision, and volumetric reconstruction. Full article

To address the growing need for field calibration of the optical properties of pedestrian targets used in autonomous emergency braking (AEB) tests, a novel three-dimensional multi-faceted standard body (TDMFSB) was developed. A camera-based analytical algorithm was proposed to evaluate the bidirectional reflectance distribution function (BRDF) characteristics of pedestrian targets. Additionally, a field calibration method applied in AEB testing scenarios (CPFAO and CPLA protocols) on one new and one aged typical pedestrian target of the same type revealed a 21% decrease in the BRDF uniformity of the aged target compared to the new one, confirming optical degradation due to repeated “crash–scatter–reassembly” cycles. The surface wear of the aged target on the side facing the vehicle produced a smoother surface, increasing its BRDF magnitude by 25% compared to the new target and making it easily detectable by the vehicle’s perception system. This led to “reverse scoring,” a safety risk in performance evaluation, necessitating timely calibration of AEB pedestrian targets to ensure reliable test results. The findings provide valuable insights into the development of regulatory techniques, evaluation standards, and technical specifications for test targets and offer a practical path toward full-life-cycle traceability and quality control. Full article

To enable accurate evaluation of satellite laser communication terminals under solar outage interference, this paper presents the design and implementation of a solar radiation simulation system targeting the 1540–1560 nm communication band. The system reconstructs co-propagating interference conditions through standardized and continuously tunable output, based on high irradiance and spectral uniformity. A compound beam homogenization structure—combining a multimode fiber and an apodizator—achieves 85.8% far-field uniformity over a 200 mm aperture. A power–spectrum co-optimization strategy is introduced for filter design, achieving a spectral matching degree of 78%. The system supports a tunable output from 2.5 to 130 mW with a 50× dynamic range and maintains power control accuracy within ±0.9%. To suppress internal background interference, a BRDF-based optical scattering model is established to trace primary and secondary stray light paths. Simulation results show that by maintaining the surface roughness of key mirrors below 2 nm and incorporating a U-shaped reflective light trap, stray light levels can be reduced to 5.13 × 10⁻¹² W, ensuring stable detection of a 10⁻¹⁰ W signal at a 10:1 signal-to-background ratio. Experimental validation confirms that the system can faithfully reproduce solar outage conditions within a ±3° field of view, achieving consistent performance in spectrum shaping, irradiance uniformity, and background suppression. The proposed platform provides a standardized and practical testbed for ground-based anti-interference assessment of optical communication terminals. Full article

Multi-angle remote sensing observations play an important role in the remote sensing of solar radiation absorbed by land surfaces. Currently, the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) teams have successively applied the Ross–Li kernel-driven bidirectional reflectance distribution function (BRDF) model to integrate multi-angle observations to produce long time series BRDF model parameter products (MCD43 and VNP43), which can be used for the inversion of various surface parameters and the angle correction of remote sensing data. Even though the MODIS and VIIRS BRDF products originate from sensors and algorithms with similar designs, the consistency between BRDF parameters for different sensors is still unknown, and this likely affects the consistency and accuracy of various downstream parameter inversions. In this study, we applied BRDF model parameter time-series data from the overlapping period of the MODIS and VIIRS services to systematically analyze the temporal and spatial differences between the BRDF parameters and derived indices of the two sensors from the site scale to the region scale in the red band and NIR band, respectively. Then, we analyzed the sensitivity of the BRDF parameters to variations in Normalized Difference Hotspot–Darkspot (NDHD) and examined the spatiotemporal distribution of zero-valued pixels in the BRDF parameter products generated by the constraint method in the Ross–Li model from both sensors, assessing their potential impact on NDHD derivation. The results confirm that among the three BRDF parameters, the isotropic scattering parameters of MODIS and VIIRS are more consistent, whereas the volumetric and geometric-optical scattering parameters are more sensitive and variable; this performance is more pronounced in the red band. The indices derived from the MODIS and VIIRS BRDF parameters were compared, revealing increasing discrepancies between the albedo and typical directional reflectance and the NDHD. The isotropic scattering parameter and the volumetric scattering parameter show responses that are very sensitive to increases in the equal interval of the NDHD, indicating that the differences between the MODIS and VIIRS products may strongly influence the consistency of NDHD estimation. In addition, both MODIS and VIIRS have a large proportion of zero-valued pixels (volumetric and geometric-optical parameter layers), whereas the spatiotemporal distribution of zero-valued pixels in VIIRS is more widespread. While the zero-valued pixels have a minor influence on reflectance and albedo estimation, such pixels should be considered with attention to the estimation accuracy of the vegetation angular index, which relies heavily on anisotropic characteristics, e.g., the NDHD. This study reveals the need in optimizing the Clumping Index (CI)-NDHD algorithm to produce VIIRS CI product and highlights the importance of considering BRDF product quality flags for users in their specific applications. The method used in this study also helps improve the theoretical framework for cross-sensor product consistency assessment and clarify the uncertainty in high-precision ecological monitoring and various remote sensing applications. Full article

Accurate solar background noise modeling in island-reef LiDAR surveys is hindered by anisotropic coastal reflectivity and dynamic light paths, which isotropic models fail to address. We propose BNR-B, a bidirectional reflectance distribution function (BRDF)-based noise model that integrates solar-receiver geometry with micro-facet scattering dynamics. Validated via single-photon LiDAR field tests on diverse coastal terrains at Jiajing Island, China, BNR-B reveals the following: (1) Solar zenith/azimuth angles non-uniformly modulate noise fields—higher solar zenith angles reduce noise intensity and homogenize spatial distribution; (2) surface reflectivity linearly correlates with noise rate (R² > 0.99), while roughness governs scattering directionality through micro-facet redistribution. BNR-B achieves 28.6% higher noise calculation accuracy than Lambertian models, with a relative phase error < 2% against empirical data. As the first BRDF-derived solar noise correction framework for coastal LiDAR, it addresses critical limitations of isotropic assumptions by resolving directional noise modulation. The model’s adaptability to marine–terrestrial interfaces enhances precision in coastal monitoring and submarine mapping, offering transformative potential for geospatial applications requiring photon-counting LiDAR in complex environments. Key innovations include dynamic coupling of geometric optics and surface scattering physics, enabling robust spatiotemporal noise quantification, critical for high-resolution terrain reconstruction. Full article