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1.
Accurate monitoring of vegetation dynamics is required to understand the inter-annual variability and long term trends in terrestrial carbon exchange in tundra and boreal ecoregions. In western North America, two Normalized Vegetation Index (NDVI) products based on spectral reflectance data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are available. The MOD/MYD13A2 NDVI product is available as a 16-day composite product in a sinusoidal projection as global hdf tiles. The eMODIS Alaska NDVI product is available as a 7-day composite geotif product in a regional equal area conic projection covering Alaska and the entire Yukon River Basin. These two NDVI products were compared for the 2012–2014 late May–late June spring green-up periods in Alaska and the Yukon Territory. Relative to the MOD/MYD13A2 NDVI product, it is likely that the eMODIS NDVI product contained more cloud-contaminated NDVI values. For example, the MOD/MYD13A2 product flagged substantially fewer pixels as “good quality” in each 16-day composite period compared to the corresponding MODIS Alaska NDVI product from a 7-day composite period. During the spring green-up period, when field-based NDVI increases, the eMODIS NDVI product averaged 43 percent of pixels that declined by at least 0.05 NDVI between 2 composite periods, consistent with cloud-contamination problems, while the MOD/MYD13A2 NDVI averaged only 6 percent of pixels. Based on a cloudy Landsat-8 scene, the eMODIS compositing process selected 23 percent pixels, while the MOD/MYD13A2 compositing process selected less than 0.003 percent pixels. Based on the results, it appears that the MOD/MYD13A2 NDVI product is superior for scientific applications based on NDVI phenology in the tundra and boreal regions of northwestern North America.  相似文献   

2.
王晓雨  管磊  李乐乐 《遥感学报》2018,22(5):723-736
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。  相似文献   

3.
真实性检验是评价遥感反演产品质量和验证遥感应用产品是否准确、真实地反映实际情况的重要途径。叶面积指数(LAI)是表征陆地植被结构和长势的关键参数,全面准确评价和验证LAI产品是产品用于陆面过程模型的前提。本文以MODIS LAI与GLASS LAI产品为研究对象,在尺度效应和尺度转换的基础上,建立了针对非均匀像元的低分辨率LAI产品真实性检验方法。在考虑空间异质性和植被长势差异的情况下,借助中分辨率的遥感影像,分别利用1 km像元平均叶面积指数和反演表观叶面积指数实现了对LAI算法和产品的真实性检验。为了比较作物长势差异和地表非均匀度对产品的影响,本文选择有代表性的河南鹤壁和甘肃张掖两个地区进行两种LAI产品真实性检验研究。研究结果表明,GLASS LAI和MODIS LAI产品均存在明显的低估现象。这并不是产品算法的问题,而是由于地表异质性和非均匀度的影响。在异质性更显著的张掖盈科灌区,低估现象更明显。GLASS LAI产品是多种LAI产品的融合,它的平均LAI比MODIS更接近真实情况,但是LAI的动态范围比MODIS窄。  相似文献   

4.
评估MODIS的BRDF角度指数产品   总被引：1，自引：2，他引：1  
应用地表观测的二向性反射数据集和多种MODIS数据产品,通过统计分析,对MODIS的二向性反射角度指数产品进行综合评估,结果表明:(1)MODIS角度指数包含了地表三维结构信息,有望用来反演地表的物理结构参数;(2)MODIS角度指数是内在的三维关系,各向异性因子(Anisotropic Factor:ANIF)和各向异性指数(Anisotropic Index:ANIX)高相关,建议去掉ANIF以精炼MODIS角度指数产品;(3)各向异性平整指数(Anisotropic FlatIndex:AFX)较好地指示了地表基本散射类型的变化,且具有较小的类内方差,对改善特定地表分类精度可能会更有用.  相似文献   

5.
Bidirectional reflectance distribution functions (BRDF) seek to represent surface reflectance anisotropy resulting from surface physical structure and changes in a satellite sensor’s view and solar illumination angles. NASA’s MODerate resolution imaging spectroradiometer (MODIS) is a wide field of view sensor that generates observations over a large range of view angles. Based on MODIS observations, a BRDF product and several sub-products have been developed by MODIS science teams, i.e. the MCD43 product suite. Variations in pixels’ ground instantaneous field of view (GIFOV), i.e. the size of a pixel’s footprint on the ground, is a well known effect associated with wide field of view sensors such as MODIS, but is not specifically considered in the MODIS BRDF algorithm nor has research been undertaken into its effects on MODIS BRDF modelling. This paper introduces two metrics to examine the relationship between reflectance variations associated with changes in MODIS pixels’ GIFOV and the MODIS BRDF (MCD43) product. These metrics are applied to four different study areas and epochs across the Australian continent. The two metrics are shown to be well correlated (mean correlation coefficient of 0.81 for the four study areas); suggesting that variations in pixels’ GIFOV are a consistent, non-random source of variance in MODIS BRDF modelling. The results contained in this paper suggest that all downstream products which include MODIS BRDF processing in their derivation and results directly based on MODIS BRDF processing may need to be reassessed.  相似文献   

6.
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  相似文献   

7.
结合像元分解和STARFM模型的遥感数据融合   总被引：4，自引：2，他引：2  
高空间、时间分辨率遥感数据在监测地表快速变化方面具有重要的作用。然而,对于特定传感器获取的遥感影像在空间分辨率和时间分辨率上存在不可调和的矛盾,遥感数据时空融合技术是解决这一矛盾的有效方法。本文利用像元分解降尺方法(Downscaling mixed pixel)和STARFM模型(Spatial and Temporal Adaptive Reflectance Fusion Model)相结合的CDSTARFM算法(Combination of Downscaling Mixed Pixel Algorithm and Spatial and Temporal Adaptive Reflectance Fusion Model)进行遥感数据融合。首先,利用像元分解降尺度方法对参与融合的MODIS数据进行分解降尺度处理;其次,利用分解降尺度的MODIS数据替代STARFM模型中直接重采样的MODIS数据进行数据融合;最后以Landsat 8和MODIS遥感影像数据对该方法进行了实验。结果表明:(1)CDSTARFM算法比STARFM和像元分解降尺度算法具有更高的融合精度;(2)CDSTARFM能够在较小的窗口下获得更高的融合精度,在相同的窗口下其融合精度也高于STARFM;(3)CDSTARFM融合的影像更接近真实影像,消除了像元分解降尺度影像中的"图斑"和STARFM模型融合影像中的"MODIS像元边界"。  相似文献   

8.
基于波谱知识库的MODIS叶面积指数反演及验证   总被引：2，自引：0，他引：2  
目前用物理模型反演叶面积指数普遍存在缺少先验知识的状况，如何获得准确的先验知识是遥感走向应用的一个关键环节。中国典型地物标准波谱数据库就是结合国家重大行业中的应用需求，研究制定地物波谱获取与分析的技术规范和数据标准，建立典型地物标准波谱数据库。从波谱数据库提取模型反演所需要的先验知识，实现了基于SAIL模型的MODIS数据（经过几何纠正与大气纠正）叶面积指数的反演。另外，基于TM数据，对MODIS混合像元进行了分解，用纯像元的叶面积指数与实测数据进行对比验证，同时，反演结果与NASA的LAI产品也进行了对比，结果表明基于波谱库的先验知识可以有效的提高叶面积指数的反演精度。  相似文献   

9.
Cloud cover is generally present in remotely sensed images, which limits the potential of the images for ground information extraction. Therefore, removing the clouds and recovering the ground information for the cloud-contaminated images is often necessary in many applications. In this paper, an effective method based on similar pixel replacement is developed to solve this task. A missing pixel is filled using an appropriate similar pixel within the remaining region of the target image. A multitemporal image is used as the guidance to locate the similar pixels. A pixel-offset based spatio-temporal Markov random fields (MRF) global function is built to find the most suitable similar pixel. The proposed method was tested on MODIS and Landsat images and their land surface temperature products, and the experiments verify that the proposed method can achieve highly accurate results and is effective at dealing with the obvious atmospheric and seasonal differences between multitemporal images.  相似文献   

10.
Detection, monitoring and precise assessment of the snow covered regions is an important issue. Snow cover area and consequently the amount of runoff generated from snowmelt have a significant effect on water supply management. To precisely detect and monitor the snow covered area we need satellite images with suitable spatial and temporal resolutions where we usually lose one for the other. In this study, products of two sensors MODIS and ASTER both on board of TERRA platform having low and high spatial resolution respectively were used. The objective of the study was to modify the snow products of MODIS by using simultaneous images of ASTER. For this, MODIS snow index image with high temporal resolution were compared with that of ASTER, using regression and correlation analysis. To improve NDSI index two methods were developed. The first method generated from direct comparison of ASTER averaged NDSI with those of MODIS (MODISI). The second method generated by dividing MODIS NDSI index into 10 codes according to their percentage of surface cover and then compared the results with the difference between ASTER averaged and MODIS snow indices (SCMOD). Both methods were tested against some 16 MODIS pixels. It is found that the precision of the MODISI method was more than 96%. This for SCMOD was about 98%. The RMSE of both methods were as good as 0.02.  相似文献   

11.
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.  相似文献   

12.
Bundle adjustment is a method for simultaneously calculating both the interior and exterior orientation parameters of a set of images, and the object-space coordinates of the observed points. In the case of long focal length lenses and narrow field-of-view (FOV) imaging situations, collinearity based (perspective projection) algorithms may result in linear dependencies between parameters that cause solution instability. The use of a scaled orthographic projection model based on linear algebraic formulations was therefore adopted to reduce this risk. Using quaternions, a new mathematical model is derived that includes the partial derivatives as well as the inner constraint equations for a scaled orthographic bundle adjustment. The model was then tested using two image sets of a single, small vessel (about 6 m length) with a cube target of known dimensions at two distinct ranges; perspective solutions were also calculated for comparison. RMS residual errors of 0.74-0.78 pixels associated with the new method compare favorably to a residual error range of 0.59-0.74 pixels using a perspective bundle adjustment of the same target points. Relative precisions (as a ratio of target size) of between 1:1650 and 1:750 have been achieved at ranges of 375 m and 850 m, respectively, given comparisons with the known cube dimensions. A third image dataset consisting of a network of 16 images was solved with a 1:2200 relative precision showing the new method can successfully handle high redundancy. For the experiments that were conducted, the new method was found to produce less precise results than the perspective bundle solution for a FOV of 0.50-0.65° where the object fills 5-8% of the image. However, it was found to match the precision of the perspective model (with an uncalibrated camera) for a FOV of 0.20-0.30° where the object of interest fills only 1-2% of the full image.  相似文献   

13.
The angular effects of emissivity are ignored in current land surface temperature (LST) products. As a result, the directionality of these LST products limits their further application in many fields. Accurate correction of the angular problem of LST products requires explicit understanding of the angular effects of emissivity at the pixel scale. Currently, nearly ten years of global emissivity products of MODIS are available. However, the pixel-scale directionality of emissivity has never been analyzed. By performing a statistical analysis of 5-year MODIS emissivity products over most of East Asia, we generated the empirical relationships between the directional emissivity, land cover, and seasonal variations. Two look-up tables (LUTs) of directional emissivity were created for typical land cover types and applied to the generalized split-window algorithm to modify the MODIS LST. The results showed that the angular effect of emissivity could introduce a significant bias of −1-3 K to the 1 km resolution LST. Finally, the spatial scale effects of emissivity were analyzed, and it was found that the temperature differences caused by scale effects fell within +/−0.5 K for most pixels if 5 km emissivity was used in 1 km LST retrieval. Therefore, wide use of the LUTs can be expected.  相似文献   

14.
遥感探测到的小目标信号一般是弱信号,利用传统的高光谱异常变化检测方法直接抑制背景来突出异常变化目标,往往导致小目标弱信号同时被抑制,造成目标探测率低、虚警率高。基于独立成分分析方法,研究了弱信号小目标的高光谱变化检测模型,该模型首先通过投影寻踪将异常变化影像投影到独立成分,突出异常变化目标,然后再抑制背景,从而达到异常变化目标和背景的有效分离。该模型可以有效降低虚警率,提高探测率。利用模拟数据和真实数据进行了精度验证,结果表明,利用模拟数据得到的探测精度为99%,利用真实数据得到的检测精度为86%,与传统异常变化检测算法相比,精度最高提高了9%。本文研究方法适用于弱信号小目标的高光谱异常变化检测。  相似文献   

15.
黄明益  吴军  高炯笠 《测绘学报》2022,51(5):703-717
针对多镜头全景摄像机MPC室内标定参数输出的实际场景球面全景视频存在视差伪影问题,提出一种场景自适应的球面全景视频无缝生成方法,主要包括两方面内容:①MPC球面投影参数最优估计。以实际场景视频重叠区域同名像点为观测值,通过最小化球面投影中心到同名像素对应球面空间点的夹角建立误差方程对球面投影参数进行最小二乘估计,从而降低子相机摄影中心与球面投影中心不重合及场景深度变化对MPC球面全景视频输出质量影响。②MPC球面全景视频生成TPS模型构建。以MPC子摄像机视频像素球面重投影几何为全局变换、以视频拼接线上同名像点为控制点建立TPS模型,实现MPC各子摄像机视频到球面拼接视频的像素直接映射,并能最小化视频重叠区域像素拼接误差,仅通过拼接线附近像素简单混合即可消除视差伪影并实现平滑过渡。模拟成像及实际场景试验结果表明,结合场景内容与摄像机内、外参数,本文方法可实现MPC球面全景视频无缝生成且计算简单、高效,完全满足MPC高帧率视频输出要求,具有良好的应用价值。  相似文献   

16.
由不同时相和不同传感器所导致的遥感数据非一致性是定量监测地表长期变化所必须面对的一个重要问题。用于消减遥感数据非一致性的归一化辐射校正和传感器交叉定标,多采用统计方法,难以满足定量遥感发展的需求。本文针对MODISL1B光学波段产品数据,推导了不同时相非变像元灰度值(SI)之间的数学表达式,并利用MODIS的可见光-短波红外波段L1B数据对该定量关系进行了验证。研究表明,在可见光-短波红外波段,L1B非变像元在不同时相间的定量关系分为乘性和加性两部分,主要与太阳光照条件、大气状态以及传感器自身等变化因素有关。虽然基于MODIS非变像元时相关系的检验结果与理想状态下的结果存在偏差,但总体趋势仍然较好。  相似文献   

17.
张猛  曾永年 《遥感学报》2018,22(1):143-152
植被净初级生产力NPP(Net Primary Production)遥感估算与分析,有赖于高时空分辨率的遥感数据,但目前中高分辨率的遥感数据受卫星回访周期及天气的影响,在中国南方地区难以获取连续时间序列的数据,从而影响了高精度的区域植被净初级生产力的遥感估算。为此,提出一种基于多源遥感数据时空融合技术与CASA模型估算高时空分辨率NPP的方法。首先,利用多源遥感数据,即Landsat8 OLI数据与MODIS13Q1数据,采用遥感数据时空融合方法,获得了时间序列的Landsat8 OLI融合数据;然后,基于Landsat8 OLI时空融合数据,并采用CASA模型,以长株潭城市群核心区为例,进行区域植被NPP的遥感估算。研究结果表明,基于时间序列Landsat融合数据估算的30m分辨率的NPP具有良好的空间细节信息,且估算值与实测值的相关系数达0.825,与实测NPP数据保持了较好的一致性。  相似文献   

18.
张猛  曾永年  朱永森 《遥感学报》2017,21(3):479-492
以洞庭湖流域为研究区,对大范围湿地信息遥感提取方法进行了研究。先基于时间序列MODIS EVI及物候特征参数,通过J-M(Jeffries-Matusita distance)距离分析,构建了MODIS(250 m)最佳时序组合分类数据;其次,通过Johnson指数确定了最佳分割尺度,采用面向对象的遥感分类方法(Random tree分类器)提取了洞庭湖流域的湿地信息,并验证该方法的适用性。研究结果表明,基于时序数据与面向对象的Random tree分类的总体精度和Kappa系数分别为78.84%和0.71,较之基于像元的相同算法的总体分类精度和Kappa系数分别提高了5.79%和0.04。同时,基于面向对象方法的湿地整体的用户精度与生产者精度较基于像元方法分别提高了4.56%和6.21%,可有效提高大区域湿地信息提取的精度。  相似文献   

19.
In Africa, food security early warning systems use satellite-derived data concerning crop conditions and agricultural production. Such systems can be improved if they are provided with a more reliable estimation of the cultivated area at national scale. This paper evaluates the potential of using time series from the MODerate resolution Imaging Spectroradiometer MOD13Q1 (16-day composite of normalized difference vegetation index at 250 m resolution) to extract cultivated areas in the fragmented rural landscapes of Mali. To this end, we first stratified Southern Mali into 13 rural landscapes based on the spatio-temporal variability of NDVI and textural indices, using an object-oriented classification scheme.The accuracy of the resulting map (MODIScrop) and how it compares with existing coarse-resolution global land products (GLC2000 Africa, GLOBCOVER, MODIS V05 and ECOCLIMAP-II), was then assessed against six crop/non-crop maps derived from SPOT 2.5 m resolution images used as references. For crop areal coverage, the MODIScrop cultivated map was successful in assessing the overall cultivated area at five out of the six validation sites (less than 6% of the absolute difference), while in terms of crop spatial distribution, the producer accuracy was between 33.1% and 80.8%. This accuracy was linearly correlated with the mean patch size index calculated on the SPOT crop maps (r2 = 0.8). Using the Pareto boundary as an accuracy assessment method at the study sites, we showed that (i) 20-40% of the classification crop error was due to the spatial resolution of the MODIS sensor (250 m), and that (ii) compared to MODIS V05, which otherwise performed better than the other existing products, MODIScrop generally minimized omission-commission errors. A spatial validation of the different products was carried out using SPOT image classifications as reference. In the corresponding error matrices, the fraction of correctly classified pixels for our product was 70%, compared to 58% for MODIS V05, while it ranged between 40% and 51% for the GLC2000, the ECOCLIMAP-II and the GLOBCOVER.  相似文献   

20.
带锐度保持的斜投影B-样条图像缩放   总被引：11，自引：0，他引：11  
吴均  朱重光 《遥感学报》2002,6(2):108-112
基于B－样条的图像缩放相对于传统图像缩放方法（最近邻点、双线性、双三次等）的优势性在诸多文献和实验中得到了印证。但基于插值的B－样条的传统方法一样，没有考虑信息损失问题，是一种次优方法。为此Unser提出正交B－样条，并从理论上证明了其最优性。由于正交B－样条的采样池数在阶数大于3时难于获取，Lee发展易于计算且保持了相当精度的斜投影B－样条。B－样条良好的连续性使图像的边缘在缩放过程中被模糊了。为了克服这一问题，提出了带锐度保持的斜投影B－样条缩放，在缩放过程中利用B－样条的递推性质对存在一阶或二阶微分过零（即有小边缘）的采样区间缩小其积分范围至边缘附近，从而达到保持锐度的目的。实验结果表明该方法在保持缩放图像的连续性、清晰度方面都具有良好的效果。  相似文献   

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