Assessment of biases in MODIS surface reflectance due to Lambertian approximation

Using MODIS data and the AERONET-based Surface Reflectance Validation Network (ASRVN), this work studies errors of MODIS atmospheric correction caused by the Lambertian approximation. On one hand, this approximation greatly simplifies the radiative transfer model, reduces the size of the look-up tables, and makes operational algorithm faster. On the other hand, uncompensated atmospheric scattering caused by Lambertian model systematically biases the results. For example, for a typical bowl-shaped bidirectional reflectance distribution function (BRDF), the derived reflectance is underestimated at high solar or view zenith angles, where BRDF is high, and is overestimated at low zenith angles where BRDF is low. The magnitude of biases grows with the amount of scattering in the atmosphere, i.e., at shorter wavelengths and at higher aerosol concentration. The slope of regression of Lambertian surface reflectance vs. ASRVN bidirectional reflectance factor (BRF) is about 0.85 in the red and 0.6 in the green bands. This error propagates into the MODIS BRDF/albedo algorithm, slightly reducing the magnitude of overall reflectance and anisotropy of BRDF. This results in a small negative bias of spectral surface albedo. An assessment for the GSFC (Greenbelt, USA) validation site shows the albedo reduction by 0.004 in the near infrared, 0.005 in the red, and 0.008 in the green MODIS bands.     

Generating vegetation leaf area index earth system data record from multiple sensors. Part 1: Theory

The generation of multi-decade long Earth System Data Records (ESDRs) of Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) from remote sensing measurements of multiple sensors is key to monitoring long-term changes in vegetation due to natural and anthropogenic influences. Challenges in developing such ESDRs include problems in remote sensing science (modeling of variability in global vegetation, scaling, atmospheric correction) and sensor hardware (differences in spatial resolution, spectral bands, calibration, and information content). In this paper, we develop a physically based approach for deriving LAI and FPAR products from the Advanced Very High Resolution Radiometer (AVHRR) data that are of comparable quality to the Moderate resolution Imaging Spectroradiometer (MODIS) LAI and FPAR products, thus realizing the objective of producing a long (multi-decadal) time series of these products. The approach is based on the radiative transfer theory of canopy spectral invariants which facilitates parameterization of the canopy spectral bidirectional reflectance factor (BRF). The methodology permits decoupling of the structural and radiometric components and obeys the energy conservation law. The approach is applicable to any optical sensor, however, it requires selection of sensor-specific values of configurable parameters, namely, the single scattering albedo and data uncertainty. According to the theory of spectral invariants, the single scattering albedo is a function of the spatial scale, and thus, accounts for the variation in BRF with sensor spatial resolution. Likewise, the single scattering albedo accounts for the variation in spectral BRF with sensor bandwidths. The second adjustable parameter is data uncertainty, which accounts for varying information content of the remote sensing measurements, i.e., Normalized Difference Vegetation Index (NDVI, low information content), vs. spectral BRF (higher information content). Implementation of this approach indicates good consistency in LAI values retrieved from NDVI (AVHRR-mode) and spectral BRF (MODIS-mode). Specific details of the implementation and evaluation of the derived products are detailed in the second part of this two-paper series.     

The MODIS (Collection V005) BRDF/albedo product: Assessment of spatial representativeness over forested landscapes

A new methodology for establishing the spatial representativeness of tower albedo measurements that are routinely used in validation of satellite retrievals from global land surface albedo and reflectance anisotropy products is presented. This method brings together knowledge of the intrinsic biophysical properties of a measurement site, and the surrounding landscape to produce a number of geostatistical attributes that describe the overall variability, spatial extent, strength of the spatial correlation, and spatial structure of surface albedo patterns at separate seasonal periods throughout the year. Variogram functions extracted from Enhanced Thematic Mapper Plus (ETM+) retrievals of surface albedo using multiple spatial and temporal thresholds were used to assess the degree to which a given point (tower) measurement is able to capture the intrinsic variability of the immediate landscape extending to a satellite pixel. A validation scheme was implemented over a wide range of forested landscapes, looking at both deciduous and coniferous sites, from tropical to boreal ecosystems. The experiment focused on comparisons between tower measurements of surface albedo acquired at local solar noon and matching retrievals from the MODerate Resolution Imaging Spectroradiometer (MODIS) (Collection V005) Bidirectional Reflectance Distribution Function (BRDF)/albedo algorithm. Assessments over a select group of field stations with comparable landscape features and daily retrieval scenarios further demonstrate the ability of this technique to identify measurement sites that contain the intrinsic spatial and seasonal features of surface albedo over sufficiently large enough footprints for use in modeling and remote sensing studies. This approach, therefore, improves our understanding of product uncertainty both in terms of the representativeness of the field data and its relationship to the larger satellite pixel.     

A new spectrogoniophotometer to measure leaf spectral and directional optical properties

In this paper we present a new spectrogoniophotometer (SGP) dedicated to the assessment of plant leaf bidirectional optical properties. It consists of a mechanical apparatus coupled with an imaging spectrometer using a bidimensional CCD photodetector. Unpolarized light fluxes are sampled at high spectral and directional resolution to provide biconical reflectance and transmittance factors, every nanometer from 500 nm to 880 nm and at 800 source-sensor configurations (four illumination directions by 200 viewing directions covering the whole sphere). From these calibrated measurements we derive the leaf Bidirectional Reflectance and Transmittance Distribution Functions (BRDF and BTDF). The angular-integrated quantities defined as the Directional Hemispherical Reflectance and Transmittance Function (DHRF and DHTF) are also calculated. The first three sections emphasize the instrumental and calibration issues, as well as the radiometric definitions. In the last section we present some experimental results acquired on various monocot and dicot leaves with special attention to surface reflection. The shape, position and magnitude of the specular lobe, which is a characteristic of many leaves in the forward direction, is investigated for beech (Fagus sylvatica L.) and laurel (Prunus laurocerasus L.) using a leaf BRDF model. The width of the specular peak is very variable according to the species and the illumination angle, as well as its contribution to the directional-hemispherical reflectance. Finally, implications in plant physiology or remote sensing are broached.     

AERONET-based surface reflectance validation network (ASRVN) data evaluation: Case study for railroad valley calibration site

The AERONET-based Surface Reflectance Validation Network (ASRVN) is an operational processing system developed for validation of satellite derived surface reflectance products at regional and global scales. The ASRVN receives 50 × 50 km² subsets of MODIS data centered at AERONET sites along with AERONET aerosol and water vapor data, and performs an atmospheric correction. The ASRVN produces surface bidirectional reflectance factor (BRF), albedo, parameters of the Ross-Thick Li-Sparse (RTLS) BRF model, as well as Hemispherical-Directional Reflectance Factor (HDRF), which is required for comparison with the ground-based measurements. This paper presents a comparison of ASRVN HDRF with the ground-based HDRF measurements collected during 2001-2008 over a bright calibration Railroad Valley, Nevada site as part of the MODIS land validation program. The ground measurements were conducted by the Remote Sensing Group (RSG) at the University of Arizona using an ASD spectrometer. The study reveals a good agreement between ASRVN and RSG HDRF for both MODIS Terra and Aqua with rmse ~ 0.01-0.025 in the 500 m MODIS land bands B1-B7. Obtained rmse is below uncertainties due to the spatial and seasonal variability of the bright calibration 1 km² area. While two MODIS instruments have a similar rmse in the visible bands, MODIS Aqua has a better agreement (lower rmse) with the ground data than MODIS Terra at wavelengths 0.87-2.1 μm. An independent overall good agreement of two MODIS instruments with the ground data indicates that the relative calibration of MODIS Terra and Aqua at medium-to-bright reflectance levels for the stated time period is significantly better than uncertainties of the ASRVN and ground data.     

Inferring hemispherical reflectance of the earth's surface for global energy budgets from remotely sensed nadir or directional radiance values

The importance of the hemispherical reflectance (albedo) of terrestrial surfaces to biospheric and atmospheric processes is briefly reviewed. It is proposed that satellite-borne instruments represent the only practical means of obtaining global estimates of surface albedo data at reasonable time resolution, the problem being how to relate the nadir or directional reflectance observations obtained from such sensors to the integrated hemispherical reflectance. This paper discusses results measured at ground level in which NOAA satellite 7/8 AVHRR data, Bands 1 (0.58–0.68 μm) and 2 (0.73–1.1 μm), were used to investigate 1) the relationships between directional reflectances (spanning the entire reflecting hemisphere) and hemispherical reflectance (albedo) and 2) the effect of solar zenith angle and cover type on these relationships. Eleven natural vegetation surfaces ranging from bare soils to dense vegetation canopies were considered in the study. The results show that errors in inferring hemispherical reflectance from nadir reflectance can be as high as 45% for all cover types and solar zenith angles. By choosing a time of observation such that the solar zenith angle is between 30 and 40° the same error is reduced to less than 20% in both bands. For both bands a view angle of 60° off-nadir and ±90° from the solar azimuth reduces this error to less than 11% for all sun angles and cover types. A technique using two specific view angles reduces this error to less than 6% for both bands and for all sun angles and cover types. These techniques may yield considerable dividends in terms of more reliable estimation of hemispherical reflectance of natural surfaces.     

Validation of MISR land surface broadband albedo

Land surface broadband albedo is a critical variable for many scientific applications. Due to the scarcity of spectral albedo measurements of the Earth's surface environments, it is useful to construct broadband albedo from spectral albedo data obtained by multi‐angle satellite observations. The Multi‐angle Imaging SpectroRadiometer (MISR) onboard NASA's Earth Observing System (EOS) Terra satellite provides land surface albedo products from multi‐angular observations; however, the products have not been comprehensively validated. We convert MISR spectral albedos to total shortwave albedos and validate them using ground measurements at different validation sites. For most surface types, a published narrowband to broadband conversion formula was used, but a new conversion formula for snow and ice covered sites is developed in this study where the spectral range of the instrument is different. Several comparisons are made: (1) between MISR directional‐hemispherical reflectance (DHR) or albedo and MODIS (Moderate Resolution Imaging Spectroradiometer) DHR; and (2) between MISR spectral DHR and bi‐hemispherical reflectance (BHR). The results show that: (1) both the value and the temporal trends of the MISR shortwave albedo and the ground measured shortwave albedo are in good agreement, with the exception of the snow and ice sites; (2) the MISR DHR conforms well to MODIS DHR; and (3) the values of MISR DHR and BHR are nearly identical.     

Variability in surface BRDF at different spatial scales (30 m-500 m) over a mixed agricultural landscape as retrieved from airborne and satellite spectral measurements

Over the past decade, the role of multiangle remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities impacted by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained ~ 1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75° off-nadir, and at spatial resolutions ranging from 3 m to 500 m. This unique dataset was used to examine the interaction of the spatial and angular characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a land cover type-specific a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertainties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.     

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。     

TM遥感影像的地形辐射校正研究

从地面所接收到的太阳直接辐射、天空散射辐射和临近地形反射附加的辐射三个方面分析计算地面每个像元的太阳总辐射,并在此基础上建立地表真实反射率恢复模型,实现对地形的辐射校正。在算法实现上,采用交互式数据语言（Interactive Data Language,IDL）,结合6S大气校正模型和数字高程模型（DEM）进行编程实现。利用北京山区的TM遥感影像所做的实验表明该方法能有效地消除卫星影像中地形的影响,为影像的后续处理提供更真实的信息。     

基于地面定标技术的地物光谱反演方法研究

阐述了利用地面光谱定标和实验室遥感仪器定标技术和遥感方程对成像光谱遥感数据进行反射率反演的理论基础、技术方案及操作规范。结合航空遥感飞行试验,对成像光谱遥感数据进行了地物反射率反演,并讨论分析了该方法的可行性条件。研究结果表明:(1)该方法简便、实用、可行;(2)地面定标点的选择及光谱测量精度是影响反射率反演准确性的主要因素;(3)遥感器的几何参量、遥感数据获取的时间跨度、地形因子及二向反射因素是造成反射率反演误差的重要原因,在实际应用中也应加以重视。     

卫星遥感影像数据的地形影响校正

地形影响校正是遥感影像辐射校正的主要内容，是获得地表真实反射率的必不可少的一步。本文提出的方法中，将6S大气校正模型与数字高程模型（DEM）结合起来，计算出水平地面上接收到的直接辐射与漫射辐射，并采用一个简单公式将其转化到地形坡面上，从而实现了对地面的辐射能量校正，同时，6S模型对卫片还进行了大气改正，可输出卫片在大气层底部的辐射亮度与反射率；然后将基于坡面的反射率换算到其在水平面上的对应值，即实现了对反射率的地形影响校正。在我们所实施的“滇金丝猴保护项目”的植被研究中，应用本方法对梅里雪山区域的ETM＋影像进行了校正，大大减小了地形对遥感数据的附加影响。     

Prior knowledge-based retrieval and validation of information from remote-sensing data at various scales

This is the preface to the special issue on the use of prior knowledge for quantitative remote sensing and validation of results from quantitative remote sensing at different spatial scales. Quantitative remote sensing is the inverse problem of retrieval of geophysical and biophysical parameters using remote-sensing data. This is usually a non-linear ill-posed problem. To overcome the ill-posed problems of retrieval, prior knowledge is normally used. Validation is a general scientific issue for the remote-sensing community. Frequent validation of remote-sensing products is necessary to ensure their quality and accuracy. This special issue includes articles on in situ measurements from a field campaign, the accuracy and precision of calibration, validation methods, and evaluation of remote-sensing quantitative retrieval information modelling. Because of the insufficient study of the validation of quantitative remote-sensing products and the lack of validation theories and practical methods, in particular, a scaling theory for heterogeneous land surface variables, further applications of remote-sensing data and products are limited.     

La Crau: A European test site for remote sensing validation

Well characterized reference sites are of major importance for the calibration of remote sensors and the validation of retrieval algorithms. A 0.4 km square zone of 'La Crau', an arid area in the South of France, is well established for the calibration of SPOT HRV sensors, and has been regularly used for a variety of remote sensing campaigns. This study reports an investigation of the potential use of a more extended area of La Crau as a validation site for lower spatial resolution satellite sensors. Sample Bidirectional Reflectance Distribution Function (BRDF) measurements were acquired over a large part of the area of La Crau during a 3-week period in July 1995. The data were analysed to provide a detailed spectral characterization of the surface of La Crau and its temporal, directional and spatial variability. The results were used to simulate the three optical channels and the 1.6 mu m channel of the ATSR-2 sensor and compared with ATSR-2 image data from the site.     

Assessing the coupling between surface albedo derived from MODIS and the fraction of diffuse skylight over spatially-characterized landscapes

In this effort, the MODerate Resolution Imaging Spectroradiometer (MODIS) (Collection V005) Bidirectional Reflectance Distribution Function (BRDF)/Albedo algorithm is used to retrieve instantaneous surface albedo at a point in time and under specific atmospheric conditions. These retrievals are then used to study the role that the fraction of diffuse skylight plays under realistic scenarios of anisotropic diffuse illumination and multiple scattering between the surface and atmosphere. Simulations of the sky radiance using the MODTRAN®5.1 radiative transfer model were performed under different aerosol optical properties, illumination conditions, and surface characteristics to describe these effects on surface albedo retrievals from MODIS. This technique was examined using a validation scheme over four measurement sites with varied aerosol levels and landscapes, ranging from croplands to tundra ecosystems, and over extended time periods. Furthermore, a series of geostatistical analyses were performed to examine the types of spatial patterns observed at each measurement site. In particular, Enhanced Thematic Mapper Plus (ETM+) retrievals of surface albedo were acquired to analyze the change in variogram model parameters as a function of increased window-size. Results were then used to assess the degree to which a given point measurement is able to capture the intrinsic variability at the scale of MODIS observations. Assessments of MODIS instantaneous albedos that account for anisotropic multiple scattering, over snow-free and snow-covered lands and at all diurnal solar zenith angles, show a slight improvement over the albedo formulations that treat the downwelling diffuse radiation as isotropic. Comparisons with field measurements show biases improving by 0.004-0.013 absolute units (root-mean-squared error) or 0.1%-2.0% relative error.     

An Albedo Downscaling Method based on Stratified Linear Regression

In recent years,remote sensing technology has been widely used in the field of surface energy,thermal environment,and climate research in small and medium-sized regions.The demand for high resolution,high precision albedo products has increased.In view of this,a physical-based downscaling method is proposed for efficiently and accurately generating high-resolution albedo results.First,under the Lambert hypothesis,the primary albedo of Landsat 8 could be obtained based on Landsat 8 reflectance at 30m resolution.On the 500 m scale,it is found that after classification,the primary albedo of Landsat 8 has a better correlation with the broad-band albedo of MODIS MCD43A3 product.Therefore,a linear regression function based on surface classification is established to integrate the high-resolution primary albedo of Landsat 8 with high-precision MCD43A3 albedo to obtain downscaled albedo.Compared to MODIS albedo,the downscaled albedo provided more rich details.Verification experience based on SURFRAD observation data shows that Bias of the albedo downscaling is 0.01,and standard deviation is 0.012,which has good adaptability for different surface categories.It shows that the algorithm has great application value for producing high-resolution albedo products.     

不同辐射校正水平下水稻植被指数监测对比分析

归一化植被指数(NDVI)是反映植被长势特征的重要参数之一。获取准确的植被指数对揭示植被长势变化等定量遥感分析至关重要。基于不同辐射校正水平(辐射定标与大气校正),分别利用Landsat ETM+影像的灰度值(DN)、表观(TOA)反射率与地表(Surface)反射率计算相应NDVI,并根据鄱阳湖区野外定点观测数据,从农田、景观尺度揭示不同辐射校正水平下水稻生育期内NDVI动态变化特征。结果表明,根据DN、TOA反射率与Surface反射率提取的NDVI基本上可以反映出年内水稻不同熟制种植信息变化特征,即移栽期NDVI处于谷值,孕穗抽穗期NDVI达到峰值。但相应NDVI逐渐增加,且波动范围逐渐增大。就不同熟制水稻生育期而言,根据DN值计算并构建的NDVI曲线差异较小,而根据TOA反射率与Surface反射率反演的NDVI曲线差异明显。在植被定量遥感研究中,通过大气校正反演地表反射率计算植被指数相对客观准确。     

冰雪反照率测量和反演及其应用研究进展

总结了反照率的相关概念和2种主要的测量方法,分析了诸如雪粒径、含水量、烟尘、雪密度、雪深、太阳天顶角、大气状况和新降雪等因素对反照率的影响,介绍了遥感反演反照率通用的基本方法步骤,包括辐射校正、大气校正、各向异性校正和窄带转宽带反照率。最后阐述了反照率的研究动态和研究应用,如地表能量平衡、冰雪面积制图、确定雪粒径和反演雪线等。     

基于地表参数真实性的GF-1和SPOT-7多光谱影像质量评价

目的 遥感影像中地表信息表达真实程度决定了影像信息提取和定量化应用水平,传统的从像素灰度和视觉特性角度的影像质量评价方法难以评价影像对地表信息表达能力,本文从地表反射率和NDVI（normalized difference vegetation index）两种地表参数真实性角度评价GF-1和SPOT-7多光谱影像质量。方法 提出了一种基于地表参数真实性的多光谱影像质量评价方法,完成GF-1和SPOT-7卫星对实验区同步成像,地面同步测量大气光学特性和典型地物样区光谱,获取同步观测数据并对多光谱影像进行辐射误差处理,计算地物样区在影像上的反射率和NDVI,通过与地面实测光谱数据比较分析了地表参数真实性,评价GF-1和SPOT-7多光谱影像质量。结果 人工靶标中GF-1影像在4个波段反射率误差均在5%内,精度优于SPOT-7;植被地物中SPOT-7影像在蓝绿红波段反射率误差在4%内,近红外波段误差在15%内,NDVI误差在16%内,反射率和NDVI精度均优于GF-1;硬地地物中GF-1影像在4个波段反射率误差在6%内,精度优于SPOT-7;评价结果表明SPOT-7多光谱影像对植被类地物光谱表达真实度更高,GF-1对硬地类地物光谱表达真实度更高。结论 提出的基于地表参数真实性的遥感影像质量评价方法,能够有效地从地物光谱信息表达精度的角度评价影像质量。     

Atmospheric correction of ENVISAT/MERIS data over inland waters: Validation for European lakes

Traditional methods for aerosol retrieval and atmospheric correction of remote sensing data over water surfaces are based on the assumption of zero water reflectance in the near-infrared. Another type of approach which is becoming very popular in atmospheric correction over water is based on the simultaneous retrieval of atmospheric and water parameters through the inversion of coupled atmospheric and bio-optical water models. Both types of approaches may lead to substantial errors over optically-complex water bodies, such as case II waters, in which a wide range of temporal and spatial variations in the concentration of water constituents is expected. This causes the water reflectance in the near-infrared to be non-negligible, and that the water reflectance response under extreme values of the water constituents cannot be described by the assumed bio-optical models. As an alternative to these methods, the SCAPE-M atmospheric processor is proposed in this paper for the automatic atmospheric correction of ENVISAT/MERIS data over inland waters. A-priori assumptions on the water composition and its spectral response are avoided by SCAPE-M by calculating reflectance of close-to-land water pixels through spatial extension of atmospheric parameters derived over neighboring land pixels. This approach is supported by the results obtained from the validation of SCAPE-M over a number of European inland water validation sites which is presented in this work. MERIS-derived aerosol optical thickness, water reflectance and water pigments are compared to in-situ data acquired concurrently to MERIS images in 20 validation match-ups. SCAPE-M has also been compared to specific processors designed for the retrieval of lake water constituents from MERIS data. The performance of SCAPE-M to reproduce ground-based measurements under a range of water types and the ability of MERIS data to monitor chlorophyll-a and phycocyanin pigments using semiempirical algorithms after SCAPE-M processing are discussed. It has been found that SCAPE-M is able to provide high accurate water reflectance over turbid waters, outperforming models based on site-specific bio-optical models, although problems of SCAPE-M to cope with clear waters in some cases have also been identified.