Reflectance spectral characterization of acid sulphate soil in South Yunderup,Western Australia

Acid sulphate soils (ASS) are widely spread worldwide and are detrimental to the environment. South Yunderup is one of the coastal areas of Western Australia heavily affected by ASS. Conventional investigation is costly and time-consuming, and thus there is an urgent need to rapidly characterize and identify this type of soil. This paper aims to characterize these soils using reflectance spectra, which may be one of the most significant steps in effectively identifying them and mapping their extent by remote sensing. The ASS from the study area were divided into several groups and subtypes according to both pH measurements and mineral composition as identified by X-ray diffraction analysis. Each group and subtype was then characterized by its spectral reflectance features. We found that the spectral characteristics of ASS are governed by the spectral features of its compositional minerals. In particular, some secondary iron-bearing minerals produced by the formation of ASS, together with surrounding minerals such as carbonate, play vitally important roles in influencing the spectral characterization of ASS. These iron-bearing minerals, including iron oxides, hydroxides/oxyhydroxides (e.g. haematite, goethite, and ferrihydrite), and iron sulphates (e.g. jarosite and copiapite), have diagnostic spectral features and are therefore detectable in the reflectance range. Moreover, these secondary iron-bearing minerals could be indicators suggesting the pH conditions in which they formed. The results of this study include the overall mineral distribution of the study area, the spectral characterization of different groups and subtypes of ASS, and the linkages between spectral features and pH ranges.     

An in situ study of the effects of surface anisotropy on the remote sensing of burned savannah

This Letter presents field‐based evidence of the perturbing effects of surface anisotropy on the remote sensing of burned savannah. The analysis is based on bidirectional spectral reflectance data collected at different solar illumination angles and convolved to Moderate‐resolution Imaging Spectroradiometer (MODIS) reflective bands. Results from a grass savannah site show that burning reduces the anisotropy of the surface compared to its pre‐burn state. In contrast, at a shrub savannah site, burning reduces or increases surface anisotropy. Spectral indices defined from 1.240 µm and 2.130 µm reflectance, and 1.640 µm and 2.130 µm reflectance, provided stronger diurnal separation between burned and unburned areas than individual reflectance bands but do not eliminate anisotropic effects. The Normalized Difference Vegetation Index (NDVI) provides weak diurnal separation relative to these near‐ and mid‐infrared based indices. Implications of the findings are discussed for burned area mapping.     

Digital classification of the contact metamorphic aureole along the Los Pedroches batholith,south-central Spain,using Landsat Thematic Mapper data

Visible and near-infrared laboratory reflectance spectra of soils sampled over the southern contact metamorphic aureole of the Los Pedroches granodiorite north of Cordoba in the southern-central part of the Iberian Peninsula are characterized in terms of relative albedo, depth, width, asymmetry, and wavelength position of absorption features. A decrease in albedo and relative depth of the Al-OH absorption feature (near 2.2μm), the H₂0 feature (near 1.9μm), and the OH feature (near 1.4μm) is observed with distance to the contact metamorphic domain. This effect is attributed to spectra quenching related to the absorbing capacity of finely disseminated carbonaceous material in soils which opacity increases with increasing temperature related to metamor-phism. Fe⁺² and Fe⁺³ cause absorption features near l.0μm. 0.55μm, and 0.46 μm and also, a decrease of reflectivity in the 0.8-0.4μm wavelength region. These absorption features, however, are unaffected by the amount of carbonaceous material. Landsat-TM images were used for mapping variations in iron, water, and hydroxyl absorption features over the contact zone using ratio and normalized difTerence images with TM-3:1 for Fe and TM-5:7 for H₂0. TM-5 was added as blue component in a colour ratio component image mapping the effect of spectral quenching. Ratios enhanced the spectral variability between individual bands resulting in correlation coefficients of the order of (plus or minus) 0-2.     

Following a site-specific secondary succession in the Amazon using the Landsat CDR product and field inventory data

Secondary forests cover large areas and are strong carbon sinks in tropical regions. They are important for ecosystem functioning, biodiversity conservation, watershed protection, and recovery of soil fertility. In this study, we used the Surface Reflectance Climate Data Record (CDR) product from 16 Thematic Mapper (TM)/Landsat-5 images (1984–2010) to continuously track the secondary succession (SS) of a forest following land abandonment in 1980. Changes in canopy structure and floristic composition were analysed using data from four field inventories (1995, 2002, 2007, and 2012). To characterize variations in brightness, greenness, spectral reflectance, and shadows with the natural regeneration of vegetation, we applied tasselled cap transformations, principal component analysis (PCA), and linear spectral mixture models to the TM datasets. Shade fractions were plotted over time and correlated with the enhanced vegetation index (EVI) and the normalized difference vegetation index (NDVI). Because image texture may reflect the variability of the successional process, eight co-occurrence-based filter metrics were calculated for selected TM bands and plotted as a function of time since abandonment. The successional forest was compared to a nearby primary reference forest (PF) and had differences in the spectral and textural means evaluated using analysis of variance (ANOVA). The results showed increases of 35% and 10.4% over time in basal area and tree height, respectively. Species richness within the assemblage of sampling units increased from 14 to 71 between 1995 and 2012, and this trend was also confirmed using an individual-based rarefaction analysis. Species richness in 2012 was still lower than that observed in the PF site, which presented greater amounts of aboveground biomass (336.4 ± 17.0 ton ha^?1 for PF versus 98.5 ± 21.4 ton ha^?1 for SS in 2012). Brightness and greenness tasselled cap differences between the SS and PF rapidly decreased from 1984 (SS at the age of 4 years) to 1991 (age of 11 years). Brightness also decreased from 1997 to 2003, as indicated by PC1 scores and surface reflectance of the TM bands 4 (near infrared) and 5 (shortwave infrared). Spectral mixture shade fraction increased from young to old successional stages with strata composition and canopy structure development, whereas NDVI and EVI decreased over time. Because EVI was strongly dependent on near infrared reflectance (r = + 0.96), it was also much more strongly correlated with the shade fraction (r = ?0.93) than NDVI. Except for the image texture mean that decreased from young to old successional stages in TM bands 4 and 5, no clear trend was observed in the remaining texture metrics over the time period of vegetation regeneration. Overall, due to structural-floristic and spectral/textural differences with the PF, the SS site was still distinguishable using Landsat data 30 years after land abandonment. Most of the spectral metric means between PF and SS were significantly different over time at 0.01 significance level, as indicated by ANOVA.     

Spectral variability and bidirectional reflectance behaviour of urban materials at a 20 cm spatial resolution in the visible and near‐infrared wavelengths. A case study over Toulouse (France)

This letter presents an experiment carried out in Toulouse in May 2004 to study the spectral variability and bidirectional reflectance behaviour of urban materials. The measurements were carried out at a 20 cm spatial resolution in the visible and near‐infrared (350–2500 nm). These measurements allow quantification of three main types of reflectance spatial variability. In addition to these in situ experiments, the bidirectional properties of urban material samples were studied in the laboratory with a goniometer.     

An improved NDVI-based threshold method for estimating land surface emissivity using MODIS satellite data

This work estimated the land surface emissivities (LSEs) for MODIS thermal infrared channels 29 (8.4–8.7 μm), 31 (10.78–11.28 μm), and 32 (11.77–12.27 μm) using an improved normalized difference vegetation index (NDVI)-based threshold method. The channel LSEs are expressed as functions of atmospherically corrected reflectance from the MODIS visible and near-infrared channels with wavelengths ranging from 0.4 to 2.2 μm for bare soil. To retain the angular information, the vegetation LSEs were explicitly expressed in the NDVI function. The results exhibited a root mean square error (RMSE) among the estimated LSEs using the improved method, and those calculated using spectral data from Johns Hopkins University (JHU) are below 0.01 for channels 31 and 32. The MODIS land surface temperature/emissivity (LST/E) products, MOD11_L2 with LSE derived via the classification-based method with 1 km resolution and MOD11C1 with LSE retrieved via the day/night LST retrieval method at 0.05° resolution, were used to validate the proposed method. The resultant variances and entropies for the LSEs estimated using the proposed method were larger than those extracted from MOD11_L2, which indicates that the proposed method better described the spectral variation for different land covers. In addition, comparing the estimated LSEs to those from MOD11C1 yielded RMSEs of approximately 0.02 for the three channels; however, more than 70% of pixels exhibited LSE differences within 0.01 for channels 31 and 32, which indicates that the proposed method feasibly depicts LSE variation for different land covers.     

The role of atmospheric correction algorithms in the prediction of soil organic carbon from Hyperion data

In this study, the role of atmospheric correction algorithm in the prediction of soil organic carbon (SOC) from spaceborne hyperspectral sensor (Hyperion) visible near-infrared (vis-NIR, 400–2500 nm) data was analysed in fields located in two different geographical settings, viz. Karnataka in India and Narrabri in Australia. Atmospheric correction algorithms, (1) ATmospheric CORection (ATCOR), (2) Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH), (3) 6S, and (4) QUick Atmospheric Correction (QUAC), were employed for retrieving spectral reflectance from radiance image. The results showed that ATCOR corrected spectra coupled with partial least square regression prediction model, produced the best SOC prediction performances, irrespective of the study area. Comparing the results across study areas, Karnataka region gave lower prediction accuracy than Narrabri region. This may be explained due to difference in spatial arrangement of field conditions. A spectral similarity comparison of atmospherically corrected Hyperion spectra of soil samples with field-measured vis-NIR spectra was performed. Among the atmospheric correction algorithms, ATCOR corrected spectra found to capture the pattern in soil reflectance curve near 2200 nm. ATCOR’s finer spectral sampling distance in shortwave infrared wavelength region compared to other models may be the main reason for its better performance. This work would open up a great scope for accurate SOC mapping when future hyperspectral missions are realized.     

Characterization of a new system for space-resolved simultaneous in situ measurements of hydrocarbons and dissolved oxygen in microchannels

A space-resolved in situ measurement technique based on laser Raman spectroscopy with high detection sensitivity is described. This method allows the simultaneous detection of the concentrations of dissolved molecular oxygen and of hydrocarbons as well as oxidation products in organic liquids in a microchannel during reaction. It can be used as a new tool for detailed kinetic studies of liquid-phase reaction. Raman spectra are produced using an argon ion laser at 488 nm with a continuous optical power of 100 mW. This radiation is coupled into a microscope and a microchannel. The arising Raman stray light is detected with a spectrometer and a sensitive CCD camera. Special optics were used to collect as much light as possible on the CCD detector. This results in high signals and low noise levels. In order to demonstrate the usefulness of the system, cyclohexane oxidation by oxygen was investigated. In a feasibility study for the products of the cyclohexane oxidation, a limit of detection of 0.05 % m/m for cyclohexanol and 0.01 % m/m for cyclohexanone was achieved. Molecular oxygen dissolved in cyclohexane could be detected at the relevant concentration ranges for carrying out the oxidation of cyclohexane with a limit of detection of 0.01 % m/m. An optically transparent microchannel reactor was built, which can be used up to temperatures of 503 K and pressures of 8 MPa. With this reactor and the in situ measurement technique, space-resolved studies with a measuring volume of 5 μm × 5 μm × 38 μm can now be realized. The spectral selectivity and sensitivity of the measurement technique applied to cyclohexane oxidation, and the characteristics of the spatially resolved measurement technique are discussed.     

Potential signatures of heavy metal complexes in lichen reflectance spectra

Lichens are sensitive to atmospheric pollutants emitted from anthropogenic activities and are thus effective biomonitors. A variety of heavy metals, such as nickel (Ni), iron (Fe), lead (Pb), copper (Cu), and cadmium (Cd), can be emitted by metal smelters. The purpose of this study was twofold: (1) to measure the spectral reflectance properties (350–2500 nm) of expected heavy metal complexes in lichens (oxalates and sulphides); and (2) to determine whether these complexes contribute features to reflectance spectra of lichens from the vicinity of a heavy metal smelter. Some metal oxalate spectra are characterized by crystal field transition absorption bands in the 500–1300 nm region, which are specific to the particular metal cation they contain and its oxidation state. The 1900–2500 nm region exhibits multiple absorption bands attributable to the oxalate molecule. The metal sulphide reflectance spectra are characterized by generally low reflectance and few if any strong or diagnostic spectral features; those that are found can be related to a specific cation and its oxidation state. These spectra were used to determine whether reflectance spectra of a diverse suite of lichens collected downwind of a smelter showed spectral evidence indicative of heavy metal oxalates or sulphides. The lichen spectra, coupled with the oxalate and sulphide spectra and independently determined heavy metal concentration, failed to reveal spectral features that could be unambiguously related to heavy metal complexes. This was likely due to a number of causes: lichen reflectance spectra have absorption bands that overlap those of oxalates; oxalate and sulphide concentrations may have been too low to allow for their unambiguous identification, and lichen spectra are naturally diverse in the region below 1300 nm. There were no strong or significant linear trends between metal concentrations and distance from the smelter (coefficient of determination (R²) values <0.05), or between absorption band depths in the lichen spectra and distance from the smelter (R² values <0.06). This was likely due to the inclusion of multiple lichen species in the analysis, which may interact with airborne pollutants in different ways, and microenvironmental effects.     

Spectral characterization of the LANDSAT Thematic Mapper sensors

A summary of the spectral characteristics of the LANDSAT-4 and LANDSAT-5 Thematic Mapper instruments, the protoflight (TM/PF) and flight (TM/F) models, respectively, is presented. Data collected by the Hughes/Santa Barbara Research Center on the instruments and their components to determine compliance with the spectral coverage and spectral matching specifications served as the basis for the characterization. Compliance with the spectral coverage specifications (e.g. band locations) was determined by deriving band-by-band relative spectral response (RSR) curves from spectral measurements on the individual components contributing to the overall spectral response: filters, detectors and optical surfaces. The integrated system RSRs were not measured. The derived RSRs for the reflective bands were similar between TM/PF and the TM/F. The bandpasses between 50 per cent RSR points varied by only 2nm at most between the sensors and were: band 1, 452-518 nm; band 2, 528-609 nm; band 3, 625-693 nm; band 4, 776-904 nm; band 5, 1568-1784 nm and band 7, 2097-2348 nm. The upper-band edge of band 5 was outside the desired and specified range of 1750 ±20 nm; this implies that there will be more contribution from variable atmospheric water vapour absorption. In the emissive thermal band 6, the TM/PF and TM/F showed fundamentally different spectral responses. Though the lower band edges were both at approximately 104/mi, the TM/PF upper-band edge was detector limited at a temperature-dependent value of about 11·7μm, whereas the TM/F upper-band edge was filter limited at 12·4μm. Despite the TM/PF's band 6 narrow bandwidth, its radiometric performance exceeded requirements, so the band's narrowness was not a serious concern. Spectral matching measures the spectral differences between channels within a band by calibrating them all with one source and comparing their outputs to a spectrally different source. Satisfactory TM/PF spectral matching data were never obtained. TM/F channels were shown to have comparable or better spectral matching than past and existing MSS sensors.     

Assessing the sun glint effect on the data bias of CrIS shortwave surface channels near 3.7 μm

The Suomi National Polar-orbiting Partnership (NPP) satellite was successfully launched on 28 October 2011. The on-board Cross-track Infrared Sounder (CrIS) provides the hyperspectral infrared radiance covering a spectral range of 3.92–15.4 μm, inheriting the task to improve numerical weather prediction (NWP) from previous hyperspectral sounders. The so-called sun glint effect results in large biases in CrIS shortwave surface channels near 3.7 μm and therefore impedes the usage of those channels in the operational data assimilation, because the data biases are required to be evaluated appropriately by any data assimilation system. This work assesses the sun glint effect on bias characteristics of those shortwave surface channels near 3.7 μm, with the help of a sun glint model developed in the community radiative transfer model (CRTM). It is demonstrated that the daytime biases of those shortwave surface channels are decreased markedly after applying sun glint correction with values close to 0 K. The dependence of daytime biases on sensor zenith angles is also eliminated by using the sun glint model. It is seen that the differences between daytime and night-time biases can reach 0.6 K near mid-latitudes in the southern hemisphere after including the sun glint effect, which implies that the sun glint model needs further enhancement. Overall, the direct assimilation of CrIS shortwave surface channels near 3.7 μm is possibly accomplished by utilizing the sun glint model implemented in CRTM during both daytime and night-time.     

Spectroscopy of sediments in the Ganges-Brahmaputra delta: Spectral effects of moisture, grain size and lithology

The lithologic composition and grain size distribution of sediments are primary determinants of their inherent reflectance properties. However, moisture content is also known to have a strong influence on reflectances of soils and sediments. If the effects of sediment composition, grain size and moisture content could be distinguished spectrally, it might be possible to map these properties at synoptic scales using hyperspectral, or perhaps even broadband, remote sensing. Mapping the spatiotemporal distribution of sediment composition and moisture content could provide unique constraints on both the processes by which the sediments are deposited as well as the constraints they may impose on subsequent water flow and sediment transport. The Ganges-Brahmaputra delta (GBD) is formed by the convergence of these two great rivers and is superlative in both size and geologic activity. Sediment redistribution and channel migration associated with the annual floods disrupt the lives of hundreds of thousands of people living on the GBD but is also critical for maintaining the delta area fertile and above sea level. The 30+ year archive of Landsat imagery could provide a basis for spatiotemporal analysis of these fluvial dynamics if sediment properties could be inferred or measured from reflectance spectra. However, before confronting the challenge of broadband detection we must understand the spectral properties of the sediments under more controlled laboratory conditions. Bidirectional reflectance spectroscopy of 109 sediment samples from the GBD yields a spectral mixing space that appears to be structured by variations in moisture content, grain size and possibly lithology. Although the individual Empirical Orthogonal Functions of the Principal Components do not correspond to unique absorption features, clustering within the mixing space is clearly influenced by moisture content and grain size. Laboratory spectra of sediment reflectance measured under varying moisture content yield distinct trajectories through the spectral mixing space for different grain size distributions of sieved sediments. These variations in moisture content account for > 98% of spectral variance observed in these samples. Drying trajectories of coarse, fine and mixed sediments are distinct and suggest that moisture and grain size might be spectrally distinguishable. These results are consistent with Angstrom's hypothesis of moisture-driven spectral absorption but more controlled experiments are necessary to test the hypothesis rigorously.     

Mapping the degree of serpentinization within ultramafic rock bodies using imaging spectrometer data

In 0·4-2·5 μm reflectance spectra of serpentinized peridotites and synthetic olivine-serpentine-magnetite mineral mixtures, serpentinization is responsible for a decrease in contrast of olivine-pyroxene iron absorption features and an appearance and increase in OH^? absorption features near 1·4 μm and 2·3 μm. It is demonstrated that the degree of serpentinization is correlated positively with the depth of the 2·3 μm absorption feature, although small amounts of magnetite may obscure the spectral contrast and decrease the overall brightness of weakly serpentinized samples. This linear relationship is applied to map the degree of serpentinization from GER 63-channel imaging spectrometer data using the following methodology: (1) vegetation masking, (2) calculating the absorption band-depth of the 2·3 μm absorption feature, (3) translating this value into percentage serpentine-group minerals using an empirical linear model, and (4) estimating the degree of serpentinization at the remaining locations using conditional simulation techniques. Comparison or the results of the simulation with 49 field samples showed differences between + 33 per cent and ? 23 per cent serpentine-group minerals estimated.     

Spectral Angle Mapper and aeromagnetic data integration for gold-associated alteration zone mapping: a case study for the Central Eastern Desert Egypt

The Spectral Angle Mapper (SAM) classification technique is integrated with the surface structure and aeromagnetic data to map the potential gold mineralization sites associated within alteration zones in Central Eastern Desert (CED), Egypt. The surface reflectances of the Enhanced Thematic Mapper Plus (ETM+) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data were classified using the SAM classifier. Five spectral reflectance curves of the alteration minerals (haematite, illite, kaolinite, chlorite, and quartz) were utilized as end-members for the SAM classification. The surface lineation, and shear zone systems were delineated using ETM+ bands. The deep-seated faults were defined using the Euler deconvolution filter on the gridded aeromagnetic data. The magnetic data analysis inferred the subsurface structural depths range from 500 m to 2000 m. Geographic information system (GIS) overlaying operation was performed using the surface lineation and the subsurface faults layers to identify the structural continuity and to extract the possible migratory pathways of the hydrothermal solutions. Within Multiple Criteria Decision Analysis (MCDA), fuzzy membership operations were applied to identify the prospective alteration sites. The mapped results were compared with global positioning system (GPS) locations of existing alteration zones. The current proposed mapping method is considered a robust tool for decision-making and potential site selection technique for further mineral exploration in CED.     

Laboratory spectral calibration of TanSat and the influence of multiplex merging of pixels

This article first reviews the main characteristics of the High-Resolution Hyperspectral Sensor for carbon observation Grating Spectrometer (HRHS-GS) and discusses the impact of spectral resolution on gas absorption lines. The major content of this article is the laboratory calibration of HRHS-GS, the signal-to-noise ratio (SNR), instrument line shape (ILS), and the spectral resolution of each channel were achieved. The SNR results met the mission requirements for the 0.76 µm band, but missed the requirement for the two Carbon dioxide (CO₂) bands. To address this problem, the model ‘Multiplex Merging of Spectral Pixels’ was established to improve the SNR by increasing the incident energy of a single spectral channel. This process would lead to spectral broadening; the spectral resolution before and after that process was obtained. The transmittance spectra before and after multiplex merging were compared by the line-by-line radiative transfer model (LBLRTM) to analyse the impact of spectral broadening on gas absorption lines. Next, the results were verified by experiment with a gas absorption cell. The results showed that ‘Multiplex Merging of Spectral Pixels’ could effectively improve the SNR. For the 0.76 µm band, the transmittance spectra before and after multiplex merging were almost the same; for the 1.61 µm band, the peak value of the transmittance spectra decays by about 5%; and for the 2.06 µm band, the attenuation of the transmittance spectra is smaller than 3%. Meanwhile, the spectral resolution after spectral broadening still satisfied the study’s requirement.     

Correction of cirrus effects in Sentinel-2 type of imagery

Optical satellite images are often contaminated with cirrus clouds. Thin cirrus can be detected with a channel at 1.38 μm, and an established cirrus removal method exists for visible/near-infrared (VNIR) channels in atmospheric window regions, which was demonstrated with Moderate Resolution Imaging Spectrometer (MODIS) data. This contribution addresses open issues of cirrus correction for Sentinel-2 type of instruments, that is, future spaceborne sensors such as Sentinel-2 or similar instruments. These issues are (i) an extension of the existing technique to account for cirrus during the water vapour retrieval (channel at 0.94 μm) and surface reflectance calculation to avoid reflectance artefacts at 0.94 μm, (ii) a discussion of options concerning cirrus removal in the short-wave infrared (SWIR, channels at 1.6 and 2.2 μm) region and (iii) an analysis of channel parallax (view angle) requirements to achieve a high-quality cirrus removal.     

Using hyperspectral data to quantify water-quality parameters in the Wabash River and its tributaries,Indiana

A hand-held spectrometer was used to collect above-water spectral measurements for measuring optically active water-quality characteristics of the Wabash River and its tributaries in Indiana. Water sampling was undertaken concurrent with spectral measurements to estimate concentrations of chlorophyll (chl) and total suspended solids (TSS). A method for removing sky and Sun glint from field spectra for turbid inland waters was developed and tested. Empirical models were then developed using the corrected field spectra and in situ chl and TSS data. A subset of the field measurements was used for model development and the rest for model validation. Spectral characteristics indicative of waters dominated by different inherent optical properties (IOPs) were identified and used as the basis of selecting bands for empirical model development. It was found that the ratio of the reflectance peak at the red edge (704 nm) with the local minimum caused by chl absorption at 677 nm was a strong predictor of chl concentrations (coefficient of determination (R²) = 0.95). The reflectance peak at 704 nm was also a good predictor for TSS estimation (R² = 0.75). In addition, we also found that reflectance within the near-infrared (NIR) wavelengths (700–890 nm) all showed a strong correlation (0.85–0.91) with TSS concentrations and generated robust models. Results suggest that hyperspectral information provided by field spectrometer can be used to distinguish and quantify water-quality parameters under complex IOP conditions.     

Fast Spectral Reflectance Recovery Using DLP Projector

Spectral reflectance is an intrinsic characteristic of objects that is independent of illumination and the used imaging sensors. This direct representation of objects is useful for various computer vision tasks, such as color constancy and material discrimination. In this work, we present a novel system for spectral reflectance recovery with high temporal resolution by exploiting the unique color-forming mechanism of digital light processing (DLP) projectors. DLP projectors use color wheels, which are composed of a number of color segments and rotate quickly to produce the desired colors. Making effective use of this mechanism, we show that a DLP projector can be used as a light source with spectrally distinct illuminations when the appearance of a scene under the projector’s irradiation is captured with a high-speed camera. Based on the measurements, the spectral reflectance of scene points can be recovered using a linear approximation of the surface reflectance. Our imaging system is built from off-the-shelf devices, and is capable of taking multi-spectral measurements as fast as 100 Hz. We carefully evaluated the accuracy of our system and demonstrated its effectiveness by spectral relighting of static as well as dynamic scenes containing different objects.     

Semi-empirical approach for estimating broadband albedo of snow

Snow is a medium that exhibits highly anisotropic reflectance throughout the solar spectrum. The anisotropic nature of snow shows more variability in snow metamorphic processes for wavelengths beyond 1.0 μm than in the visible spectrum. This behavior poses challenges for the development of a model that can retrieve broadband albedo from reflectance measurements throughout the snow season. In this paper, a semi-empirical model is presented to estimate near infrared (0.8-2.5 μm) albedo of snow. This model estimates spectral albedo at a wavelength of 1.240 μm using only three variables: solar zenith angle, scattering angle and measured reflectance, which is used to retrieve near infrared albedo. To form a base for such a model, quantification of reflectance patterns and variability in varying snow condition, i.e. snow grain size, and sun-sensor geometry are prerequisite. In this study the DIScrete Ordinate Radiative Transfer (DISORT) model is used to simulate bi-directional reflectance. The performance of the developed model is evaluated by using DISORT simulated spectral albedo for various snow grain sizes and solar zenith angles, as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) and in-situ measurements. The developed model is shown to be capable of estimating spectral albedo at 1.240 μm with acceptable accuracy. The mean error (ME), mean absolute error (MAE), and root mean squared error (RMSE) in the estimates are found to be 0.053, 0.055 and 0.064, respectively, for a wide range of sun-sensor geometries and snow grain sizes. The model shows better accuracy for spectral albedo estimates than for those computed using the Lambertian reflectance assumption for snow, reducing the error in the range and standard deviation by 75% and 65%, respectively. Applying the model to MODIS, the retrieved albedo is found to be in good quantitative agreement (r = 0.82) with in-situ measurements. These improvements in albedo estimation should allow more accurate use of remote sensing measurements in climate and hydrological models.