Accuracy assessment of four cloud-free snow cover products over the Qinghai-Tibetan Plateau

Four up-to-date daily cloud-free snow products – IMS (Interactive Multisensor Snow products), MOD-SSM/I (combination of the MODIS and SSM/I snow products), MOD-B (Blending method basing on the MODIS snow cover products) and TAI (Terra–Aqua–IMS) – with high-resolutions over the Qinghai-Tibetan Plateau (QTP) were comprehensively assessed. Comparisons of the IMS, MOD-SSM/I, MOD-B and TAI cloud-free snow products against meteorological stations observations over 10 snow seasons (2004–2013) over the QTP indicated overall accuracies of 76.0%, 89.3%, 92.0% and 92.0%, respectively. The K_hat values of the IMS, MOD-SSM/I, MOD-B and TAI products were 0.084, 0.463, 0.428 and 0.526, respectively. The TAI products appear to have the best cloud-removal ability among the four snow products over the QTP. Based on the assessment, an I-TAI (Improvement of Terra–Aqua–IMS) snow product was proposed, which can improve the accuracy to some extent. However, the algorithms of the MODIS series products show instability when identifying wet snow and snow under forest cover over the QTP. The snow misclassification is an important limitation of MODIS snow cover products and requires additional improvements.     

基于二次多项式的AOD数据融合方法

针对Aqua和Terra MODIS AOD数据利用线性回归算法拟合结果不够精确的问题,本文提出了二次多项式回归算法对其进行拟合,二次多项式是指这个多项式的项数超过1,且最高次方数为2。采用二次多项式回归和线性回归算法分别对2015年随机选择的一天和4-6月的AOD数据进行拟合,并将两种方法拟合的结果进行对比分析。研究结果显示,针对同一组Aqua和Terra MODIS AOD数据的拟合,二次多项式回归方法拟合得到的RMSE、MAE、R值比线性回归拟合方法得到的值精度都要高很多,说明二次多项式回归拟合方法在Aqua和Terra MODIS AOD数据的拟合方面优于线性回归方法的拟合,证明了二次多项式回归拟合方法适用于此方面的研究,而且能够提升Aqua和Terra MODIS AOD数据拟合结果的精度。     

A new method for retrieving band 6 of aqua MODIS

The Moderate Resolution Imaging Spectroradiometer (MODIS) is a key research instrument for the NASA Earth Observing System (EOS) mission. It was successfully launched onboard the Terra satellite in December 1999 and Aqua satellite in May 2002. Both MODIS instruments have been working well except that 15 of the 20 detectors in Aqua MODIS band 6 (1.628-1.652 /spl mu/m) are either nonfunctional or noisy. The striping in Aqua MODIS band 6 caused by its nonfunctional or noisy detectors has been a serious problem for MODIS snow products, which use band 6 primarily for snow detection. MODIS scientists have been using Aqua MODIS band 7 (2.105-2.155 /spl mu/m) instead of band 6 for computing the normalized difference snow index to continue detecting global snow coverage. The main objective of this letter is to retrieve Aqua MODIS band 6 using other bands based on their relationships in Terra MODIS. The band retrieval approach proposed in this letter is also very useful for the next generation of MODIS sensor-the Visible/Infrared Imager/Radiometer Suite (VIIRS) band M10 proxy data generation. Such proxy data can support the VIIRS prelaunch end-to-end testing, postlaunch calibration/validation, and data quality checking.     

Estimation of Systematic Errors of MODIS Thermal Infrared Bands

This letter reports a statistical method to estimate detector-dependent systematic error in Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared (TIR) Bands 20-25 and 27-36. There exist scan-to-scan overlapped pixels in MODIS data. By analyzing a sufficiently large amount of those most overlapped pixels, the systematic error of each detector in the TIR bands can be estimated. The results show that the Aqua MODIS data are generally better than the Terra MODIS data in 160 MODIS TIR detectors. There are no detector-dependent systematic errors in Bands 31 and 32 for both Terra and Aqua MODIS data. The maximum detector errors are 3.00 K in Band 21 of Terra and -8.15 K in that of Aqua for brightness temperatures of more than 250 K     

利用TERRA和AQUA共同反演陆地上空的气溶胶光学厚度

利用TERRA和AQUA共同反演气溶胶光学厚度和地表反射率特征，对其原理及方法进行了详细的讨论。通过Terra和Aqua两颗卫星对同一地点的不同角度的观测，结合多个光学通道的信息，反演了北京地区光学厚度及地表反射率信息。反演的气溶胶光学厚度同地面观测的结果相比具有很好的一致性。同时，对地表反射率及气溶胶波长指数等也进行了讨论和对比，结果显示，对北京地区，MODIS1通道地表反射率和7通道地表反射率的比在0．66左右，3通道和7通道的比在0．28左右。相比于NASA暗背景全球反演算法中1、3通道和7通道的比为0．50和0．25的处理方法，反演得到的气溶胶光学厚度结果也较好。     

Dust Radiative Effects Over Global Oceans

Using one year of moderate resolution imaging spectroradiometer (MODIS) and clouds and the Earth's radiant energy system (CERES) data, we provide a satellite-based assessment of top-of-atmosphere (TOA) cloud-free shortwave and longwave dust radiative effects over global oceans from the Terra satellite. Over global cloud-free oceans, the dust net radiative effect is -0.7 plusmn0.2 W middotm^-2, and the TOA dust shortwave radiative effect (SWRE) dominates the longwave radiative effect (LWRE). Globally, the annual mean dust contribution to the total MODIS level 2 aerosol optical thickness (AOT, at 550 nm) is about 30% with a dust SWRE of -0.7 plusmn0.2 W middotm^-2 and LWRE of 0.03 plusmn0.02 W middotm^-2. Averaged over all seasons, the cloud-free diurnal mean dust radiative efficiency is -33 plusmn5 W middotm^-2 middottau^-1, and there is a remarkable linear relationship between the CERES SWRE and the MODIS AOT. This is the first satellite-based assessment of dust net radiative effect over the global oceans and will serve as a useful constraint for numerical modeling analysis.     

Characterisation of Residue Burning from Agricultural System in India using Space Based Observations

Biomass burning is a global phenomenon with agriculture residue burning having a sizeable share. Biomass burning is a major source of emission of green house gases (GHGs). Thus the space-based observations of global distribution of fire form a key component of climate change studies. This study is a step towards understanding the spatio-temporal occurrence of agricultural residues burning in Indo-Gangetic plains of India using fire products from space borne satellites. The 3 years daily active fire data of MODIS (Aqua/Terra) from August, 2006 to July, 2009 have been used in this study. The data analysis showed that out of total fire events, around 69% contribution comes from agricultural areas and remaining (31%) comes from non-agricultural areas. This is mainly due to the intensive cultivation in this belt. The characterisation analysis revealed that, 84% of agriculture residues burning is from Rice-Wheat system (RWS) alone and remaining 16% in other types of crop rotations. The fire incidents were very high in October–December (55%) compared to that in March–May (36%), further indicating that burning of rice residue is more prevalent than that of wheat.     

Fusing MODIS with Landsat 8 data to downscale weekly normalized difference vegetation index estimates for central Great Basin rangelands,USA

Data fused from distinct but complementary satellite sensors mitigate tradeoffs that researchers make when selecting between spatial and temporal resolutions of remotely sensed data. We integrated data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra satellite and the Operational Land Imager sensor aboard the Landsat 8 satellite into four regression-tree models and applied those data to a mapping application. This application produced downscaled maps that utilize the 30-m spatial resolution of Landsat in conjunction with daily acquisitions of MODIS normalized difference vegetation index (NDVI) that are composited and temporally smoothed. We produced four weekly, atmospherically corrected, and nearly cloud-free, downscaled 30-m synthetic MODIS NDVI predictions (maps) built from these models. Model results were strong with R² values ranging from 0.74 to 0.85. The correlation coefficients (r ≥ 0.89) were strong for all predictions when compared to corresponding original MODIS NDVI data. Downscaled products incorporated into independently developed sagebrush ecosystem models yielded mixed results. The visual quality of the downscaled 30-m synthetic MODIS NDVI predictions were remarkable when compared to the original 250-m MODIS NDVI. These 30-m maps improve knowledge of dynamic rangeland seasonal processes in the central Great Basin, United States, and provide land managers improved resource maps.     

Snow and ice mask for the MODIS aerosol products

Atmospheric products have been derived operationally from multichannel imaging data collected with the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua spacecraft. Preliminary validations of the products were previously reported. Through analysis of more extensive time-series of MODIS aerosol products (Collection 4), we have found that the aerosol products over land areas are slightly contaminated by snow and ice during the springtime snow-melting season. We have developed an empirical technique using MODIS near-infrared channels centered near 0.86 and 1.24 /spl mu/m and a thermal emission channel near 11 /spl mu/m to mask out these snow-contaminated pixels over land. Improved aerosol retrievals over land have been obtained. Sample results from application of the technique to MODIS data acquired over North America, northern Europe, and northeastern Asia are presented. The technique has been implemented into the MODIS Collection 5 operational algorithm for retrieving aerosols over land from MODIS data.     

Using a Cold Earth Surface Target to Characterize Long-Term Stability of the MODIS Thermal Emissive Bands

The Moderate Resolution Imaging Spectroradiometer (MODIS) has successfully provided Earth image products for instruments on the Terra and Aqua satellites since 2000 and 2002, respectively. Maintaining accurate radiometric calibration and calibration consistency between two sensors is an important issue for continued quality of long-term data records, especially as the instruments operate beyond their original projected mission lifetime. A strategy to use frequent MODIS measurements of the brightness temperature of the land surface in the area surrounding Dome Concordia, Antarctica (75.1, 123.4 ) to track the long-term stability of MODIS Band 31 is presented. Dome Concordia, located on the Antarctic plateau, is one of the most homogeneous land surfaces on Earth in terms of surface temperature and emissivity, with a seasonal temperature range of 190-250 K. The extremely dry, cold, and rarefied atmosphere of the site makes it ideal to track and detect any long-term changes in the MODIS thermal band response through trend analyses of near-nadir MODIS overpass data in conjunction with surface temperature measurements. Application of this approach shows an average relative bias between Terra and Aqua MODIS Band 31 (11 ) measurements of 0.08 K, which is well within the calibration uncertainty.     

Validation of MODIS integrated water vapor product against reference GPS data at the Iberian Peninsula

In this work, the water vapor product from MODIS (MODerate-resolution Imaging Spectroradiometer) instrument, on-board Aqua and Terra satellites, is compared against GPS water vapor data from 21 stations in the Iberian Peninsula as reference. GPS water vapor data is obtained from ground-based receiver stations which measure the delay caused by water vapor in the GPS microwave signals. The study period extends from 2007 until 2012. Regression analysis in every GPS station show that MODIS overestimates low integrated water vapor (IWV) data and tends to underestimate high IWV data. R² shows a fair agreement, between 0.38 and 0.71. Inter-quartile range (IQR) in every station is around 30–45%. The dependence on several parameters was also analyzed. IWV dependence showed that low IWV are highly overestimated by MODIS, with high IQR (low precision), sharply decreasing as IWV increases. Regarding dependence on solar zenith angle (SZA), performance of MODIS IWV data decreases between 50° and 90°, while night-time MODIS data (infrared) are quite stable. The seasonal cycles of IWV and SZA cause a seasonal dependence on MODIS performance. In summer and winter, MODIS IWV tends to overestimate the reference IWV value, while in spring and autumn the tendency is to underestimate. Low IWV from coastal stations is highly overestimated (∼60%) and quite imprecise (IQR around 60%). On the contrary, high IWV data show very little dependence along seasons. Cloud-fraction (CF) dependence was also studied, showing that clouds display a negligible impact on IWV over/underestimation. However, IQR increases with CF, except in night-time satellite values, which are quite stable.     

Water quality classification of lakes using 250-m MODIS data

The traditional method used in the water quality classification of Finnish lakes includes the collection of water samples from lakes and their analysis in laboratory conditions. The classification is based on statistical analysis of water quality parameter values and on expert opinion. It is possible to acquire similar information by using radiance values measured with the Earth Observing System Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS). In this letter, the classification accuracy with MODIS data is about 80%. Only about 0.2% of the 20 391 pixels were misclassified by two or more classes, as a four-class classification system is used.     

利用天宫一号高光谱红外谱段估算青藏高原地表通量与蒸散量

利用天宫一号高光谱红外谱段,结合准同步的Aqua MODIS (MYD021KM) 资料,在对地表特征参数估算的基础上,利用地表能量平衡系统模式计算藏北高原地区的地表通量与蒸散量.结果表明基于天宫一号高分辨率高光谱红外谱段的地表通量与蒸散量估算结果和地表实际状况吻合,具有很大的应用潜力.     

FY-3B/MWRI和Aqua/AMSR-E海冰密集度比较及印证

本文对2011-07-01—2011-09-30风云三号B星(FY-3B)搭载的微波成像仪MWRI(Microwave Radiometer Imager)和Aqua卫星搭载的微波扫描辐射计AMSR-E(Advanced Microwave Scanning Radiometer for Earth Observing System)观测数据获取的海冰密集度产品进行比较及印证。首先,逐日比较FY-3B/MWRI和Aqua/AMSR-E区域平均海冰密集度;其次,逐月比较FY-3B/MWRI和Aqua/AMSR-E月平均海冰密集度;最后,使用Aqua卫星搭载的中等分辨率成像光谱辐射计MODIS数据进行印证。MWRI和AMSR-E比较结果为(1)MWRI与AMSR-E逐日区域平均海冰密集度变化趋势一致,MWRI海冰密集度均高于AMSR-E,7—9月MWRI与AMSR-E逐日平均偏差月平均值分别为8.55%、7.67%、2.58%,逐日标准差月平均值分别为12.16%、12.08%、10.43%,二者差异逐月减小。(2)MWRI与AMSR-E月平均海冰密集度差呈现逐月递减趋势,7—9月MWRI与AMSR-E逐月平均偏差分别为7.37%、6.53%、1.51%,逐月标准差分别为4.61%、4.36%、3.64%,MWRI与AMSR-E差异逐月减小的原因是二者在密集度较低的边缘区域差异较大,而夏季随着边缘区域海冰的融化,二者差异逐渐减小。MWRI和AMSRE海冰密集度与MODIS印证结果为:(1)密集度小于95%情况下,MWRI与AMSR-E海冰密集度均比MODIS偏高,AMSR-E更接近MODIS,MWRI高估,误差较大。(2)密集度大于等于95%情况下,MWRI与AMSR-E海冰密集度均比MODIS偏低,AMSR-E偏低更多,MWRI结果更好。     

Prototyping an artificial neural network for burned area mapping on a regional scale in Mediterranean areas using MODIS images

Each year thousands of ha of forest land are affected by forest fires in Southern European countries such as Spain. Burned area maps are a valuable instrument for designing prevention and recovery policies. Remote sensing has increasingly become the most widely used tool for this purpose on regional and global scales, where a large variety of techniques and data has been applied. This paper proposes a semiautomatic method for burned area mapping on a regional scale in Mediterranean areas (the Iberian Peninsula has been used as a study case). A Multi-layer Perceptron Network (MLPN) has been designed and applied to MODIS/Terra Surface Reflectance Daily L2G Global 500m SIN Grid multitemporal composite monthly images. The compositing criterion was based on maximum surface temperature. The research covered a six year period (2001–2006) from June to September, when most of the forest fires occur. The resulting burned area maps have been validated using official fire perimeters and compared with MODIS Collection 5 Burned Area Product (MCD45A1). The MLPN shown as an effective method, with a commission error of 29.1%, in the classification of the burned areas, while the omission error was of 14.9%. The results were compared with the MCD45A1 product, which had a slightly higher commission error (30.2%) and a considerably higher omission error (26.2%), indicating a high underestimation of the burned area.     

NPPVIIRS数据反演气溶胶光学厚度

利用NPP卫星的VIIRS传感器数据,基于暗像元法反演陆地气溶胶光学厚度AOD。首先,根据红外波段的归一化植被指数NDVI来对暗像元进行识别;然后,利用6S软件进行辐射传输计算构建查找表;最后,根据VIIRS数据从查找表插值得到AOD,并对其进行海拔校正。选取华北地区作为反演实验区,获得了2013年9月1日的气溶胶分布。利用AERONET北京站太阳光度计地基观测结果对反演结果对比验证,发现二者具有显著的相关性,相关系数达到0.7920。将2013年9月1日的MODIS AOD产品与本研究反演的AOD进行比对,发现二者分布趋势一致,相关系数为0.7059,相关性显著。反演结果表明,本文算法反演陆地AOD效果较好,为大气颗粒物环境监测提供了良好方法手段和数据源。     

A new method for generating a clear-sky Landsat composite for cropland from cloud-contaminated Landsat-7 and Landsat-8 images

A new method was developed in this study for producing a clear-sky Landsat composite for cropland from cloud-contaminated Landsat images acquired in a short time period. It used Thiel–Sen regression to normalize all Landsat scenes to a MODIS image to make all Landsat images radiometrically consistent and comparable. Pixel selection criteria combining the modified maximum vegetation index and the modified minimum visible reflectance selection methods were designed to enhance the pixel selection of land/water over cloud/shadow in the image compositing. The advantages of the method include (1) avoiding complicated atmospheric corrections but with reliable surface reflectance results, (2) being insensitive to errors induced by image co-registration uncertainties between Landsat and MODIS images, (3) avoiding the lack of samples for the regression analysis using the full Landsat scenes (rather than overlay regions), and (4) enhancing cloud/shadow detection. The composite image has MODIS-like surface reflectance, thus making MODIS algorithms applicable for retrieving biophysical parameters. The method was automatically implemented on a set of 13 cloud-contaminated (>39%) Landsat-7 (Scan-Line Corrector-Off) and Landsat-8 scenes acquired during peak growing season in a crop region of Manitoba, Canada. The result was a 95.8% cloud-free image. The method can also substantially increase the usage of cloud-contaminated Landsat data.     

FY-3C VIRR大气可降水产品生成和检验

风云三号C星(FY-3C)可见光红外扫描辐射计(VIRR)两个红外分裂窗通道数据生成的晴空大气可降水(TPW)产品已投入业务使用。本文介绍了该产品的生成方法,并从产品精度和稳定性两个方面评价产品质量。与MODIS Terra TPW的月平均数据对比,FY-3C VIRR TPW能正确反应大气可降水的全球分布。与2015年3月—4月的全球探空数据对比,FY-3C VIRR TPW均方根误差为5.36 mm,相对误差在水汽值大于30 mm时在20%以内,并且夜间产品精度优于白天。相比于MODIS红外TPW产品与探空数据的误差,FY-3C TPW精度略好。计算2015年1月至2016年7月FY-3C VIRR TPW产品相对探空数据的月均方根误差,19个月均方根误差的标准差是0.54 mm,小于同期MODIS Terra TPW均方根误差的标准差,说明FY-3C VIRR TPW产品在检验时期内更稳定。FY-3C VIRR TPW产品精度较高且质量稳定,具备广泛应用能力。     

Semi-automated mapping of burned areas in semi-arid ecosystems using MODIS time-series imagery

Understanding spatial and temporal patterns of burned areas at regional scales, provides a long-term perspective of fire processes and its effects on ecosystems and vegetation recovery patterns, and it is a key factor to design prevention and post-fire restoration plans and strategies. Remote sensing has become the most widely used tool to detect fire affected areas over large tracts of land (e.g., ecosystem, regional and global levels). Standard satellite burned area and active fire products derived from the 500-m Moderate Resolution Imaging Spectroradiometer (MODIS) and the Satellite Pour l’Observation de la Terre (SPOT) are available to this end. However, prior research caution on the use of these global-scale products for regional and sub-regional applications. Consequently, we propose a novel semi-automated algorithm for identification and mapping of burned areas at regional scale. The semi-arid Monte shrublands, a biome covering 240,000 km² in the western part of Argentina, and exposed to seasonal bushfires was selected as the test area. The algorithm uses a set of the normalized burned ratio index products derived from MODIS time series; using a two-phased cycle, it firstly detects potentially burned pixels while keeping a low commission error (false detection of burned areas), and subsequently labels them as seed patches. Region growing image segmentation algorithms are applied to the seed patches in the second-phase, to define the perimeter of fire affected areas while decreasing omission errors (missing real burned areas). Independently-derived Landsat ETM+ burned-area reference data was used for validation purposes. Additionally, the performance of the adaptive algorithm was assessed against standard global fire products derived from MODIS Aqua and Terra satellites, total burned area (MCD45A1), the active fire algorithm (MOD14); and the L3JRC SPOT VEGETATION 1 km GLOBCARBON products. The correlation between the size of burned areas detected by the global fire products and independently-derived Landsat reference data ranged from R² = 0.01–0.28, while our algorithm performed showed a stronger correlation coefficient (R² = 0.96). Our findings confirm prior research calling for caution when using the global fire products locally or regionally.     

HJ-1A/B卫星CCD影像辅助的MODIS水色大气校正产品质量改进

针对我国近岸高浑浊水体区域MODIS短波红外波段大气校正产品中存在的信号饱和及条带问题,利用神经网络模型,采用准同步的HJ-1A/B卫星CCD影像及实测遥感反射率数据对MODIS/Terra水色遥感大气校正产品进行了质量改进。改进后结果与MODIS/Terra遥感反射率产品相比,平均相对误差为13.3%,信号饱和区域修复结果与实测数据各波段平均相对误差为28.2%。结果表明,该方法在保证结果精度的情况下,能有效地修复MODIS/Terra水色波段因为信号饱和而产生的数据空白区域,同时也能较好地解决MODIS/Terra大气校正产品中的条带问题。