Landsat-8卫星数据应用探讨

在过去的40年里,Landsat系列卫星对启蒙和推动遥感应用技术的发展起到了重要作用,其遥感图像数据在我国得到了广泛应用.Landsat-8卫星是Landsat系列卫星的后续任务,已于2013年2月发射,目标是延续Landsat系列卫星数据的连续性,为农业、水资源管理、植被监测、灾害响应等领域继续提供高质量的图像数据.本文将首先介绍Landsat-8卫星的研制背景、卫星的基本参数和新型成像仪的数据特点,然后对比ETM+数据,介绍了Landsat-8卫星的数据产品分级以及数据的应用方向上的变化.     

Landsat-8姿态抖动对多光谱影像配准影响

鉴于遥感器姿态数据的准确性对影像几何定位的重要性,该文对Landsat-8卫星成像过程中,姿态抖动对多光谱影像配准的影响进行评价和分析。首先介绍了美国地质调查局(USGS)对Landsat-8卫星姿态抖动处理方法;其次,从Landsat-8陆地成像仪(OLI)的多光谱影像入手,基于蒙特卡洛数值模拟及Landsat-8真实影像,定量分析了姿态数据高频抖动对Landsat-8OLI数据波段间配准造成的误差;最后,通过模拟改变卫星姿态测量频率,进一步分析卫星抖动处理在不同频率时对抖动误差去除的适应性。Landsat-8卫星姿态抖动配准精度评估及处理方法的适应性分析,可为提高国产卫星姿态抖动处理能力及多光谱影像配准精度提供有益借鉴。     

基于Bumper Mode的Landsat-5数据图像校正与补偿算法设计与实现

2002年Landsat-5星上TM扫描仪出现了扫描装置同步问题,为此美国宇航局(NASA)调整了TM扫描仪的工作模式,消除了上述问题,但同时造成了图像数据正反扫描不能对齐和错行的问题。本文针对目前Landsat-5卫星Bumper Mode模式下出现的问题进行了详细分析,完成了快速几何校正和补偿的算法设计与软件实现。并通过对Landsat-5多轨零级图像和移动窗图像处理加以验证,获得了良好的效果。为同类遥感卫星传感器出现相似问题提供了一条简便、快速的解决途径。     

基于通用分裂窗算法和Landsat-8数据的地表温度反演研究

基于通用分裂窗算法和Landsat-8数据开展地表温度(Land Surface Temperature,LST)反演研究。首先,使用MODTRAN和SeeBor V5数据库开展辐射传输模拟,建立LST与Landsat-8热红外传感器(Thermal InfraRed Sensor,TIRS)第10(10.9μm)和11波段(12.0μm)观测亮温、地表比辐射率(Land Surface Emissivities,LSEs)、观测角度和总可降水量(Total Precipitable Water,TPW)之间的关系。其次,对模拟数据进行分组,用多元线性回归求解算法系数,并进行敏感性分析。然后,从经过交叉辐射定标的晴空Landsat-8数据反演得到LST,其中LSEs从Landsat-8陆地成像仪(Operational Land Imager,OLI)数据估算,TPW从欧洲中尺度天气预报中心再分析数据提取。最后,用Terra卫星中分辨率成像光谱仪的LST/比辐射率产品(MOD11_L2 V5)对反演结果进行验证。该算法能够较精确地从Landsat-8数据反演LST,主要误差源自LSEs和TPW的不确定性,对LSEs和TPW纠正前后的误差分别为-0.64±0.81K和0.10±0.68K。     

LANDSAT—7卫星的检错纠错系统

Landsat-7(陆地卫星－7）卫星继续保持了以前Landsat卫星飞行任务所创造的为用户提供地球遥感数据持续25年以上的记录,同时Landsat-7卫星大大提高了辐射测量和几何测量的性能。Landsat-7卫星公用舱的设计充分继续了DMSP／TIROS卫星系列的成功经验,在此基础上加以改进,延长了卫星自主安全运营的时间。本文介绍在传统设计的基础上增加的检错纠错（FDAC）设计功能,阐明FDAC系统方案的确定、技术实现和测试。这一设计的成果使得卫星在轨容错能力大大加强,很能确保卫星从故障状态下恢复正常运行。Landsat-7卫星的FDAC设计由3个主要检测单元和一个分层结构的纠正措施阵列组成。故障检测的基础就是所谓的冗余管理（REDMN）功能,这一功能连续监测所选定的卫星功能和性能参数,同时管理故障部件的切换,确保航天器工作状态正常和安全。Landsat－7卫星设计中所考虑的第二个关键功能称之为互连监视（ICMON）,这一功能利用加权的部件故障和性能的遥测数据来推断共用硬件的数据通道的异常,这些共同数据通道的异常本身按另一种方式表现为多部件故障。ICMON本质是通过切换备选的数据通道来替代REDMN功能,以避免同时切换多个部件。第三个检测功能是额外增加的一种遥测功能,称之为状态监视功能（SMON）,SMON增加了对FDAC各功能的可观测性,因而提高了地面应付星上故障事件的重构能力,促使卫星迅速恢复到正常工作状态。各种纠正措施均依赖部位的切换以及备份模式的切换,其中包括新增加一个保持姿态安全和能源安全的太阳指出姿态模式。     

卫星遥感数据分类不确定性的容差粗糙集处理

提出一种基于光谱特征邻域的容差粗糙集分类方法,用来处理卫星遥感数据分类中的不确定性问题。利用北京地区Landsat-5 TM数据进行分类试验,将结果与现有容差粗糙集方法分类结果进行对比和统计。结果表明,该方法具有良好的可理解性和稳定性,能够处理卫星遥感数据分类的不确定性,在具有复杂光谱特征地物分类方面具有发展潜力。     

卫星遥感计划的现状

目前,不少国家在发展卫星遥感系统。美国 NASA(国家航空与:航天局)1982年发射了 Landsat-4,该卫星传送由多光谱扫描仪和专题成象仪获取的高质量数据、航天飞机的多项飞行任务均预定配备部分遥感设备:合成孔径雷达、胶片摄影机与光电传     

Landsat-8卫星OLI成像仪调制传递函数在轨评测

鉴于传统调制传递函数(modulation transfer function,MTF)空间域分析结果受实验目标选择影响很大,应用EROS提出的频率域线状地物法对Landsat-8卫星OLI成像仪MTF进行在轨评测,并通过对比实验验证方法。基于目标和传感器特性分析,分别建立目标模型和系统传递函数模型,利用拟合数据求解模型参数,进而计算得到MTF值。并将EROS方法与传统T choi方法测得的MTF值进行对比。实验结果表明,EROS方法能有效应用于Landsat-8卫星OLI成像仪的MTF在轨测量,且明显减少了目标选择对于MTF评测结果的影响。     

广州市河网水体总悬浮物变化的遥感分析

悬浮物是指悬浮在水中的固体物质,它的含量是衡量水污染程度的指标之一,同时也是影响水体光学属性的主要指标之一。珠江是我国境内的第三长河流,包括东江、西江、北江等支流,汇合至广州河段然后进入南海。该研究基于高精度光学卫星遥感数据对珠江河网悬浮泥沙含量进行评价。利用5个航次现场实测的总悬浮物及水体光谱数据,建立了基于Landsat卫星的珠江河网总悬浮物浓度遥感反演模型,并使用Landsat-7与Landsat-8数据提取了1999—2014年珠江广州段河网总悬浮物浓度。研究发现,珠江广州段总悬浮物浓度自1999年开始增加,至2002年达到最高,2002年以后存在逐步降低的趋势。该研究成果可为决策部门及广大市民提供快速、高质量、可视化的水质变化信息。     

基于WRS-2的陆地卫星分景算法研究

WRS-2是为了便于陆地卫星数据的查询和管理而设计的一种全球参考系。本文深入研究了基于WRS-2参考系的2种分景算法WRSID1和WRSID2,比较分析了2种分景算法的异同,最后以Landsat-5为例分别实现2种算法并进行数据验证。通过研究和数据验证,发现WRSID2能显著减少高纬度地区的分景误差。该算法原理适用于美国陆地系列卫星,也能够为其他卫星地面系统的研制提供参考。     

Deriving land surface temperature from Landsat 5 and 7 during SMEX02/SMACEX

A sequence of five high-resolution satellite-based land surface temperature (T_s) images over a watershed area in Iowa were analyzed. As a part of the SMEX02 field experiment, these land surface temperature images were extracted from Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper (ETM) thermal bands. The radiative transfer model MODTRAN 4.1 was used with atmospheric profile data to atmospherically correct the Landsat data. NDVI derived from Landsat visible and near-infrared bands was used to estimate fractional vegetation cover, which in turn was used to estimate emissivity for Landsat thermal bands. The estimated brightness temperature was compared with concurrent tower based measurements. The mean absolute difference (MAD) between the satellite-based brightness temperature estimates and the tower based brightness temperature was 0.98 °C for Landsat 7 and 1.47 °C for Landsat 5, respectively. Based on these images, the land surface temperature spatial variation and its change with scale are addressed. The scaling properties of the surface temperature are important as they have significant implications for changes in land surface flux estimation between higher-resolution Landsat and regional to global sensors such as MODIS.     

Multi-temporal and multi-source cartography of the glacial cover of Nevado Coropuna (Arequipa,Peru) between 1955 and 2003

This study reports on the glacial cover evolution of the Nevado Coropuna between 1955 and 2003, based on Peruvian topographic maps and satellite images taken from the Landsat 2 and 5 multispectral scanner (MSS), Landsat 5 Thematic Mapper (TM) and Landsat 7 (ETM+). The normalized difference snow index has been applied to these images to estimate the glacierized area of Coropuna. The satellite-based results show that the glacier area was 105 ± 16 km² in 1975 (Landsat 2 MSS), which then reduced to 96 ± 15 km² in 1985 (Landsat 5 MSS), 64 ± 8 km² in 1996 (Landsat 5 TM) and 56 ± 6 km² in 2003 (Landsat 5 TM). Altogether, between 1955 and 2003, Coropuna lost 66 km² of its glacial cover, which represents a mean retreat of 1.4 km² year^?1, that is, a loss of 54% in 48 years (11% loss per decade). The maximum rate of retreat occurred during the 1980s and 1990s, a phenomenon probably linked with the pluviometric deficit of El Niño events of 1983 and 1992.     

针对TM6有效波长的计算方法及其对地温反演的影响研究

相对NOAA-AVHRR及MODIS的热波段而言,Landsat TM6有更高的空间分辨率;因而更适合于地面热力场分布特征及微环境研究的准确分析需要。有效波长的确定对反演地表温度有重要影响。本文根据Landsat5及Landsat7 TM6对波长的光谱响应函数(RSR),推导出相应的有效波长值并分析其对地温反演的影响。分析结果表明,一般情况下,就Landsat5而言,用中心波长反演地表温度不会有太大影响;但利用Landsat7反演地表温度时则必须使用有效波长,因为中心波长可能会导致较大的地表温度反演误差。     

Continuity of Landsat observations: Short term considerations

As of writing in mid-2010, both Landsat-5 and -7 continue to function, with sufficient fuel to enable data collection until the launch of the Landsat Data Continuity Mission (LDCM) scheduled for December of 2012. Failure of one or both of Landsat-5 or -7 may result in a lack of Landsat data for a period of time until the 2012 launch. Although the potential risk of a component failure increases the longer the sensor's design life is exceeded, the possible gap in Landsat data acquisition is reduced with each passing day and the risk of Landsat imagery being unavailable diminishes for all except a handful of applications that are particularly data demanding. Advances in Landsat data compositing and fusion are providing opportunities to address issues associated with Landsat-7 SLC-off imagery and to mitigate a potential acquisition gap through the integration of imagery from different sensors. The latter will likely also provide short-term, regional solutions to application-specific needs for the continuity of Landsat-like observations. Our goal in this communication is not to minimize the community's concerns regarding a gap in Landsat observations, but rather to clarify how the current situation has evolved and provide an up-to-date understanding of the circumstances, implications, and mitigation options related to a potential gap in the Landsat data record.     

Image Quality Assessment for Visual and Infrared Multis-pectral Imager of Gaofen-5

Gaofen-5(GF-5) satellite was successfully launched on May 29, 2018. The Visual and Infrared Multispectral Imager(VIMI) developed independently by China is a multi-spectral imager in the range of visible band to long-wave infrared band, which has broad application prospects. The quality assessment of satellite image is not only the verification of whether the remote sensing satellite meets the design criteria, but also the reference for image processing and application. In this paper, the quality assessment for VIMI is provided, which provides reference for the processing and application of the image. Four indicators, named the Signal-to-Noise Ratio (SNR), clarity, information content and radiation heterogeneity, were used for quality assessment, and were compared with Landsat 8 images. The results show that the SNR of the shortwave infrared band (320.44~388.42) is slightly higher than that of the visible near-infrared band(208.24~238.03). The clarity (0.82~0.91) in the near-shortwave infrared band is higher than that in the other bands, especially in the long-wave infrared band (0.01~0.21). The information content of short-wave infrared band (9.01~9.97) is higher than that of medium-long-wave infrared band (5.71~8.31). The radiation heterogeneity of all 12 bands is less than 2%. The results of comparison with Landsat 8 show that ①the clarity of B1~B4 is better than Landsat 8 and this of other bands are close to Landsat 8,②for information content, B1~B10 of VIMI is close to Landsat 8, while this of B11 and B12 is less than Landsat 8 with 5.23 for B11 and 5.61 for B12,(3)for SNR, GF-5 VIMI still needs to be further improved, with 280.41、226.84 and 151.92 less than Landsat 8 for B1,B2 and B6.     

高分五号全谱段光谱成像仪影像数据质量评价研究

高分五号卫星上搭载的我国自主研发的全谱段光谱成像仪是从可见光到长波红外光谱范围的星载多光谱成像仪,具有广泛的应用前景。对卫星影像进行质量评价,既是对遥感卫星是否满足设计指标的验证与检验,也可以为影像的处理与应用提供参考。利用信噪比、清晰度、信息量、辐射不均一性4个指标对高分五号全谱段光谱成像仪进行影像质量评价,并以美国陆地卫星Landsat 8影像为参考进行对比分析。结果表明:高分五号卫星全谱段光谱成像仪短波红外谱段的信噪比(320.44~388.42)略高于可见近红外谱段(208.24~238.03);近-短波红外谱段的清晰度(0.82~0.91)要高于其余谱段,尤其是长波红外谱段(0.01~0.21);可见短波红外谱段的信息量(9.01~9.97)要高于中长波红外谱段(5.71~8.31);所有12个谱段的辐射不均一性均小于2%。与Landsat 8的比较结果表明:在清晰度方面,全谱段光谱成像仪可见近红外谱段优于Landsat 8,其他谱段接近Landsat 8;在信息量方面,可见短波红外谱段与Landsat 8比较接近,但是B11、B12两个分裂窗谱段差距较大,分别相差5.23和5.61;在信噪比方面GF-5 VIMI仍有待进一步改善,又以B1、B2、B63个谱段落后Landsat 8最大,分别相差280.41、226.84和151.92。     

Evaluation of segment‐based gap‐filled Landsat ETM+ SLC‐off satellite data for land cover classification in southern Saskatchewan,Canada

This paper describes single‐date and multi‐date land‐cover classification accuracy results using segment‐based, gap‐filled Landsat 7 Enhanced Thematic Mapper data compared with Landsat 5 Thematic Mapper data captured one day apart. Maximum likelihood and Decision tree classification algorithms were evaluated. The same training and verification sets of ground data were used for each classification evaluation. For the comparison with the single‐date classification, an average decrease of 2.8% in the classification accuracy was obtained with the use of the gap‐filled Landsat data. Area estimates for the mid‐summer images differed, on average, from 0.6% to 1.9% for a four‐class and eight‐class classification, respectively. A multi‐date land‐cover classification was also completed with the addition of a late spring Landsat 5 image, resulting in an average decrease in classification accuracy of 1.8%.     

Cross-sensor comparisons between Landsat 5 TM and IRS-P6 AWiFS and disturbance detection using integrated Landsat and AWiFS time-series images

Routine acquisition of Landsat 5 Thematic Mapper (TM) data was discontinued recently and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) has an ongoing problem with the scan line corrector (SLC), thereby creating spatial gaps when covering images obtained during the process. Since temporal and spatial discontinuities of Landsat data are now imminent, it is therefore important to investigate other potential satellite data that can be used to replace Landsat data. We thus cross-compared two near-simultaneous images obtained from Landsat 5 TM and the Indian Remote Sensing (IRS)-P6 Advanced Wide Field Sensor (AWiFS), both captured on 29 May 2007 over Los Angeles, CA. TM and AWiFS reflectances were compared for the green, red, near-infrared (NIR), and shortwave infrared (SWIR) bands, as well as the normalized difference vegetation index (NDVI) based on manually selected polygons in homogeneous areas. All R ² values of linear regressions were found to be higher than 0.99. The temporally invariant cluster (TIC) method was used to calculate the NDVI correlation between the TM and AWiFS images. The NDVI regression line derived from selected polygons passed through several invariant cluster centres of the TIC density maps and demonstrated that both the scene-dependent polygon regression method and TIC method can generate accurate radiometric normalization. A scene-independent normalization method was also used to normalize the AWiFS data. Image agreement assessment demonstrated that the scene-dependent normalization using homogeneous polygons provided slightly higher accuracy values than those obtained by the scene-independent method. Finally, the non-normalized and relatively normalized ‘Landsat-like’ AWiFS 2007 images were integrated into 1984 to 2010 Landsat time-series stacks (LTSS) for disturbance detection using the Vegetation Change Tracker (VCT) model. Both scene-dependent and scene-independent normalized AWiFS data sets could generate disturbance maps similar to what were generated using the LTSS data set, and their kappa coefficients were higher than 0.97. These results indicate that AWiFS can be used instead of Landsat data to detect multitemporal disturbance in the event of Landsat data discontinuity.     

Assessing the potential of VEGETATION sensor data for mapping snow and ice cover: A Normalized Difference Snow and Ice Index

The VEGETATION (VGT) sensor in SPOT 4 has four spectral bands that are equivalent to Landsat Thematic Mapper (TM) bands (blue, red, near-infrared and mid-infrared spectral bands) and provides daily images of the global land surface at a 1-km spatial resolution. We propose a new index for identifying and mapping of snow/ice cover, namely the Normalized Difference Snow/Ice Index (NDSII), which uses reflectance values of red and mid-infrared spectral bands of Landsat TM and VGT. For Landsat TM data, NDSII is calculated as NDSII_TM=(TM3-TM5)/(TM3+TM5); for VGT data, NDSII is calculated as NDSII_VGT=(B2-MIR)/(B2+MIR). As a case study we used a Landsat TM image that covers the eastern part of the Qilian mountain range in the Qinghai-Xizang (Tibetan) plateau of China. NDSIITM gave similar estimates of the area and spatial distribution of snow/ice cover to the Normalized Difference Snow Index (NDSI=(TM2-TM5)/(TM2+TM5)) which has been proposed by Hall et al. The results indicated that the VGT sensor might have the potential for operational monitoring and mapping of snow/ice cover from regional to global scales, when using NDSII_VGT.     

Extension of retrospective datasets using multiple sensors. An approach to radiometric intercalibration of Landsat TM and MSS data

The establishment of monitoring frameworks for environmental problems is frequently based on retrospective, multi-temporal series of satellite images. The derivation of concise conclusions from these series largely depends on their quantitative consistency; hence, a completely standardized analysis of multi-temporal time series is mandatory. In the context of the required radiometric rectification, sensor calibration is an essential component, the accuracy of which largely determines the overall result. While for newer sensor systems extensive documentation on the development of the sensor's sensitivity exists, older systems often lack the corresponding information.A methodology has been developed, tested and validated to radiometrically intercalibrate different sensor systems based on the precondition of simultaneous image acquisition, which is for example provided by the Landsat TM and MSS sensor systems hosted on Landsat 5. Different interpolation and processing steps within the procedure have been analyzed, and an intercalibration scheme is proposed to derive Landsat MSS calibration factors from Landsat TM, which is used as a calibrated reference. It supports a full radiometric rectification of Landsat MSS data and enables their incorporation into satellite image time series, which can thus be significantly extended by a maximum of 12 years.