The application of imaging spectrometry data to mapping alteration zones associated with gold mineralization in southern Spain

The gold mineralization at the Rodalquilar mine in southern Spain is of the acid-sulphate type. We have assessed the ability of AVIRIS imaging spectrometer data to detect the hydrothermal alteration mineralogy mapped using traditional ground-based techniques at Rodalquilar. Four methods of retrieving apparent surface reflectance have been evaluated, the empirical line method and three methods of radiative transfer modelling. This study indicates that radiative transfer modelling, using only atmospheric information derived from the imaging spectrometry data, can satisfactorily correct the atmospheric effects involved in retrieving apparent surface reflectance. The alteration at Rodalquilar is characterized by propylitic (vermiculite), illitic, kaolinitic (pyrophyllitic), alunitic and silicic zones with an increasing degree of alteration towards the formative hydrothermal cells in whose fossil cores the gold mineralization is found. However, several factors act against the usefulness of the AVIRIS data for mapping these mineral zones: the mine site is heavily disturbed with exposed workings, often of high albedo altered rocks, whilst unworked areas have partial iron-rich soil and dry vegetation cover; the alteration itself is highly discontinuous at the scale of 10 m and the shortwave infrared (SWIR) data where much of the diagnostic information for these hydrothermal minerals lies is very noisy. Nevertheless it has proved possible to map successfully, at the individual pixel level, the zones of gold-bearing alunitic alteration using the joint presence of alunite absorption features at 1480 and 1760 nm. The data from the 2000-2400 nm spectral range allow the areas with general absorption features centred around 2200 nm to be mapped but zonation based on individual minerals identification is not possible.     

Landsat8卫星影像大气校正及其植被指数与SEVI性能比较

遥感影像受大气的吸收散射以及地形起伏变化的影响,使得传感器接收到的辐射信号既包含了地物的信息,同时也包含了大气以及地形的信息。为了提高地表反射率的反演精度,需要去除遥感影像中大气和地形的影响。提出了一种基于查找表的Landsat8-OLI遥感影像的大气校正方法,该方法由6S辐射传输模型生成查找表,其中输入的参数包括大气水蒸汽含量、臭氧浓度和气溶胶光学厚度等MODIS大气参数产品。利用传统方法建立的大气参数查找表通常只考虑一部分因素,这对于以MODIS产品为输入参数的大气校正是不适用的。本文建立了一个包括大部分输入参数的高维大气校正查找表,对于Landsat-8 OLI传感器具有很高的通用性,通过进行光谱分析、与USGS地表反射率产品交叉验证等方式来验证模型的精度。验证结果表明该方法能有效地反演精确可靠的地表反射率。最后,采用目视解译、统计分析将校正结果与SEVI做对比分析,比较地形影响消减的效果。结果表明该模型与SEVI在地形消减的效果上作用相当。     

Landsat8卫星影像大气校正及其植被指数与SEVI性能比较

遥感影像受大气的吸收散射以及地形起伏变化的影响，使得传感器接收到的辐射信号既包含了地物的信息，同时也包含了大气以及地形的信息。为了提高地表反射率的反演精度，需要去除遥感影像中大气和地形的影响。提出了一种基于查找表的Landsat8-OLI遥感影像的大气校正方法，该方法由6S辐射传输模型生成查找表，其中输入的参数包括大气水蒸汽含量、臭氧浓度和气溶胶光学厚度等MODIS大气参数产品。利用传统方法建立的大气参数查找表通常只考虑一部分因素，这对于以MODIS产品为输入参数的大气校正是不适用的。本文建立了一个包括大部分输入参数的高维大气校正查找表，对于Landsat-8 OLI传感器具有很高的通用性，通过进行光谱分析、与USGS地表反射率产品交叉验证等方式来验证模型的精度。验证结果表明该方法能有效地反演精确可靠的地表反射率。最后，采用目视解译、统计分析将校正结果与SEVI做对比分析，比较地形影响消减的效果。结果表明该模型与SEVI在地形消减的效果上作用相当。     

An O2-A Band Atmospheric Correction Algorithm for Tower-based Platform based on Look-up Table

Tower-based spectral observation is an important connecting bridge between flux sites and satellite remote sensing data，and the effect of atmospheric absorption and scattering between horizontal surface and tower-based platform on the atmospheric absorption band such as O2-A is difficult to ignore.Firstly，the influence of atmospheric radiation transfer on the up-welling radiance and down-welling irradiance of the tower-based platform is analyzed，and the atmospheric correction method of based on upward and downward transmittance is established，that is，the influence of the upwelling radiance and down-welling irradiance is corrected by the direct transmittance and the total transmittance.Secondly，using the simulation data of MODTRAN model，the influence of AOD550 and radiative transfer path length on atmospheric transmittance is quantitatively analyzed，and the LUT of AOD550 is established based on the ratio of down-welling irradiance of near-infrared and red bands and solar zenith angle，as well as the upward and downward atmospheric transmittance LUT based on the AOD550 and the radiative transfer path length.Finally，using the canopy spectral data of different growth stages observed by the tower-based platform，the difference of the apparent reflectance between the inside and outside of the O₂-A band absorption line before and after atmospheric correction was analyzed.The results show that the atmospheric correction method based on LUT of AOD550 and radiative transfer path length proposed in this paper can better correct the influence of upwelling radiance and down-welling on the O₂-A absorption band of the tower-based platform，and provides important method support for applications such as SIF observation on the tower platform.     

Atmospheric correction of PROBA/CHRIS data in an urban environment

The Compact High Resolution Imaging Spectrometer (CHRIS) is an imaging spectrometer onboard the European Space Agency (ESA) Project for On-Board Autonomy (PROBA) satellite. However, it has been shown that CHRIS presents some miscalibration trends over the spectral region covered. This paper reports a practical procedure for the atmospheric correction of CHRIS images based on field recalibration in an urban environment. In the first stage, the spectra of surface targets are measured and used to simulate the spectral radiance at the top of the atmosphere (TOA) for each channel and to determine the recalibration coefficients of the CHRIS images. In the second stage, two methods for atmospheric correction are examined: the radiative transfer model (RTM) and the improved dark-object subtraction (IDOS) method. For comparison purposes, the empirical line method (ELM) is also evaluated. The accuracy assessment shows that the RTM with the Moderate Resolution Transmittance (MODTRAN) code provides the most accurate atmospheric correction for the multiangular CHRIS images when using the proposed procedure.     

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.     

Geo-atmospheric processing of airborne imaging spectrometry data. Part 2: Atmospheric/topographic correction

A method for the radiometric correction of wide field-of-view airborne imagery has been developed that accounts for the angular dependence of the path radiance and atmospheric transmittance functions to remove atmospheric and topographic effects. The first part of processing is the parametric geocoding of the scene to obtain a geocoded, orthorectified image and the view geometry (scan and azimuth angles) for each pixel as described in part 1 of this jointly submitted paper. The second part of the processing performs the combined atmospheric/ topographic correction. It uses a database of look-up tables of the atmospheric correction functions (path radiance, atmospheric transmittance, direct and diffuse solar flux) calculated with a radiative transfer code. Additionally, the terrain shape obtained from a digital elevation model is taken into account. The issues of the database size and accuracy requirements are critically discussed. The method supports all common types of imaging airborne optical instruments: panchromatic, multispectral and hyperspectral, including fore/aft tilt sensors covering the wavelength range 0.35-2.55 w m and 8-14 w m. The processor is designed and optimized for imaging spectrometer data. Examples of processing of hyperspectral imagery in flat and rugged terrain are presented. A comparison of ground reflectance measurements with surface reflectance spectra derived from airborne imagery demonstrates that an accuracy of 1-3% reflectance units can be achieved.     

Inspecting MIVIS capability to retrieve chemical–mineralogical information: evaluation and analysis of VNIR–SWIR data acquired on a volcanic area

This work is a contribution to the assessment of MIVIS (Multi-spectral Infrared and Visible Imaging Spectrometer) airborne imaging spectrometer capability in applications of surface characterization. The focus is on the visible and near-infrared–short wave infrared (VNIR–SWIR) spectral region, using a dataset acquired in 1994 on Vulcano Island (Italy), to retrieve chemical–mineralogical information on the altered deposits related to volcanic activity. The main processing steps include data quality evaluation in terms of signal-to-noise ratio, atmospheric and topographic corrections and spectral interpretation of the image. Estimation of surface reflectance is based on atmospheric modelling by MODTRAN3.5 and 6S radiative transfer codes. Representative MIVIS reflectance spectra of the main surface units are compared with spectra measured in the laboratory on field samples, and interpreted to characterize the mineralogy on the basis of their spectral features. A thematic map of the main alteration units is then produced by applying spectral mapping techniques to the surface reflectance image, using a set of channels selected on the basis of their data quality and image-derived end-member spectra.     

The identification of pseudo-invariant targets using ground field spectroscopy measurements intended for the removal of atmospheric effects from satellite imagery: a case study of the Limassol area in Cyprus

This study proposes five types of commonly located surfaces that were evaluated to be determined for use as pseudo-invariant targets (PITs) in order to apply the so-called ‘empirical-line’ atmospheric correction method. Spectroradiometric measurements were taken over wet and dry conditions to obtain the spectral signatures of the targets. From the acquired in situ spectroradiometric campaign, it was found that the proposed commonly found PITs (sandy, concrete and asphalt) are suitable non-variant targets. An accuracy assessment of the empirical-line atmospheric correction method using the five PITs was performed using other calibration targets and aerosol optical thickness (AOT) values from MICROTOPS hand-held sun photometers acquired simultaneously with the satellite overpass. The radiative transfer equation was used to determine AOT levels, using the reflectance values derived from the empirical-line method, in order to conduct an accuracy assessment with in situ AOT measurements. It was also shown that precipitation conditions should be considered when using non-variant targets in atmospheric correction methods.     

Radiation physics and modelling for off-nadir satellite-sensing of non-Lambertian surfaces

The primary objective of this paper is to provide a deeper understanding of the physics of satellite remote-sensing when off-nadir observations are considered. Emphasis is placed on the analysis and modelling of atmospheric effects and the radiative transfer of non-Lambertian surface reflectance characteristics from ground-level to satellite locations. We evaluate the relative importance of spectral, spatial, angular, and temporal reflectance characteristics for satellite-sensed identification of vegetation types in the visible and near-infrared wavelength regions. Highest identification value is attributed to angular reflectance signatures. Using radiative transfer calculations to evaluate the atmospheric effects on angular reflectance distributions of vegetation surfaces, we identify atmosphere-invariant angular reflectance features such as the “hot spot” and the “persistent valley”. A new atmospheric correction formalism for complete angular reflectance distributions is described. A sample calculation demonstrates that a highly non-Lambertian measured surface reflectance distribution can be retrieved from simulated satellite data in the visible and near infrared to within about 20% accuracy for almost all view directions up to 60° off-nadir. Thus the high value of angular surface reflectance characteristics (the “angular signature”) for satellite-sensed feature identification is confirmed, which provides a scientific basis for future off-nadir satellite observations.     

An atmospheric correction method for the automatic retrieval of surface reflectances from TM images

Most of the atmospheric correction methods proposed in the literature are not easily applicable in reaJ cases. The most sophisticated models frequently require inputs which are not commonly available, whilst traditional simple dark object subtraction techniques do not generally give real reflectance values. In the present work an atmospheric correction method applicable to Landsat-TM data is described, which requires only inputs that are commonly available and the presence in the imaged scenes of some dark surfaces in TM bands 1 (blue) and 3 (red). The method consists of an inversion algorithm based on a simplified radiative transfer model in which the characteristics of atmospheric aerosols are estimated by the use of the path radiance in two TM bands rather than a priori assumed. On the basis of this information, which is crucial for determining the atmospheric properties, the retrieval of real reflectances from TM images is possible. The method can be applied to all TM scenes in which some dark points can be realistically supposed to be present, which is particularly advantageous in retrospective studies. Several TM scenes taken from different landscapes and in different seasons were corrected using the model. The reflectance values found were tested against ground measurements and compared with data from the literature. The results show a substantial improvement in the accuracy of the reflectance estimates with respect to estimates without atmospheric correction. Given some care in the identification of dark values, the relative error in actual reflectance retrieval is always rather low (?10–20 per cent); this error can be considered acceptable for most practical applications.     

Correction of atmospheric effects of satellite remote sensing data (Landsat MSS-NOAA AVHRR) for surface canopy investigations

Abstract

A new correction method for atmospheric effects in Landsat-MSS and NOAA AVHRR data is presented which uses only the remotely-sensed multispectral data. The method is based on a new quasi-single-variable radiative transfer model, and as a first step we assumed that the surface is covered by vegetation. For Landsat-MSS data the method was developed for the tasseled cap indices using known empirical relationships among them. For NOAA AVHRR data ‘ cap-like’ indices and the average reflectance of the average canopy in the visible band known from Landsat-MSS data were used. The method was used in yield forecasting project in north-eastern part of Hungary and provided a significant enhancement in the quality of remotely sensed data.     

基于IDL的遥感影像大气与地形校正方法实现

介绍了利用交互式数据语言（Interactive Data Language,IDL）开发TM/ETM遥感影像大气与地形校正模型的详细过程,以2000年4月30日密云ETM影像为例,对大气与地形校正方法的有效性和实用性进行了验证。结果表明,该方法有效地消除了大气与地形影响,提高了地表反射率等地表参数的反演精度和数据质量,为进一步开展定量遥感研究提供了数据质量保障。     

Hybrid atmospheric correction algorithms and evaluation on VNIR/SWIR Hyperion satellite data for soil organic carbon prediction

ABSTRACT

Visible near-infrared and shortwave infrared data acquired by spaceborne sensors contain atmospheric noise, along with target reflectance that may affect its end applications, e.g. geological, vegetation, soil surface studies, etc. Several atmospheric correction algorithms have been already developed to remove unwanted atmospheric components of a spectral signature of Earth targets obtained from airborne/spaceborne hyperspectral image. In spite of this, choosing of an appropriate atmospheric correction algorithm is an ongoing research. In this study, two hybrid atmospheric correction (HAC) algorithms incorporating a modified empirical line (EL_m) method were proposed. The first HAC model (named HAC_1) combines (i) a radiative transfer (RT) model based on the concepts of RT equations, which uses real-time in situ atmospheric and climatic data, and (ii) an EL_m technique. The second one (named HAC_2) combines (i) the well-known ATmospheric CORrection (ATCOR) model and (ii) an EL_m technique. Both HAC algorithms and their component single atmospheric correction algorithms (ATCOR, RT, and EL_m) were applied to radiance data acquired by Hyperion satellite sensor over study sites in Australia. The performances of both HAC algorithms were analysed in two ways. First, the Hyperion reflectances obtained by five atmospheric correction algorithms were analysed and compared using spectral metrics. Second, the performance of each atmospheric correction algorithm was analysed for prediction of soil organic carbon (SOC) using Hyperion reflectances obtained from atmospheric correction algorithms. The prediction model of SOC was built using partial least square regression model. The results show that (i) both the hybrid models produce a good spectrum with lower Spectral Angle Mapper and Spectral Information Divergence values and (ii) both hybrid algorithms provided better SOC prediction accuracy, in terms of coefficient of determination (R²), residual prediction deviation (RPD), and ratio of performance to interquartile (RPIQ), with R² ≥ 0.75, RPD ≥ 2, and RPIQ ≥ 2.58 than single algorithms. HAC algorithms, developed using EL_m technique, may be recommended for atmospheric correction of Hyperion radiance data, when archived Hyperion reflectance data have to be used for SOC prediction mapping.     

MAIS图像大气订正及其在岩矿制图中的应用

：针对１９９５年９月１３日在内蒙大青山地区的一次ＭＡＩＳ航空遥感飞行试验,给出了一种以地面大气同步测量为前提、基于计算机查找表的大气订正方法。该方法具有简单、实用等特点,特别适合于像航空成像光谱遥感这样大数据量的图像定量信息获取。在可见、近红外光谱区（０．４～１．２μｍ）,该方法的订正精度约为８．５％（总误差）,即反射率在３％～５０％范围内时,反射率获取精度约为０．００２～０．０５反射率单位。利用大气订正后的ＭＡＩＳ反射率图像,得到了中粒钾长花岗岩、绿泥化片麻岩和灰岩这三种岩矿在该试验区的空间分布。与地面勘查结果比较表明,大气订正后的高光谱分辨率航空成像遥感数据（如ＭＡＩＳ）可用于干旱、半干旱地区的岩矿分布研究与制图。     

A comparison of empirical and neural network approaches for estimating corn and soybean leaf area index from Landsat ETM+ imagery

Plant foliage density expressed as leaf area index (LAI) is used in many ecological, meteorological, and agronomic models, and as a means of quantifying crop spatial variability for precision farming. LAI retrieval using spectral vegetation indices (SVI) from optical remotely sensed data usually requires site-specific calibration values from the surface or the use of within-scene image information without surface calibrations to invert radiative transfer models. An evaluation of LAI retrieval methods was conducted using (1) empirical methods employing the normalized difference vegetation index (NDVI) and a new SVI that uses green wavelength reflectance, (2) a scaled NDVI approach that uses no calibration measurements, and (3) a hybrid approach that uses a neural network (NN) and a radiative transfer model without site-specific calibration measurements. While research has shown that under a variety of conditions NDVI is not optimal for LAI retrieval, its continued use for remote sensing applications and in analysis seeking to develop improved parameter retrieval algorithms based on NDVI suggests its value as a “benchmark” or standard against which other methods can be compared. Landsat-7 ETM+ data for July 1 and July 8 from the Soil Moisture EXperiment 2002 (SMEX02) field campaign in the Walnut Creek watershed south of Ames, IA, were used for the analysis. Sun photometer data collected from a site within the watershed were used to atmospherically correct the imagery to surface reflectance. LAI validation measurements of corn and soybeans were collected close to the dates of the Landsat-7 overpasses. Comparable results were obtained with the empirical SVI methods and the scaled SVI method within each date. The hybrid method, although promising, did not account for as much of the variability as the SVI methods. Higher atmospheric optical depths for July 8 leading to surface reflectance errors are believed to have resulted in overall poorer performance for this date. Use of SVIs employing green wavelengths, improved method for the definition of image minimum and maximum clusters used by the scaled NDVI method, and further development of a soil reflectance index used by the hybrid NN approach are warranted. More importantly, the results demonstrate that reasonable LAI estimates are possible using optical remote sensing methods without in situ, site-specific calibration measurements.     

HJ-1A高光谱数据高效大气校正及应用潜力初探

环境与灾害监测预报小卫星于2009年3月30日开始正式交付使用,A星上搭载了我国自主研制的空间调制型干涉高光谱成像仪（HSI）,作为一种新型传感器,HSI数据的应用在我国还处于探索阶段。要充分发挥超光谱数据优势、进行有效的遥感应用,首先需要消除遥感成像过程中的大气影响,获得不同波段的地物真实反射辐射信息。通过使用FLAASH大气辐射传输模型对HSI数据进行大气校正,并与表观反射率进行对比分析,证明了校正后获得的地表光谱反射率的有效性。同时基于校正后得到的光谱反射率图像,进行改良型土壤调整植被指数（MSAVI）与叶面积指数（LAI）的反演,初步展现了HSI数据的实际应用效果。     

Quality assessment of several methods to recover surface reflectance using synthetic imaging spectroscopy data

A synthetic data spectral cube that represents at-sensor radiance data of AVIRIS was used to examine the accuracy of several methods to recover absolute surface reflectance data of terrestrial targets. Soil and vegetation targets, selected to represent the images of ground variation and their spectra, were retrieved using HATCH, Empirical Line (EL) and their hybrids methods. After a synthetic radiance data cube was generated, reflectance recovery was carried out and compared with the true (input) reflectance information. It was found that even under controlled and ideal conditions, the spectral recovery using HATCH code provided differences of up to 40%. The EL methods, using the two end-members that represent the scene reduced this difference to about 4%, and in some cases, even to 0.1% It was found that selecting the calibration targets over low water vapor content improved the results. Applying EL on radiance data provided a severe difference of more than 200% in areas located outside the calibration target water vapor zone. Only over similar water vapor zones were the EL methods found to reasonably recover the surface reflectance. Examining the spectral variability in the calibration targets showed that using of spectral features targets with relative spectral similarity is almost as effective as using spectrally featureless targets for the EL process. Applying EL, using external spectral information of possible known targets, revealed a relatively high difference, as compared to the true reflectance data. However, thematic analysis using a SAM classifier proved that even under non-ideal conditions, the EL correction can yield a reasonable spatial mapping capability relative to those obtained under real reflectance domains. It was concluded that EL must be run on reflectance data (generated from absolute based method) over low water vapor zones to provide the most precise reflectance information. Also, it was found that it is not mandatory to select calibration targets that are totally featureless or characterized by low or high albedo response.     

SEBASS hyperspectral thermal infrared data: surface emissivity measurement and mineral mapping

This study focuses on mapping surface minerals using a new hyperspectral thermal infrared (TIR) sensor: the spatially enhanced broadband array spectrograph system (SEBASS). SEBASS measures radiance in 128 contiguous spectral channels in the 7.5- to 13.5-μm region with a ground spatial resolution of 2 m. In September 1999, three SEBASS flight lines were acquired over Virginia City and Steamboat Springs, Nevada. At-sensor data were corrected for atmospheric effects using an empirical method that derives the atmospheric characteristics from the scene itself, rather than relying on a predicted model. The apparent surface radiance data were reduced to surface emissivity using an emissivity normalization technique to remove the effects of temperature. Mineral maps were created with a pixel classification routine based on matching instrument- and laboratory-measured emissivity spectra, similar to methods used for other hyperspectral data sets (e.g. AVIRIS). Linear mixtures of library spectra match SEBASS spectra reasonably well, and silicate and sulfate minerals mapped remotely, agree with the dominant minerals identified with laboratory X-ray powder diffraction and spectroscopic analyses of field samples. Though improvements in instrument calibration, atmospheric correction, and information extraction would improve the ability to map more pixels, these hyperspectral TIR data nevertheless show significant advancement over multispectral thermal imaging by mapping surface materials and lithologic units with subtle spectral differences in mineralogy.     

Evaluation of atmospheric correction to airborne hyperspectral data relying on radiative transfer concepts

Physically based atmospheric correction is one of the most important but also perilous radiometric corrections in remote-sensing imagery. The main objective of this work was to evaluate the efficiency of atmospheric correction algorithms, based not only on quantification of the changes induced but also on a step-by-step interpretation of the results, in association with the radiative transfer (RT) processes that occur in the atmosphere and on Earth. A four-level atmospheric correction scheme was applied to airborne hyperspectral visible/near-infrared (VNIR) imagery and the performance was evaluated. Each atmospheric correction level was more numerous than the previous following adjunctive assessment of the following parameters: (1) atmospheric influence, (2) the adjacency effect, (3) cast shadows, and (4) effects induced by the Earth’s surface reflectance anisotropy. Performance assessment showed that, even though a more complex atmospheric correction scheme resembles in greater detail the conditions under which the image acquisition was carried out, it is more sensitive to restrictions that arise from either the sensor’s characteristics or the algorithms and data used. Moreover, it was shown that evaluating atmospheric correction results using criteria based on RT concepts can considerably assist in the evaluation process.