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.     

A multiple dataset approach for 30-m resolution land cover mapping: a case study of continental Africa

Recent developments in global land-cover mapping have focused on spatial resolution improvement with more heterogeneous features to integrate spatial, spectral and temporal information. In this study, hundreds of features derived from four seasonal Landsat 8 OLI (Operational Land Imager) spectral bands, Moderate Resolution Imaging Spectroradiometer (MODIS) time series vegetation index (VI) data, night-time light (NTL), digital elevation models (DEM) and climatic variables were used for land cover mapping with a target 30-m resolution for the whole African continent. In total, 49,007 training samples (from 11,231 locations) and 23,803 validation samples (from 5,414 locations) interpreted from seasonal Landsat, MODIS Normalized Difference Vegetation Index (NDVI) time series and high-resolution images in Google Earth were used for classifier training (Random Forest) and map validation. Overall accuracy was 76% at 30-m spatial resolution, which is better than previous land cover mapping for the African continent. Besides, accuracies for cropland were improved dramatically by more than 10%. Our method also addressed many remaining issues for 30-m mapping (e.g. boundary effects and declines in resolution). This framework is promising for automatic and efficient global land cover mapping resulting in better visual effects and classification accuracy.     

Quantitative study of net radiation from MODIS data in the lower boundary layer in Poyang Lake area of Jiangxi Province,China

This paper focuses on quantitative calculation of longwave radiation and shortwave radiation from MODIS data in the Poyang Lake area of Jiangxi Province, China. The sum of the net longwave radiation and the shortwave radiation is the net radiation. These parameters are critical for the study of energy exchange in the lower boundary layer on land surface. Two of the most important factors for the retrieval of longwave radiation are the land surface temperature and emissivity. In this paper, the land surface temperature and emissivity were calculated from MODIS data using the regional self‐iterative split‐window method. The most important factor in the determination of the shortwave radiation is Earth surface albedo. The spectral reflectance and surface albedo were derived from MODIS data using the Synergy of TERRA and AQUA MODIS data (SYNTAM) algorithm. The net shortwave and longwave radiation were calculated and compared with the in situ measurement data. Our results indicate that the methods for quantitative calculation of net longwave radiation, shortwave radiation and net radiation from MODIS data can have a good accuracy. The relative errors are between 2.1% to 9.72% for longwave radiation, 0.15% to 10.48% for shortwave radiation and 0.64% to 13.7% for net radiation. We can conclude that a good accuracy can be achieved for deriving longwave radiation, shortwave radiation and net radiation, which are helpful for heat exchange, environmental, hydrology and ecology research in land areas.     

Boosted decision tree classifications of land cover over Turkey integrating MODIS,climate and topographic data

This study investigates the impact of using different combinations of Moderate Resolution Imaging Spectroradiometer (MODIS) and ancillary datasets on overall and per-class classification accuracies for nine land cover types modified from the classification system of the International Geosphere Biosphere Programme (IGBP). Twelve land cover maps were generated for Turkey using boosted decision trees (BDTs) based on the stepwise addition of 14 explanatory variables derived from a time series of 16-day MODIS composites between 2000 and 2006 (Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and four spectral bands) and ancillary climate and topographic data (minimum and maximum air temperature, precipitation, potential evapotranspiration, aspect, elevation, distance to sea and slope) at 500-m resolution. Evaluation of the 12 BDTs indicated that the BDT built as a function of all the MODIS and climate variables, aspect and elevation produced the highest degree of overall classification accuracy (79.8%) and kappa statistic (0.76) followed by the BDTs that additionally included distance to sea (DtS), and both DtS and slope. Based on an independent validation dataset derived from a pre-existing national forest map and Landsat images of Turkey, the highest overall accuracy (64.7%) and kappa coefficient (0.58) among the 12 land cover maps was achieved by using MODIS-derived NDVI time series only, followed by NDVI and EVI time series combined; NDVI, EVI and four MODIS spectral bands; and the combination of all MODIS and climate data, aspect, elevation and distance to sea, respectively. The largest improvements in producer's accuracies were observed for grasslands (+50%), barrenlands (+46%) and mixed forests (+39%) and in user's accuracies for grasslands (+53%), shrublands (+30%) and mixed forests (+28%), in relation to the lowest producer's accuracy. The results of this study indicate that BDTs can increase the accuracy of land cover classifications at the national scale.     

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.     

Narrowband to broadband conversions of land surface albedo: II. Validation

In the first paper of this series, we developed narrowband to broadband albedo conversion formulae for a series of sensors. These formulae were determined based on extensive radiative transfer simulations under different surface and atmospheric conditions. However, it is important to validate the simulation results using independent measurement data. In this paper, the validation results for three broadband albedos (total-shortwave, -visible and -near-IR albedos) using ground measurement of several cover types on five different days at Beltsville, MD are presented. Results show that the conversion formulae in the previous paper are very accurate and the average residual standard errors of the resulting broadband albedos for most sensors are around 0.02, which meets the required accuracy for land surface modeling.     

Validation of Narrow-band Surface Albedo Retrieved from FY-3C MERSI Satellite Data

Surface albedo is one of the driving factors in surface radiant energy balance and surface-atmosphere interaction.It is widely used in surface energy balance, medium and long-term weather forecasting and global change research.This study aims to validate the surface albedo retrieved from FY-3C MERSI. This paper selected four regions in Africa and North America as study areas to validate the retrieved albedo from the reflectance data and angle data of FY-3C MERSI at 250 m resolution in 2014. The semi-empirical kernel-driven BRDF(bidirectional reflectance distribution function) model RossThick-LiSparseR and least squares fitting method were used to calculate the parameter of BRDF. Then four narrow-band black-sky albedos and four narrow-band white-sky albedos can be obtained by angle integration. Finally, the cross-validation of FY-3C surface narrow-band albedo products with MODIS albedo products (MCD43A3) was carried out. The results show that theRoot Mean Square Error(RMSE) between the FY-3C narrow-band albedo and the corresponding MODIS narrow-band albedo is in the range of 0.01 ~ 0.04, and the Mean Bias (MBIAS) is 0.09. FY-3C narrow-band albedo has good consistency with the corresponding MODIS narrow-band albedo in the visible and near-infrared bands. So, the methodologyof using the BRDF model to invert the surface albedo of FY-3C medium resolution imaging spectrometer data is feasible and reliable. The further improvement of the inversion accuracy of FY3C-MERSI surface albedo also depends on the improvement of basic data processing quality, including image geometric correction, calibration, and strict data quality control.     

FY-3C中分辨率成像光谱仪数据的窄波段地表反照率验证研究

地表反照率数据对地表能量平衡和全球变化研究具有重要意义。基于2014年FY-3C卫星250 m分辨率的反射率数据和角度数据,选取非洲及北美洲的4个区域作为研究区,采用RossThick-LiSparseR模型作为BRDF(Bidirectional Reflectance Distribution Function)核模型反演了地表窄波段反照率,得到250 m分辨率的4个窄波段黑空、白空反照率。将反演得到的FY-3C地表窄波反照率产品与MODIS反照率产品（MCD43A3）数据进行了交叉验证,结果表明：FY-3C窄波段反照率与对应MODIS窄波段反照率对比的均方根误差在0.01~0.04,平均偏差(MBIAS)为0.09,FY-3C窄波段反照率与对应的MODIS窄波段反照率在可见光波段、近红外波段有较好的一致性。本研究提升了国产风云极轨卫星的应用范围,可为FY-3C地表反照率业务化产品提供算法支撑。     

Validating MODIS land surface reflectance products using ground-measured reflectance spectra – a case study in semi-arid grassland in Inner Mongolia,China

Validation of Moderate-Resolution Imaging Spectroradiometer (MODIS) land surface reflectance products is important to effective utilization of such products for earth systems science. Ground-based measurements are normally utilized for such validation. However, the major scale mismatch between the ground ‘point’ measurement and MODIS resolution (500 m and 1 km) makes direct comparison infeasible over many land surface types. In this paper, an indirect comparison between ground ‘point’ measurements and MODIS land surface products via high-resolution remotely sensed imagery (Landsat Thematic Mapper/TM) was utilized in semi-arid grassland of Inner Mongolia in summer 2005, where ground measurements are relatively sparse in comparison with other locations around the world. Within the validation, the TM reflectance imagery was first calibrated by the ground ‘point’ measurements, and then aggregated to MODIS data resolution for determination of their accuracy. Besides common direct spectral band comparison of reflectance between TM and MODIS, empirical/indirect comparison between TM and MODIS was also implemented. Both types of validation showed that the absolute error of bidirectional reflectance from atmospheric correction (MOD09) is less than 9.4%, and for nadir bidirectional reflectance distribution function (BRDF)-adjusted reflectance (MOD43B4) it is less than 3.1%, in which the error of visible bands of two data sets is less than 1.35% and 0.95%, respectively. This validation will help improve the accuracy of MODIS products used in this area.     

MODIS、MISR与POLDER 3种全球地表反照率卫星反演产品的比较与分析

对MODIS、MISR和POLDER 3种由多角度卫星观测反演得到的全球地表反照率数据(无冰雪覆盖区域)短波波段(SW,0.3~5 μm)与可见光波段(VIS,0.3~0.7 μm)的黑空地表反照率(DHR)进行了相互比较。3种产品6年平均的全球均值存在显著差异,其值从大到小依次为POLDER\,MISR和MODIS。3种产品的纬向平均在35°N以北区域表现出较大的差异。3种产品彼此之间相关性比较高,其中MODIS与MISR产品的相关性最强,MISR与POLDER产品的相关性最低,短波波段的相关系数(r) 分别为0.939与0.911。3种产品在可见光波段的相关性大于短波波段。在不同地表类型上,3种产品表现出了大致相似的差异,表明其对地表类型并不敏感。对气溶胶的分析表明:MODIS与MISR的550 nm气溶胶光学厚度(AOD)较为相似,其差异不足以解释DHR的差别;但是POLDER的865 nm AOD明显小于MISR,因此可以认为是由于POLDER的AOD估算偏低,导致了POLDER的DHR值大于MODIS与MISR。     

Spatial, spectral and temporal patterns of tropical forest cover change as observed with multiple scales of optical satellite data

This article describes the development of a methodology for scaling observations of changes in tropical forest cover to large areas at high temporal frequency from coarse resolution satellite imagery. The approach for estimating proportional forest cover change as a continuous variable is based on a regression model that relates multispectral, multitemporal MODIS data, transformed to optimize the spectral detection of vegetation changes, to reference change data sets derived from a Landsat data record for a study site in Central America. A number of issues involved in model development are addressed here by exploring the spatial, spectral and temporal patterns of forest cover change as manifested in a time-series of multi-scale satellite imagery.The analyses highlighted the distinct spectral change patterns from year-to-year in response to the possible land cover trajectories of forest clearing, regeneration and changes in climatic and land cover conditions. Spectral response in the MODIS Calibrated Radiances Swath data set followed more closely with the expected patterns of forest cover change than did the spectral response in the Gridded Surface Reflectance product. With forest cover change patterns relatively invariant to the spatial grain size of the analysis, the model results indicate that the best spectral metrics for detecting tropical forest clearing and regeneration are those that incorporate shortwave infrared information from the MODIS calibrated radiances data set at 500-m resolution, with errors ranging from 7.4 to 10.9% across the time periods of analysis.     

Retrieval of subpixel snow covered area, grain size, and albedo from MODIS

We describe and validate a model that retrieves fractional snow-covered area and the grain size and albedo of that snow from surface reflectance data (product MOD09GA) acquired by NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). The model analyzes the MODIS visible, near infrared, and shortwave infrared bands with multiple endmember spectral mixtures from a library of snow, vegetation, rock, and soil. We derive snow spectral endmembers of varying grain size from a radiative transfer model specific to a scene's illumination geometry; spectra for vegetation, rock, and soil were collected in the field and laboratory. We validate the model with fractional snow cover estimates from Landsat Thematic Mapper data, at 30 m resolution, for the Sierra Nevada, Rocky Mountains, high plains of Colorado, and Himalaya. Grain size measurements are validated with field measurements during the Cold Land Processes Experiment, and albedo retrievals are validated with in situ measurements in the San Juan Mountains of Colorado. The pixel-weighted average RMS error for snow-covered area across 31 scenes is 5%, ranging from 1% to 13%. The mean absolute error for grain size was 51 µm and the mean absolute error for albedo was 4.2%. Fractional snow cover errors are relatively insensitive to solar zenith angle. Because MODSCAG is a physically based algorithm that accounts for the spatial and temporal variation in surface reflectances of snow and other surfaces, it is capable of global snow cover mapping in its more computationally efficient, operational mode.     

MODIS卫星数据地表反照率反演的简化模式

以内蒙西部地区的MODIS遥感图像数据和地表野外同步观测的光谱数据为例,在野外数据量较少且有定标数据的条件下反演地表反照率。使用6S大气1辐射传输模型进行大气校正,并通过MODTRAN4.0模型获取各波段地表入射光通量和窄波段的地表反照率;在窄波段反照率与宽波段反照率之间存在线性关系的前提下,以各波段的入射光通量占总入射通量的比例作为反演参数,实现窄波段到宽波段的反演。反演结果证明此方法简便可行。     

MODIS snow albedo bias at high solar zenith angles relative to theory and to in situ observations in Greenland

In situ measurements of snow albedo at five stations along a north-south transect in the dry-snow facies of the interior of Greenland follow the theoretically expected dependence of snow albedo with solar zenith angle (SZA). Greenland Climate Network (GC-Net) measurements from 1997 through 2007 exhibit the trend of modest surface brightening with increasing SZA on both diurnal and seasonal timescales. SZA explains up to 50% of seasonal albedo variability. The two other environmental factors considered, temperature and cloudiness, play much less significant roles in seasonal albedo variability at the five stations studied. Compared to the 10-year record of these GC-Net measurements, the five-year record of MODIS satellite-retrieved snow albedo shows a systematic negative bias for SZA larger than about 55°. Larger bias of MODIS snow albedo exists at more northerly stations. MODIS albedos successfully capture the snow albedo dependence on SZA and have a relatively good agreement with GC-Net measurements for SZA < 55°. The discrepancy of MODIS albedo with in situ albedo and with theory is determined mainly by two related factors, SZA and retrieval quality. While the spatiotemporal structure, especially zonal features, of the MODIS-retrieved albedo may be correct for large SZA, the accuracy deteriorates for SZA > 55° and often becomes physically unrealistic for SZA > 65°. This unphysical behavior biases parameterizations of surface albedo and restricts the range of usefulness of the MODIS albedo products. Seasonal-to-interannual trends in surface brightness in Greenland, and in polar (i.e., large SZA) regions in general, and model simulations of these trends, should be evaluated in light of these limitations.     

NOAA AVHRR land surface albedo algorithm development

The primary objective of this research is to develop a surface albedo model for the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR). The primary test site is the Konza prairie, Kansas (U.S.A.), used by the International Satellite Land Surface Climatology Project (ISLSCP) in the First ISLSCP Field Experiment (FIFE). In this research, high spectral resolution field spectrometer data was analyzed to simulate AVHRR wavebands and to derive surface albedos. Development of a surface albedo algorithm was completed by analysing a combination of satellite, field spectrometer, and ancillary data. Estimated albedos from the field spectrometer data were compared to reference albedos derived using pyranometer data. Variations from surface anisotropy of reflected solar radiation were found to be the most significant albedo-related error. Additional error or sensitivity came from estimation of a shortwave mid-IR reflectance (1.3-4.0 mu m) using the AVHRR red and near-IR bands. Errors caused by the use of AVHRR spectral reflectance to estimate both a total visible (0.4-0.7 mu m) and near-IR (0.7-1.3 mu m) reflectance were small. The solar spectral integration, using the derived ultraviolet, visible, near-IR and SW mid-IR reflectivities, was not sensitive to many clear-sky changes in atmospheric properties and illumination conditions.     

基于中国通量网的MODIS短波反照率验证与分析

遥感地表反照率产品的验证与分析是将其应用于环境研究的基础。采用中国通量网的地表实测短波反照率数据对MODIS反照率产品进行对比和分析,针对选取的8个地面站点,提取了2004年的MODIS反照率产品并进行验证。这些站点的植被覆盖情况涵盖了草地、森林和农业用地。结果显示MODIS在多数情况下能提供准确的地表反照率产品。针对各个站点的误差、均方根误差、相关系数分析都显示了这个结果,总体反演误差在0.002左右。较大的误差出现在有冰雪影响的时候,排除受积雪影响的数据,总体均方根误差可达0.028。分析了引起误差的原因并提出了改进意见。     

Comparing MODIS and ETM+ data for regional and global land classification

Nearly simultaneous reflectance data sets from the Landsat 7 Enhanced Thematic Mapper Plus (ETM+), at 30-m resolution, and the Terra satellite instrument MODIS, at 500-m resolution, are compared for their ability to map fractional coverage of surface types over large areas. Lower spatial resolution MODIS classification results are generally comparable those of ETM+, with discrepancies for some regions with mixed surface types. Analysis of laboratory and field spectra suggests an ambiguity, the “brightness ambiguity”, which can prevent accurate area estimation of pixels having two or more surface types. This ambiguity, plus general mathematical inversion issues, can account for the discrepancy. Thus, occasional high-resolution measurements, as from Landsat 7, are necessary to refine estimations of large area surface types from MODIS and similar lower spatial resolution instruments.     

Retrieval of land surface albedo and temperature using data from the Indian geostationary satellite: a case study for the winter months

The shortwave and longwave radiation budget at land surfaces is largely dependent on two fundamental quantities, the albedo and the land surface temperature (LST). A time series (November 2005 to March 2006) of daily data from the Indian geostationary satellite Kalpana‐1 Very High Resolution Radiometer (K1VHRR) sensor in the visible (VIS), water vapour (WV) and thermal infrared (TIR) bands from noontime (0900 GMT) observations were processed to retrieve these quantities in clear skies for five winter months. Cloud detection was carried out using bispectral threshold tests (in both VIS and TIR bands) in a dekadal time series. Surface albedo was retrieved using a simple atmospheric transmission model. K1VHRR albedo was compared with Moderate Resolution Imaging Spectroradiometer (MODIS) AQUA noontime albedo over different land targets (agriculture, forest, desert, scrub and snow) that showed minimum differences over agriculture and forest. The comparison of spatial albedo over different landscapes yielded a root mean square deviation (RMSD) of 0.021 in VHRR albedo (9% of MODIS albedo). A mono‐window algorithm was implemented with a single TIR band to retrieve the LST. Its accuracy was also verified over different land targets by comparison with aggregated MODIS AQUA LST. The maximum RMSD was obtained over agriculture. Spatial comparison of VHRR and AQUA LSTs over homogeneous and heterogeneous landscape cutouts revealed an overall RMSD of 2.3 K. An improvement in the retrieval accuracy is expected to be achieved with atmospheric products from the sounder and split thermal bands in the imager of future INSAT 3D missions.     

Accuracy assessment of the MODIS 16-day albedo product for snow: comparisons with Greenland in situ measurements

The accuracy of the Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day albedo product (MOD43) is assessed using ground-based albedo observations from automatic weather stations (AWS) over spatially homogeneous snow and semihomogeneous ice-covered surfaces on the Greenland ice sheet. Data from 16 AWS locations, spanning the years 2000-2003, were used for this assessment. In situ reflected shortwave data were corrected for a systematic positive spectral sensitivity bias of between 0.01 and 0.09 on a site-by-site basis using precise optical black radiometer data. Results indicate that the MOD43 albedo product retrieves snow albedo with an average root mean square error (RMSE) of ±0.07 as compared to the station measurements, which have ±0.035 RMSE uncertainty. If we eliminate all satellite retrievals that rely on the backup algorithm and consider only the highest quality results from the primary bidirectional reflectance distribution function (BRDF) algorithm, the MODIS albedo RMSE is ±0.04, slightly larger than the in situ measurement uncertainty. There is general agreement between MODIS and in situ observations for albedo <0.7, while near the upper limit, a −0.05 MODIS albedo bias is evident from the scatter of the 16-site composite.     

Narrowband-to-broadband albedo conversion for glacier ice and snow: equations based on modeling and ranges of validity of the equations

In this paper, we propose equations for narrowband-to-broadband (NTB) albedo conversion for glacier ice and snow for four types of satellite sensors: thematic mapper (TM), advanced very high resolution radiometer (AVHRR), moderate resolution imaging spectroradiometer (MODIS), and multi-angle imaging spectroradiometer (MISR). We do this on the basis of spectral albedos and incident spectral irradiances generated with radiative-transfer models of the (sub-)surface (a two-stream model) and the atmosphere, respectively. First, we establish equations for reference values of atmospheric components and the surface elevation. These equations describe measurements with root-mean-square differences of ∼0.016. We then show that the “reference equations” also perform well when total ozone and aerosol optical depth are changed with respect to the reference. The negative effect of humidity and elevation variations on the performance of the equations can be eliminated by adding a correction term. We argue that narrowband albedos are much less sensitive to variations in the incident spectral irradiance than broadband albedos. Hence, our conclusions about the effects of variations in atmospheric composition and elevation are also valid for equations for NTB conversion proposed in other papers.