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[IEEE 2018 7th International Conference on Agro-geoinformatics (Agro-geoinformatics) - Hangzhou (2018.8.6-2018.8.9)] 2018 7th International Conference on Agro-geoinformatics (Agro-geoinformatics) - Hyperspectral Inversion of Soil Moisture Content Based on SOILSPECT Model
摘要： Soil moisture content (SMC) is the important information for the crop land irrigation management and drought warning. The study of SMC quantitative inversion based on hyperspectral remote sensing technology has become the hot spot. Because of using statistical modeling methods and without considering soil bidirectional reflection characteristics, the SMC inversion accuracy and model applicable scope were limited. The purpose of this study was to use the soil radiation transfer model (SOILSPECT) to invert SMC in order to not only improve the SMC hyperspectral inversion accuracy, but also make the model applying widely. Taking the black soil and chernozem in Gongzhuling city of Jilin province as the study object, spectrometry measurement for different SMC from 5% to 45% (5% interval) to get measured soil reflectance by using the ASD Fieldspec Pro spectrometer under the indoor condition. The influences of the light source zenith angle, observing zenith angle, azimuth angle and SMC on soil bidirectional reflectance analyzed. Then distribution SOILSPECT model parameters were obtained by using Particle Swarm Optimization (PSO) method under the different SMC gradients, and SMC inversion by using SOILSPECT model was conducted. The results showed that soil BRDF declined with SMC rising in the range of 400~1400 nm wavelength, when SMC was less than the field water holding capacity, and soil BRDF rose with SMC rising when SMC was larger than the field water holding capacity. In the range of 1400~2400nm wavelength and under different observing zenith angles, there was no rules for soil BRDF changing. SMC inversion accuracy based on SOILSPECT model was higher. R2 value was above 0.98 compared the estimated values with the measured values. The inversion accuracy for 15% and 30% of SMC were higher at every sensitive band, but that for other SMC was unsteadiness. SMC inversion accuracy based on SOILSPECT model increased with the decreasing of the observational zenith angle. The vertical observation can get the highest SMC inversion accuracy.
关键词： BRDF,SOILSPECT model,hyperspectral inversion,soil moisture content
更新于2025-09-11 14:15:04
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BRDF Analysis with Directional Statistics and Its Applications
摘要： Data-driven BRDF models using real material measurements have become increasingly prevalent due to the development of novel goniore?ectometers, but ef?cient use of these models in many graphical applications remains challenging due to the few functionalities the raw data could provide. To ameliorate this issue, we propose to analyze BRDFs using directional statistics for better handling and exploring measured materials, especially isotropic materials, with ef?cient computation and compact storage. We conduct a thorough statistical analysis on both analytical BRDF models and measured materials from the MERL database. We show that different aspects of visual appearance can be characterized by different spherical moments, from which several descriptive measures can be derived to further facilitate their usage. We demonstrate how these measures are best leveraged in some graphical applications including gamut mapping using a new BRDF similarity measure, BRDF or SVBRDF reconstruction based on material clustering, and importance sampling for measured materials based on fast extracted GGX distributions. We ?nally show the potential of our approach in the categorization of surface re?ectance types which is common for traditional photon mapping.
关键词： rendering,clustering,BRDF,directional statistics,importance sampling
更新于2025-09-10 09:29:36
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Development of a snow kernel to better model the anisotropic reflectance of pure snow in a kernel-driven BRDF model framework
摘要： The linear kernel-driven RossThick-LiSparseReciprocal (RTLSR) bidirectional reflectance distribution function (BRDF) model was originally developed from the simplified scenarios of continuous and discrete vegetation canopies, and has been widely used to fit multiangle observations of vegetation-soil systems of the land surface in many fields. Although this model was not developed explicitly for snow surfaces, it can capture the geometric-optical effect caused by the shadowing of rugged or undulating snow surfaces. However, in this study, this model has been further developed to better characterize the scattering properties of snow surface, which can also exhibit strongly forward-scattering behavior. This study proposes a new snow kernel to characterize the reflectance anisotropy of pure snow based on the asymptotic radiative transfer (ART) model that assumes snow can be modeled as a semi-infinite, plane-parallel, weakly absorbing light scattering layer. This new snow kernel adopts a correction term with a free parameter α to correct the analytic form of the ART model that has been reported to underestimate observed snow reflectance in the forward-scattering direction in the principal plane (PP), particularly in cases of a large viewing zenith angle (> 60°). This snow kernel has now been implemented in the kernel-driven RTLSR BRDF model framework in conjunction with two additional kernels (i.e., the volumetric scattering kernel and geometric-optical scattering kernel) and is validated using observed and simulated multiangle data from three data sources. Pure snow targets were selected from the extensive archive of the Polarization and Directionality of the Earth's Reflectance (POLDER) BRDF data. Antarctic snow field measurements, which were taken from the top of a 32-m-tall tower at Dome C Station and include 6336 spectral bidirectional reflectance factors (BRFs), were also utilized. Finally, a set of simulated BRFs, generated by a hybrid scattering snow model that combines the geometric optics with vector radiative transfer theory, were used to further assess the proposed method. We first retrieve the value of the free parameter α for a comprehensive analysis using single multiangle snow data with a sufficient BRDF sampling. Then, we determine the optimally fixed value of the α parameter as prior information for potential users. The new snow kernel method is shown to be quite accurate, presenting a high correlation coefficient (R2 = ~0.9) and a negligible bias between the modeled BRFs and the various snow BRDF validation data. The finding demonstrates that this snow kernel provides an improved potential compared to that of the original kernel-driven model framework for a pure snow surface in many applications, particularly those involving the global water cycle and radiation budget, where snow cover plays an important role.
关键词： Kernel-driven model,POLDER BRDF data,Bidirectional reflectance distribution function (BRDF),Asymptotic radiative transfer (ART) model,Snow,Forward scattering,RTLSR model
更新于2025-09-09 09:28:46
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Radiometric Cross-Calibration of GF-4 PMS Sensor Based on Assimilation of Landsat-8 OLI Images
摘要： Earth observation data obtained from remote sensors must undergo radiometric calibration before use in quantitative applications. However, the large view angles of the panchromatic multispectral sensor (PMS) aboard the GF-4 satellite pose challenges for cross-calibration due to the effects of atmospheric radiation transfer and the bidirectional reflectance distribution function (BRDF). To address this problem, this paper introduces a novel cross-calibration method based on data assimilation considering cross-calibration as an optimal approximation problem. The GF-4 PMS was cross-calibrated with the well-calibrated Landsat-8 Operational Land Imager (OLI) as the reference sensor. In order to correct unequal bidirectional reflection effects, an adjustment factor for the BRDF was established, making complex models unnecessary. The proposed method employed the Shuffled Complex Evolution-University of Arizona (SCE-UA) algorithm to find the optimal calibration coefficients and BRDF adjustment factor through an iterative process. The validation results revealed a surface reflectance error of <5% for the new cross-calibration coefficients. The accuracy of calibration coefficients were significantly improved when compared to the officially published coefficients as well as those derived using conventional methods. The uncertainty produced by the proposed method was less than 7%, meeting the demands for future quantitative applications and research. This method is also applicable to other sensors with large view angles.
关键词： GF-4 PMS,cross-calibration,SCE-UA,data assimilation,Landsat-8 OLI,BRDF
更新于2025-09-09 09:28:46
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - BRDF Effect on the Estimation of Canopy Chlorophyll Content in Paddy Rice from UAV-Based Hyperspectral Imagery
摘要： The bidirectional reflectance distribution function (BRDF) effect due to the surface reflectance anisotropy and variations in the solar and viewing geometry has been studied in the remote sensing community for several decades, and most attention was paid to the satellite sensors with large field of view (FOV), such as MODIS with a 110° FOV. With the development of unmanned aerial vehicle (UAV) technique, the imagery acquired at UAV platform provides important information about crop growth status, which is a promising and efficient approach for precise agriculture. However, few studies explored the BRDF effect in UAV images, especially for the sensors with small FOVs. This study investigated the BRDF effect on the estimation of canopy chlorophyll content (CCC) with the UHD 185 hyperspectral imagery (27° FOV) acquired at a UAV platform. Our results from a rice field-plot experiment demonstrated that the CCC was highly correlated to the red-edge chlorophyll index derived at five different view angles. However, the regression models were significantly different among these view angles. This implied that no single CCC estimation model can be applied to the whole image for CCC mapping. The findings suggest the BRDF effect should be considered for providing reliable and consistent CCC estimation.
关键词： Chlorophyll content,BRDF,Hyperspectral imagery,Paddy rice
更新于2025-09-09 09:28:46
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Unmanned aerial system nadir reflectance and MODIS nadir?BRDF-adjusted surface reflectances intercompared?over?Greenland
摘要： Albedo is a fundamental parameter in earth sciences, and many analyses utilize the Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF)/albedo (MCD43) algorithms. While derivative albedo products have been evaluated over Greenland, we present a novel, direct comparison with nadir surface reflectance collected from an unmanned aerial system (UAS). The UAS was flown from Summit, Greenland, on 210 km transects coincident with the MODIS sensor overpass on board the Aqua and Terra satellites on 5 and 6 August 2010. Clear-sky acquisitions were available from the overpasses within 2 h of the UAS flights. The UAS was equipped with upward- and downward-looking spectrometers (300–920 nm) with a spectral resolution of 10 nm, allowing for direct integration into the MODIS bands 1, 3, and 4. The data provide a unique opportunity to directly compare UAS nadir reflectance with the MODIS nadir BRDF-adjusted surface reflectance (NBAR) products. The data show UAS measurements are slightly higher than the MODIS NBARs for all bands but agree within their stated uncertainties. Differences in variability are observed as expected due to different footprints of the platforms. The UAS data demonstrate potentially large sub-pixel variability of MODIS reflectance products and the potential to explore this variability using the UAS as a platform. It is also found that, even at the low elevations flown typically by a UAS, reflectance measurements may be influenced by haze if present at and/or below the flight altitude of the UAS. This impact could explain some differences between data from the two platforms and should be considered in any use of airborne platforms.
关键词： NBAR,UAS,Greenland,reflectance,BRDF,Albedo,MODIS
更新于2025-09-09 09:28:46
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Perceptually Validated Cross-Renderer Analytical BRDF Parameter Remapping
摘要： Material appearance of rendered objects depends on the underlying BRDF implementation used by rendering software packages. A lack of standards to exchange material parameters and data (between tools) means that artists in digital 3D prototyping and design, manually match the appearance of materials to a reference image. Since their effect on rendered output is often non-uniform and counter intuitive, selecting appropriate parameterisations for BRDF models is far from straightforward. We present a novel BRDF remapping technique, that automatically computes a mapping (BRDF Difference Probe) to match the appearance of a source material model to a target one. Through quantitative analysis, four user studies and psychometric scaling experiments, we validate our remapping framework and demonstrate that it yields a visually faithful remapping among analytical BRDFs. Most notably, our results show that even when the characteristics of the models are substantially different, such as in the case of a phenomenological model and a physically-based one, our remapped renderings are indistinguishable from the original source model.
关键词： BRDF model,Virtual Materials,Perceptual validation,Surface perception
更新于2025-09-09 09:28:46
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MatMix 1.0: Using optical mixing to probe visual material perception
摘要： MatMix 1.0 is a novel material probe we developed for quantitatively measuring visual perception of materials. We implemented optical mixing of four canonical scattering modes, represented by photographs, as the basis of the probe. In order to account for a wide range of materials, velvety and glittery (asperity and meso-facet scattering) were included besides the common matte and glossy modes (diffuse and forward scattering). To test the probe, we conducted matching experiments in which inexperienced observers were instructed to adjust the modes of the probe to match its material to that of a test stimulus. Observers were well able to handle the probe and match the perceived materials. Results were robust across individuals, across combinations of materials, and across lighting conditions. We conclude that the approach via canonical scattering modes and optical mixing works well, although the image basis of our probe still needs to be optimized. We argue that the approach is intuitive, since it combines key image characteristics in a "painterly" approach. We discuss these characteristics and how we will optimize their representations.
关键词： material probe,reflectance,BRDF,material perception,MatMix 1.0
更新于2025-09-04 15:30:14
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Improved Vegetation Profiles with GOCI Imagery Using Optimized BRDF Composite
摘要： The purpose of this study was to optimize a composite method for the Geostationary Ocean Color Imager (GOCI), which is the first geostationary ocean color sensor in the world. Before interpreting the sensitivity of each composite with ground measurements, we evaluated the accuracy of bidirectional reflectance distribution function (BRDF) performance by comparing modeled surface reflectance from BRDF simulation with GOCI-measured surface reflectance according to composite period. The root mean square error values for modeled and measured surface reflectance showed reasonable accuracy for all of composite days since each BRDF composite period includes at least seven cloud-free angular sampling for all BRDF performances. Also, GOCI-BRDF-adjusted NDVIs with four different composite periods were compared with field-observation NDVI and we interpreted the sensitivity of temporal crop dynamics of GOCI-BRDF-adjusted NDVIs. The results showed that vegetation index seasonal profiles appeared similar to vegetation growth curves in both field observations from crop scans and GOCI normalized difference vegetation index (NDVI) data. Finally, we showed that a 12-day composite period was optimal in terms of BRDF simulation accuracy, surface coverage, and real-time sensitivity.
关键词： bidirectional reflectance distribution function (BRDF),vegetation profiles,Geostationary Ocean Color Imager (GOCI),composite period,normalized difference vegetation index (NDVI)
更新于2025-09-04 15:30:14
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Quantifying the Reflectance Anisotropy Effect on Albedo Retrieval from Remotely Sensed Observations Using Archetypal BRDFs
摘要： The re?ectance anisotropy effect on albedo retrieval was evaluated using the Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional re?ectance distribution functions (BRDFs) product, and archetypal BRDFs. Shortwave-band archetypal BRDFs were established, and validated, based on the Anisotropy Flat indeX (AFX) and time series MODIS BRDF over tile h11v03. To generate surface albedo, archetypal BRDFs were used to ?t simulated re?ectance, based on the least squares method. Albedo was also retrieved based on the least root-mean-square-error (RMSE) method or normalized difference vegetation index (NDVI) based prior BRDF knowledge. The difference between those albedos and the MODIS albedo was used to quantify the re?ectance anisotropy effect. The albedo over tile h11v03 for day 185 in 2009 was retrieved from single directional re?ectance and the third archetypal BRDF. The results show that six archetypal BRDFs are suf?cient to represent the re?ectance anisotropy for albedo estimation. For the data used in this study, the relative uncertainty caused by re?ectance anisotropy can reach up to 7.4%, 16.2%, and 20.2% for suf?cient, insuf?cient multi-angular and single directional observations. The intermediate archetypal BRDFs may be used to improve the albedo retrieval accuracy from insuf?cient or single observations with a relative uncertainty range of 8–15%.
关键词： NDVI,AFX,single observation,archetypal BRDF,MODIS
更新于2025-09-04 15:30:14