Aspects of operational atmospheric correction of hyperspectral imagery

The large number of spectral bands of hyperspectral instruments and the time required for the calculation of atmospheric look-up tables and the reflectance image cube pose very challenging requirements on an operational processing facility. This contribution presents some aspects and suggestions to reduce the processing time. Essential components are a precalculated database with a reduced number of spectral bands, an interactive phase to determine the appropriate atmospheric parameters, and a choice between medium and high accuracy levels for the atmospheric correction. The medium accuracy levels work with look-up tables for a reduced number of spectral bands employing interpolation for the channels omitted in the look-up tables. The high accuracy level uses tables for all channels and includes the scan angle dependence of the atmospheric radiance and transmittance functions. These ideas were successfully implemented and tested during several airborne hyperspectral campaigns resulting in an estimated time saving of a factor 3-7. The deviations of field measured reflectance spectra and spectra retrieved from airborne HyMap imagery are in the range of 2-3% or better.     

SIERRA: A new approach to atmospheric and topographic corrections for hyperspectral imagery

In mountainous areas, slope and altitude variations modulate the airborne sensed hyperspectral radiance image. A new algorithm, SIERRA, has been developed for atmospheric, relief and BRDF corrections in order to extract the surface reflectance in the form of bi-hemispherical albedo that does not depend on solar incidence and observation angles. The forward modeling efforts focus on the estimation of diffuse irradiance and upwelling diffuse radiance, and on the formulation of BRDF effects. The inversion scheme consists of four steps, that go deeper and deeper into the phenomena's complexity.To validate the model, reflectance images are assessed from radiance images simulated with different radiative transfer codes or forward models: MODTRAN4 in the case of homogeneous and flat ground, AMARTIS and SIERRA forward models for heterogeneous and mountainous cases. The surface reflectance is retrieved with a 5% relative error under standard acquisition conditions.SIERRA is applied to HyMap data acquired over the hilly landscape near Calanas, Spain. The hypercube reflectances are compared with those obtained using ATCOR4 and COCHISE. The benefit of relief correction is clearly demonstrated.     

Extrapolation of the aerosol reflectance from the near-infrared to the visible: the single-scattering epsilon vs multiple-scattering epsilon method

In the atmospheric correction algorithm for Sea-viewing Wide Field-of-view Sensor, the effects of the spectral variation of the aerosol radiance contributions at the two near-infrared (NIR) bands are estimated directly from sensor-measured radiance. The aerosol effects at the NIR are then extrapolated into the visible through a process of aerosol model selection from evaluation of the NIR single-scattering epsilon value, which is defined as the ratio of the single-scattering aerosol reflectance between two NIR bands. The aerosol radiance contribution at the visible wavelengths is then removed. In this paper, a slightly different approach in the aerosol model selection and extrapolation, i.e. using the NIR multiple-scattering epsilon instead of the single-scattering epsilon, is examined. The NIR multiple-scattering epsilon is the ratio of the aerosol multiple-scattering reflectance between two NIR wavelengths. Simulations show that, in general, both methods give comparable results. Statistically, more than 95% of cases in the retrieved ocean colour spectrum are within required accuracy for both methods. For clear atmosphere, however, the results of the atmospheric correction using the single-scattering epsilon method usually performed slightly better than the multiple-scattering epsilon method. On the other hand, for the large aerosol optical thickness the multiple-scattering epsilon method has slightly better retrievals for the Tropospheric aerosols. Some detailed analyses and discussions are provided to explain differences in these two approaches for extrapolating and retrieving the aerosol effects in the visible.     

Mapping inland water carbon content with Landsat 8 data

Landsat 8 is the first Earth observation satellite with sufficient radiometric and spatial resolution to allow global mapping of lake CDOM and DOC (coloured dissolved organic matter and dissolved organic carbon, respectively) content. Landsat 8 is a multispectral sensor however, the number of potentially usable band ratios, or more sophisticated indices, is limited. In order to test the suitability of the ratio most commonly used in lake carbon content mapping, the green–red band ratio, we carried out fieldwork in Estonian and Brazilian lakes. Several atmospheric correction methods were also tested in order to use image data where the image-to-image variability due to illumination conditions would be minimal. None of the four atmospheric correction methods tested, produced reflectance spectra that matched well with in situ measured reflectance. Nevertheless, the green–red band ratio calculated from the reflectance data was in correlation with measured CDOM values. In situ data show that there is a strong correlation between CDOM and DOC concentrations in Estonian and Brazilian lakes. Thus, mapping the global CDOM and DOC content from Landsat 8 is plausible but more data from different parts of the world are needed before decisions can be made about the accuracy of such global estimation.     

Multi-temporal MODIS-Landsat data fusion for relative radiometric normalization, gap filling, and prediction of Landsat data

A semi-physical fusion approach that uses the MODIS BRDF/Albedo land surface characterization product and Landsat ETM+ data to predict ETM+ reflectance on the same, an antecedent, or subsequent date is presented. The method may be used for ETM+ cloud/cloud shadow and SLC-off gap filling and for relative radiometric normalization. It is demonstrated over three study sites, one in Africa and two in the U.S. (Oregon and Idaho) that were selected to encompass a range of land cover land use types and temporal variations in solar illumination, land cover, land use, and phenology. Specifically, the 30 m ETM+ spectral reflectance is predicted for a desired date as the product of observed ETM+ reflectance and the ratio of the 500 m surface reflectance modeled using the MODIS BRDF spectral model parameters and the sun-sensor geometry on the predicted and observed Landsat dates. The difference between the predicted and observed ETM+ reflectance (prediction residual) is compared with the difference between the ETM+ reflectance observed on the two dates (temporal residual) and with respect to the MODIS BRDF model parameter quality. For all three scenes, and all but the shortest wavelength band, the mean prediction residual is smaller than the mean temporal residual, by up to a factor of three. The accuracy is typically higher at ETM+ pixel locations where the MODIS BRDF model parameters are derived using the best quality inversions. The method is most accurate for the ETM+ near-infrared (NIR) band; mean NIR prediction residuals are 9%, 12% and 14% of the mean NIR scene reflectance of the African, Oregon and Idaho sites respectively. The developed fusion approach may be applied to any high spatial resolution satellite data, does not require any tuning parameters and so may be automated, is applied on a per-pixel basis and is unaffected by the presence of missing or contaminated neighboring Landsat pixels, accommodates for temporal variations due to surface changes (e.g., phenological, land cover/land use variations) observable at the 500 m MODIS BRDF/Albedo product resolution, and allows for future improvements through BRDF model refinement and error assessment.     

Spectral assessment of new ASTER SWIR surface reflectance data products for spectroscopic mapping of rocks and minerals

ASTER reflectance spectra from Cuprite, Nevada, and Mountain Pass, California, were compared to spectra of field samples and to ASTER-resampled AVIRIS reflectance data to determine spectral accuracy and spectroscopic mapping potential of two new ASTER SWIR reflectance datasets: RefL1b and AST_07XT. RefL1b is a new reflectance dataset produced for this study using ASTER Level 1B data, crosstalk correction, radiance correction factors, and concurrently acquired level 2 MODIS water vapor data. The AST_07XT data product, available from EDC and ERSDAC, incorporates crosstalk correction and non-concurrently acquired MODIS water vapor data for atmospheric correction. Spectral accuracy was determined using difference values which were compiled from ASTER band 5/6 and 9/8 ratios of AST_07XT or RefL1b data subtracted from similar ratios calculated for field sample and AVIRIS reflectance data. In addition, Spectral Analyst, a statistical program that utilizes a Spectral Feature Fitting algorithm, was used to quantitatively assess spectral accuracy of AST_07XT and RefL1b data.Spectral Analyst matched more minerals correctly and had higher scores for the RefL1b data than for AST_07XT data. The radiance correction factors used in the RefL1b data corrected a low band 5 reflectance anomaly observed in the AST_07XT and AST_07 data but also produced anomalously high band 5 reflectance in RefL1b spectra with strong band 5 absorption for minerals, such as alunite. Thus, the band 5 anomaly seen in the RefL1b data cannot be corrected using additional gain adjustments. In addition, the use of concurrent MODIS water vapor data in the atmospheric correction of the RefL1b data produced datasets that had lower band 9 reflectance anomalies than the AST_07XT data. Although assessment of spectral data suggests that RefL1b data are more consistent and spectrally more correct than AST_07XT data, the Spectral Analyst results indicate that spectral discrimination between some minerals, such as alunite and kaolinite, are still not possible unless additional spectral calibration using site specific spectral data are performed.     

Parametrized BRDF for atmospheric and topographic correction and albedo estimation in Jiangxi rugged terrain,China

A method is presented for bi‐directional reflectance distribution function (BRDF) parametrization for topographic correction and surface reflectance estimation from Landsat Thematic Mapper (TM) over rugged terrain. Following this reflectance, albedo is calculated accurately. BRDF is parametrized using a land‐cover map and Landsat TM to build a BRDF factor to remove the variation of relative solar incident angle and relative sensor viewing angle per pixel. Based on the BRDF factor and radiative transfer model, solar direct radiance correction, sky diffuse radiance and adjacent terrain reflected radiance correction were introduced into the atmospheric‐topographic correction method. Solar direct radiance, sky diffuse radiance and adjacent terrain reflected radiance, as well as atmospheric transmittance and path radiance, are analysed in detail and calculated per pixel using a look‐up table (LUT) with a digital elevation model (DEM). The method is applied to Landsat TM imagery that covers a rugged area in Jiangxi province, China. Results show that atmospheric and topographic correction based on BRDF gives better surface reflectance compared with sole atmospheric correction and two other useful atmospheric‐topographic correction methods. Finally, surface albedo is calculated based on this topography‐corrected reflectance and shows a reasonable accuracy in albedo estimation.     

Evaluation of apparent surface reflectance estimation methodologies

The estimation of apparent surface reflectance values from imaging spectroscopy data requires a correction for the efTects of the intervening atmosphere. Four methods of estimating apparent surface reflectance have been evaluated, the empirical line method and three methods of radiative transfer modelling. To compare the results of these correction methodologies two high albedo targets, of identified composition, were selected. The empirical line method was found to be sensitive to errors in locating and spectral variations within the ground survey targets and also target height differences. The radiative transfer modelling techniques gave relatively similar results, reasonably close to the library spectra. This study indicates that radiative transfer modelling using only atmospheric information derived from the imaging spectroscopy data, while still not as sensitive as correction methods using additional ground and atmospheric information, can satisfactorily correct the atmospheric elfects involved in estimating apparent surface reflectance, allowing the identification of the major diagnostic absorption features.     

Classification of Australian forest communities using aerial photography, CASI and HyMap data

Within Australia, the discrimination and mapping of forest communities has traditionally been undertaken at the stand scale using stereo aerial photography. Focusing on mixed species forests in central south-east Queensland, this paper outlines an approach for the generation of tree species maps at the tree crown/cluster level using 1 m spatial resolution Compact Airborne Spectrographic Imager (CASI; 445.8 nm–837.7 nm wavelength) and the use of these to generate stand-level assessments of community composition. Following automated delineation of tree crowns/crown clusters, spectral reflectance from pixels representing maxima or mean-lit averages of channel reflectance or band ratios were extracted for a range of species including Acacia, Angophora, Callitris and Eucalyptus. Based on stepwise discriminant analysis, classification accuracies of dominant species were greatest (87% and 76% for training and testing datasets; n = 398) when the mean-lit spectra associated with a ratio of the reflectance (ρ) at 742 nm (ρ₇₄₂) and 714 nm (ρ₇₁₄) were used. The integration of 2.6 m HyMap (446.1 nm–2477.8 nm) spectra increased the accuracy of classification for some species, largely because of the inclusion of shortwave infrared wavebands. Similar increases in accuracy were achieved when classifications of field spectra resampled to CASI and HyMap wavebands were compared. The discriminant functions were applied subsequently to classify crowns within each image and produce maps of tree species distributions which were equivalent or better than those generated through aerial photograph interpretation. The research provides a new approach to tree species mapping, although some a priori knowledge of the occurrence of broad species groups is required. The tree maps have application to biodiversity assessment in Australian forests.     

海岸带高光谱遥感与近海高光谱成像仪(HICO)

应海岸带监测需求,高光谱成像仪开始在海岸带监测中发挥重要作用。搭载于国际空间站上的HICO(Hyperspectral Imager for the Coastal Ocean)是第一颗针对近岸海洋遥感的高光谱成像仪,其波谱范围为360～1 080 nm,光谱分辨率为5 nm。介绍了HICO数据的基本情况,并与在轨星载高光谱成像仪EO-1 Hyperion和HJ-1A HSI基本参数做了对比。同时针对高浑浊水体,以黄河三角洲近岸3种典型地物为例,结合FLAASH大气校正模型,提取了辐亮度和地表反射率,初步对比分析了HICO和HSI的光谱性能。结果表明HICO能更好地反映近岸地物的光谱特征。     

Atmospheric correction of ENVISAT/MERIS data over case II waters: the use of black pixel assumption in oxygen and water vapour absorption bands

The Medium Resolution Imaging Spectrometer (MERIS) sensor, with its good physical design, can provide excellent data for water colour monitoring. However, owing to the shortage of shortwave-infrared (SWIR) bands, the traditional near-infrared (NIR)–SWIR algorithm for atmospheric correction in inland turbid case II waters cannot be extended to the MERIS data directly, which limits its applications. In this study, we developed a modified NIR black pixel method for atmospheric correction of MERIS data in inland turbid case II waters. In the new method, two special NIR bands provided by MERIS data, an oxygen absorption band (O₂ A-band, 761 nm) and a water vapour absorption band (vapour A-band, 900 nm), were introduced to keep the assumption of zero water-leaving reflectance valid according to the fact that both atmospheric transmittance and water-leaving reflectance are very small at these two bands. After addressing the aerosol wavelength dependence for the cases of single- and multiple-scattering conditions, we further validated the new method in two case lakes (Lake Dianchi in China and Lake Kasumigaura in Japan) by comparing the results with in situ measurements and other atmospheric correction algorithms, including Self-Contained Atmospheric Parameters Estimation for MERIS data (SCAPE-M) and the Basic ERS (European Remote Sensing Satellite) & ENVISAT (Environmental Satellite) (A)ATSR ((Advanced) Along-Track Scanning Radiometer) and MERIS (BEAM) processor. We found that the proposed method had acceptable accuracy in the bands within 560–754 nm (MERIS bands 5–10) (average absolute deviation (AAD) = 0.0081, average deviation (AD) = 0.0074), which are commonly used in the estimation models of chlorophyll-a (chl-a) concentrations. In addition, the performance of the new method was superior to that of the BEAM processor and only slightly worse than that of SCAPE-M in these bands. Considering its acceptable accuracy and simplicity both in principle and at implementation compared with the SCAPE-M method, the new method provides an option for atmospheric correction of MERIS data in inland turbid case II waters with applications aiming for chl-a estimation.     

Separating a color signal into illumination and surface reflectancecomponents: theory and applications

A separation algorithm for achieving color constancy and theorems concerning its accuracy are presented. The algorithm requires extra information, over and above the usual three values mapping human cone responses, from the optical system. However, with this additional information-specifically, a sampling across the visible range of the reflected, color-signal spectrum impinging on the optical sensor-the authors are able to separate the illumination spectrum from the surface reflectance spectrum contained in the color-signal spectrum which is, of course, the product of these two spectra. At the heart of the separation algorithm is a general statistical method for finding the best illumination and reflectance spectra, within a space represented by finite-dimensional linear models of statistically typical spectra, whose product closely corresponds to the spectrum of the actual color signal. Using this method, the authors are able to increase the dimensionality of the finite-dimensional linear model for surfaces to a realistic value. One method of generating the spectral samples required for the separation algorithm is to use the chromatic aberration effects of a lens. An example of this is given. The accuracy achieved in a large range of tests is detailed, and it is shown that agreement with actual surface reflectance is excellent     

An optimization approach to estimate and calibrate column water vapour for hyperspectral airborne data

The article describes a novel approach to estimate and calibrate column water vapour (CWV), a key parameter for atmospheric correction of remote-sensing data. CWV is spatially and temporally variable, and image-based methods are used for its inference. This inference, however, is affected by methodological and numeric limitations, which likely propagate to reflectance estimates. In this article, a method is proposed to estimate CWV iteratively from target surface reflectances. The method is free from assumptions for at sensor radiance-based CWV estimation methods. We consider two cases: (a) CWV is incorrectly estimated in a processing chain and (b) CWV is not estimated in a processing chain. To solve (a) we use the incorrect estimations as initial values to the proposed method during calibration. In (b), CWV is estimated without initial information. Next, we combined the two scenarios, resulting in a generic method to calibrate and estimate CWV. We utilized the hyperspectral mapper (HyMap) and airborne prism experiment (APEX) instruments for the synthetic and real data experiments, respectively. Noise levels were added to the synthetic data to simulate real imaging conditions. The real data used in this research are cloud-free scenes acquired from the airborne campaigns. For performance assessment, we compared the proposed method with two state-of-the-art methods. Our method performed better as it minimizes the absolute error close to zero, only within 8–10 iterations. It thus suits existing operational chains where the number of iterations is considerable. Finally, the method is simple to implement and can be extended to address other atmospheric trace gases.     

Quantitative relationships of near-surface spectra to Landsat radiometric data

The aim of our research has been to determine the quantitative relationship between the surface spectral character of a variety of geologic terrains and that sensed by the Landsat multispectral scanner. A spectral sampling and measurement program was conducted to accurately characterize the surface spectral reflectance of the Landsat resolution element and, for the first time, to establish statistically the degree of sampling required for a variety of natural terrains. Results from the study showed that for typical homogeneous and moderately heterogeneous terrains, the number of samples required to estimate the mean reflectance of a pixel is small. Only 9–20 samples are required to be within 2% reflectance at the 95% probability level. Coincident field measurements and satellite observations were used to test the equivalency and correlation of the reflectance data. Before the Landsat data could be compared with the surface measurements the satellite brightness values must be converted to absolute radiometric units, and corrected for atmospheric attenuation and scattering. A conversion method using a standard/target comparison, which indirectly compensated for atmospheric attenuation and scattering, produced a Landsat equivalent reflectance that exhibited a root-mean-square error of ± 4% reflectance, when compared with the surface measured value at 12 test sites. Although the equivalence of the surface and satellite data cannot be shown to be better than 4% reflectance, statistical study indicates that the surface and satellite data are highly correlated within defined contrast constraints. However, this correlation is present only after the satellite brightness values are corrected for between band gain differences and compensation is made for atmospheric attenuation and scattering.     

The derivation of water volume reflectances from airborne MSS data using in situ water volume reflectances,and a combined optimization technique and radiative transfer model

Abstract

Water volume reflectance images of three water cooling reservoirs were derived from airborne Daedalus DS-1260 multispectral scanner (MSS) data using a radiative transfer model to eliminate atmospheric effects and to derive downwell-ing irradiances. Sixty in situ water volume reflectances and the associated sensor and sun geometries were input into the radiative transfer model. Using the radiative transfer model to generate water volume reflectance values at each field site, an optimization procedure minimized the difference between modelled and in situ water volume reflectances resulting in optimized sensor brightness value to radiance conversion gain and bias factors, and optimized surface visual range and mean terrain background reflectance. Subsequently water volume reflectance images were derived at six wavelengths encompassing the blue to near-infrared using the optimized atmospheric parameters and conversion factors as inputs into the radiative transfer model. Modelled reflectance images were evaluated for accuracy by statistical comparison to the in situ reflectances, and for improved contrast by subjective comparison to the original images. Daedalus DS-1260 MSS bands 3, 4, 5, 7 and 8 modelled reflectances explained 19, 78, 86, 89 and 82 per cent, respectively of the in situ reflectance variances, while band 2 correlation was not significant (p<0.05). All generated reflectance image histograms showed dramatic improvement in contrast when compared with the histograms depicting variance within the original images.     

松花湖水体叶绿素a含量与反射光谱特征关系初探

根据2008年7月在松花湖实测的水体反射光谱及实验室分析得到的叶绿素浓度数据,对松花湖水体反射光谱特征与叶绿素浓度之间的关系进行探讨与分析。研究结果表明:水体叶绿素浓度与各波长点处反射率相关性均较好,并选择700 nm处反射率建立单波段模型。而700 nm和677 nm波长处反射率比值、685 nm处光谱一阶微分、700 nm波长处波峰几何特征具有较好的相关性,给出了松花湖水体叶绿素浓度估算模型,为松花湖水体叶绿素浓度反演监测提供了一定的理论基础与参考。     

Aerosol optical depth retrieval over snow using AATSR data

Aerosol observations over the Arctic are important because of the effects of aerosols on Arctic climate, such as their direct and indirect effects on the Earth's radiation balance and on snow albedo. Although information on aerosol properties is available from ground-based measurements, passive remote sensing using satellite measurements would offer the advantage of large spatial coverage with good temporal resolution, even though, due to light limitations, this is only available during the Arctic summer. However, aerosol optical depth (AOD) retrieval over the Arctic region is a great challenge due to the high reflectance of snow and ice and due to the high solar zenith angle. In this article, we describe a retrieval algorithm using Advanced Along-Track Scanning Radiometer (AATSR) data, a radiometer flying on the European Space Agency (ESA) Environmental Satellite (ENVISAT), which offers two views (near nadir and at 55° forward) at seven wavelengths in the visible thermal-infrared (VIS-TIR). The main idea of the Dual-View Multi-Spectral (DVMS) approach is to use the dual view to separate contributions to reflectance measured at the top of the atmosphere (TOA) due to atmospheric aerosol and the underlying surface. The algorithm uses an analytical snow bidirectional reflectance distribution function (BRDF) model for the estimation of the ratio of snow reflectances in the nadir and forward views, as well as an estimate of the atmospheric contribution to TOA reflectance obtained using the dark pixel method over the adjacent ocean surface, assuming that this value applies over nearby land surfaces in the absence of significant sources across the coastline. An iteration involving all four AATSR wavebands in the visible near-infrared (VIS-NIR) is used to retrieve the relevant information. The method is illustrated for AATSR overpasses over Greenland with clear sky in April 2009. Comparison of the retrieved AOD with AErosol Robotic Network (AERONET) data shows a correlation coefficient of 0.75. The AODs retrieved from AATSR using the DVMS approach and those obtained from AERONET data show similar temporal trends, but the AERONET results are more variable and the highest AOD values are mostly missed by the DVMS approach. Limitations of the DVMS method are discussed. The pure-snow BRDF model needs further correction in order to obtain a better estimation for mixtures of snow and ice.     

Atmospheric correction of high-spatial-resolution satellite images with adjacency effects: application to EO-1 ALI data

Adjacency effects are an interesting physical phenomenon caused by multiple scattering between the atmosphere and the surface. It is necessary to remove adjacency effects in the surface reflectance retrieved from satellite data at a high spatial resolution. In this study, we propose an atmospheric correction method with adjacency effect correction to derive surface reflectance from Earth Observing-1 (EO-1) Advanced Land Imager (ALI) data. Adjacency effects are corrected using an atmospheric point spread function. An analytical expression of the atmospheric point spread function is presented based on a single scattering approximation. This method was applied to ALI imagery acquired through Watershed Airborne Telemetry Experimental Research (WATER) on 20 May 2008. Compared with the surface reflectance before the adjacency effects were corrected for, the surface reflectance after correction exhibited increased between-pixel contrast. Furthermore, the discrepancies between the surface reflectance before and after corrections decreased from the blue band to the shortwave infrared band.     

Mapping lithology of the Sarfartoq carbonatite complex, southern West Greenland, using HyMap imaging spectrometer data

The Sarfartoq carbonatite complex occurs in the southern West Greenland in a transition zone between Archaean gneiss complex to the south and a Proterozoic mobile belt to the north. The Sarfartoq carbonatite complex consists of a core zone composed of dolomite carbonatite and minor søvite (calcite carbonatite) surrounded by a fenite zone and a marginal zone of gneisses frequently altered due to hydrothermal activity. High spatial and spectral resolution imaging spectrometer data recorded by the HyMap imaging system were used to map lithology of the Sarfartoq carbonatite complex. A careful analysis of the spectral reflectance properties of the carbonatite lithology preceded the HyMap data analysis stage. The spectral reflectance measurements showed that the various lithologic units including dolomite carbonatite, søvite, fenite and the marginal alteration zone have distinct spectral reflectance characteristics. The analysis of the HyMap data was based on an unsupervised clustering algorithm, the Self Organizing Maps (SOM), for the mapping of the main lithology and a hierarchical tree for the mapping of sparsely occurring søvite rocks. Spectral mixture analysis was applied to map fractional abundances and compare with the SOM results. The resulting lithological map shows the spatial distribution of dolomite carbonatite, søvite, fenite with abundant carbonatite dykes (representing the outer core of the carbonatite complex), fenite and hematized gneiss (marginal alteration zone). The results compare well with the field data collected for the assessment of the mapping accuracy and due to the spatially contiguous nature of the hyperspectral data could be used to better map the outcropping carbonatite lithology. The spectral reflectance measurements and the mapping results provide information of petrological importance for the carbonatite core zone.     

Comparison of multi-temporal ASTER images for hydrothermal alteration mapping using a fractal-aided SAM method

The shortwave infrared (SWIR) spectral bands of four multi-temporal images acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on NASA’s Terra platform were analysed for evaluating the effects of acquisition properties and atmospheric pre-processing levels on the resulting hydrothermal alteration maps a using the fractal-aided Spectral Angle Mapper (SAM) method. Three ASTER level-1B products covering the Sar Cheshmeh area in Iran were used for hydrothermal alteration mapping. These images were converted to surface reflectance using the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) method. The low reflectance of band 5 of the level-1B products was compensated for by using the spectra of collected rock samples. Level-2 (AST2B05S) SWIR ASTER images that had already been processed were also used. Reference spectra of the main hydrothermal alteration types were extracted for each product. The threshold angles were determined using the real value–area (RV–A) fractal technique. Then, SAM classification was carried out to map hydrothermal alteration for every product. It is concluded that the level-1B products that had been converted to reflectances have a better spectral contrast than the AST2B05S product. Summer images with lower tilt angle and higher solar elevation should be used to increase the accuracy of the image classification and minimize the effect of vegetation on the spectra of index minerals. By comparing the resulting hydrothermal alteration maps with known alteration types using a confusion matrix, it was shown that the application of the RV–A fractal technique to produce less biased threshold angles increases the accuracy of SAM classification.