中巴地球资源02星CCD图像的大气校正研究

利用LANDSAT-5的专题制图仪(TM)对中巴地球资源卫星(CBERS)-02的CCD1～4波段进行交叉定标,得到了CCD1～4波段的参考定标系数。利用该定标系数并应用气象数据和ATCOR3软件对CBERS-02的CCD数据进行大气校正;对比大气修正前后图像的清晰度和归一化的植被指数。结果表明,大气校正增强了图像的对比度,归一化植被指数(NDVI)的均值明显提高,增大了高植被覆盖区与低植被覆盖区NDVI的差别,植被信息更加突出。对于山区崎岖地表状况下,大气校正后,山体的棱角分明,轮廓清晰可见,还原了下垫面的原貌,有利于遥感信息的提取。     

CBERS-2 CCD相机绝对辐射定标系数验证与评价

卫星遥感器绝对辐射定标系数的有效性检验，是对卫星遥感精度进行全面评价的最有效手段之一。利用绝对辐射定标系数反演反射率值与实测值对比的方法，对CBERS-2CCD相机绝对辐射定标结果进行了有效性检验与误差分析，根据分析结果对CCD相机4个波段的绝对辐射定标系数作出了客观的评价。验证表明，两点法获得的CCD相机定标系数可靠，定标效果较好，而单点法获得的定标系数对CCD相机不适用。     

归一化阴影植被指数NSVI的构建及其应用效果

以ALOS AVNIR-2、CBERS-02B CCD、HJ1A-CCD2、Landsat 7 ETM四幅中分辨率遥感影像为试验数据,分析明亮区植被、阴影区植被与水体区的光谱特征与差异,基于近红外波段与归一化植被指数NDVI,构建归一化阴影植被指数NSVI,并评价其光谱差异增强及分类效果.结果表明,NSVI大幅扩大了明亮区植被、阴影区植被、水体区间的光谱相对差异,降低光谱混淆概率;利用NSVI阈值法对四幅试验影像进行分类,总精度均大于97%,总Kappa在0.96以上,且阴影区植被的检测精度均在94%以上,总Kappa系数亦高于0.96.该指数利用地物在近红外波段的辐射差异,解决NDVI只能部分削弱地形影响的问题,扩大地物间的光谱差异,从而提升地物尤其是阴影检测的有效性,且不存在NDVI“易饱和”问题,可为遥感影像阴影去除提供一种新的解决方案.     

归一化阴影植被指数NSVI的构建及其应用效果（英文）

以ALOS AVNIR-2、CBERS-02B CCD、HJ1A-CCD2、Landsat 7 ETM四幅中分辨率遥感影像为试验数据,分析明亮区植被、阴影区植被与水体区的光谱特征与差异,基于近红外波段与归一化植被指数NDVI,构建归一化阴影植被指数NSVI,并评价其光谱差异增强及分类效果.结果表明,NSVI大幅扩大了明亮区植被、阴影区植被、水体区间的光谱相对差异,降低光谱混淆概率;利用NSVI阈值法对四幅试验影像进行分类,总精度均大于97%,总Kappa在0.96以上,且阴影区植被的检测精度均在94%以上,总Kappa系数亦高于0.96.该指数利用地物在近红外波段的辐射差异,解决NDVI只能部分削弱地形影响的问题,扩大地物间的光谱差异,从而提升地物尤其是阴影检测的有效性,且不存在NDVI"易饱和"问题,可为遥感影像阴影去除提供一种新的解决方案.     

大气校正对几种MODIS植被指数影响的分析

利用NASA—ESE提供的算法和代码对EOS/MODIS进行大气校正计算,得到CH1-CH7的地面反射率。再分别用大气校正前后的表观反射率和地面反射率数据计算三种常见植被指数(RVI、NDVI、NDVIg),分析三种植被指数在大气校正前后的变化以及与季节、地物类型之间的关系。指出大气校正并未完全抵消RVI中气溶胶的影响,但在绿度低值区补偿明显；而NDVI和NDVIg从整体上部分补偿了大气影响,在气溶胶较厚或使用绿通道(NDVIg)时必须进行大气校正。     

大气校正对几种MODIS植被指数影响的分析

利用NASA—ESE提供的算法和代码对EOS／MODIS进行大气校正计算，得到CHl-CH7的地面反射率．再分别用大气校正前后的表观反射率和地面反射率数据计算三种常见植被指数（RVI、NDVI、NDVIg），分析三种植被指数在大气校正前后的变化以及与季节、地物类型之间的关系。指出大气校正并未完全抵消RVI中气溶胶的影响，但在绿度低值区补偿明显；而NDVI和NDVIg从整体上部分补偿了大气影响，在气溶胶较厚或使用绿通道（NDVIg）时必须进行大气校正。     

400-1000nm波段反演气溶胶光学厚度的暗像元法

从卫星遥感的角度来看,气溶胶的不确定性是可见一近红外遥感中大气校正的难点,从遥感数据本身来反演气溶胶参数,进而完成大气校正,一直是遥感研究的重点.针对可见一近红外波段大气辐射传输特点,提出了利用浓密植被红波段(660 nm)与近红外波段(830 nm)之间的线性关系反演气溶胶光学厚度的基于可见近红外波段的暗像元法,该方法主要思想是首先假设在清洁大气的条件下,利用MODTRAN辐射传输模型对遥感图像进行大气校正,以减少近红外波段大气的影响,再通过双层叠代法搜索浓密植被像元作为暗像元,根据红波段和近红外波段之间的线性关系通过近红外波段计算暗像元的红波段表观反射率,并反演气溶胶光学厚度.利用该方法对PHI航空高光谱图像进行了气溶胶光学厚度的反演,并给出了反演原理、步骤和误差分析.     

气溶胶散射对海洋水色遥感辐射偏振校正的影响

辐射偏振校正对具有相对较大偏振响应的海洋水色卫星遥感器(如Aqua MODIS)是十分必要的,可在一定程度上提高海洋水色信息提取的精度.目前, MODIS已经实现了业务化的辐射偏振校正,但其算法中忽略了气溶胶散射对大气顶辐射偏振分量的影响.利用海洋-大气耦合矢量辐射传输模型PCOART,分别模拟获得纯瑞利大气(无气溶胶)和气溶胶光学厚度为0.2大气时的大气顶辐射偏振分量.结果表明,除太阳耀斑区外,气溶胶散射对蓝光波段(443 nm)大气顶线偏振辐亮度的贡献很小,可以忽略不计,而对近红外波段(865 nm)大气顶线偏振辐亮度的贡献显著.此外,将PCOART数值模拟的大气顶瑞利散射辐射线偏振反射率与POLDER实际观测的大气顶线偏振反射率进行了比较,结果同样说明了气溶胶散射对蓝光波段(443 nm)大气顶线偏振反射率的贡献很小,而对近红外波段(865 nm).大气顶线偏振反射率的贡献显著.最后,在现有MODIS辐射偏振校正算法基础上,提出了考虑气溶胶散射的海洋水色卫星遥感辐射偏振校正算法,并利用POLDER实测的大气顶线偏振反射率对算法进行了检验,结果表明,无论是在443 nm波段,还是在865 nm波段,均比MODIS辐射偏振校正算法估算大气顶辐射偏振分量更接近POLDER实测结果.     

CBERS-2 CCD遥感图像辐射校正技术

在对CBERS-2卫星CCD遥感图像辐射校正技术进行深入研究的基础上,给出了图像的0级预处理、传感器标定、大气辐射校正、照度校正等技术方法。在0级图像预处理方面,提出了利用测试数据来解决拼接区的辐射失真问题,并提出一种新的条纹检测技术;传感器的标校方面,讨论了底电平和非均匀性的消除方法;大气辐射校正采用回归分析法和直方图法;给出了太阳高度和地形坡度的照度校正方法与技术。     

基于短波红外波段的Ⅱ类水体MODIS影像大气校正算法

提出了一种基于短波红外(SWIR,short wave infrared)波段离水反射率为0的Ⅱ类水体大气校正算法.采用MODIS的1.240μm和1.640μm两个SWIR波段的反射率计算出了可见光及近红外(NIR, near infrared)波段气溶胶散射反射率,进而反演得到了这些波段的离水反射率.应用该算法对中国东部近海及湖泊的Ⅱ类水体进行了大气校正,并与实测数据和常用的大气校正算法进行了比较分析,结果表明该算法能够有效地去除大气的影响.     

基于辐照度法的场地辐射校正试验研究——场地同步观测仪器的比较

２０００年９月在敦煌辐射校正场用国内外两组仪器同时获取场地数据,经数据处理分析后,对中巴地球资源一号卫星ＣＣＤ相机进行了绝对辐射定标。本文通过对试验数据的结果比对和误差分析,证明国产仪器完全能满足对中巴地球资源一号卫星进行绝对辐射定标的精度要求。     

HJ-1A/B星CCD相机在轨辐射性能检测分析

为检测分析HJ-1A/B星CCD相机在轨辐射探测性能及其辐射定标的有效性,提出了基于多种光学特性地面目标的在轨检测方法。首先,介绍了HJ-1A/B星CCD相机在轨辐射性能检测方法,并基于2013年HJ-1A/B卫星地面同步观测试验数据,获取了HJ-1A/B星过境时刻的卫星入瞳处等效辐亮度。然后以该等效辐亮度为基准,对HJ-1A/B星CCD相机历次在轨辐射定标结果进行检验,分析HJ-1A/B星CCD相机的在轨运行期间辐射探测性能变化趋势。结果表明：HJ-1A/B星在轨运行过程中,辐射性能在不断发生变化;在轨运行5年多时间里,HJ-1A/B星的CCD相机各波段的辐射性能平均衰变量最低为3.7%,最大为39.6%;为保证遥感数据的定量化精度,定期的在轨绝对辐射定标十分必要。     

Estimation of the ratio of sensor degradation between NOAA AVHRRchannels 1 and 2 from monthly NDVI composites

Vegetation monitoring, based on the normalized difference vegetation index (NDVI) calculated from the Advanced Very High Resolution Radiometer (AVHRR) channels 1 and 2 data, requires continuous updates of calibration coefficients to correct for the sensor degradation in these channels. A method was developed to estimate calibration coefficients with monthly composited NDVI data from desert targets without recourse to the component channels 1 and 2 data. The method was tested on NDVI data from the AVHRR onboard the NOAA-7, -9, and -11 satellites for the period from 1982 until 1993. The results of the method outlined in this paper correlated high r, between 0.94 and 0.95, with the results from other studies that estimated sensor degradation for the individual AVHRR bands     

Bidirectional NDVI and atmospherically resistant BRDF inversion for vegetation canopy

The normalized difference vegetation index (NDVI) has been widely applied in optical remote sensing. However, it has been demonstrated that NDVI is still partially affected by atmospheric path scattering and bidirectional (illumination and viewing geometry) effects. In this paper we present the benefit of using a bidirectional NDVI, and we discuss the problems in using the maximum NDVI composite method. Based on the assumption that a clear day has a larger NDVI value and a cloudy day has a smaller NDVI value (smaller reflectance in the near-infrared band and larger reflectance in red band due to atmospheric path scattering), the ratio of squared observed NDVI values and calculated NDVI values is used as a weight in our inversion method. The calculated NDVI values are derived from previously inverted bidirectional reflectance distribution functions (BRDFs). The inversion process will loop until all weights converge. Our research on the early Terra/MODIS data using a semiempirical kernel-driven BRDF model (the RossThick-LiTransit model) shows that this new method can improve inversion results whenever some cloudy pixels are not filtered out. As cloud detection and subpixel cloudiness are always a problem, this technique should still be very useful in improving the quality of BRDF inversion.     

Sun and view angle corrections on reflectances derived fromNOAA/AVHRR data

A new method is proposed for the reduction of the noise-like fluctuations associated with variations of Sun-target-sensor geometry in multitemporal AVHRR data in the visible and near-infrared bands. Its principle is to adjust, over a monthly period, a three-parameter model of surface bidirectional reflectance on a time series of cloud-free atmospherically corrected AVHRR data. One parameter of the model represents the surface reflectance corrected for angular effects. Time profiles of corrected reflectances are obtained by making the monthly period slide over the annual vegetation cycle. This procedure is applied to an annual cycle of AVHRR data on seven test sites in France representative of bare soils, agricultural crops, and forested thematic areas. The method is evaluated according to two criteria, which are the ability of the bidirectional reflectance model to reduce the amount of noise-like temporal fluctuations of AVHRR data, and the stability of the retrieved parameters when random noise is artificially added to the original AVHRR data set. The perturbations induced by the coupling between diffuse sky radiance effects and the non-Lambertian behavior of ground reflectance are also discussed. The method is proved to give satisfactory results, and can potentially be used to compare satellite-derived reflectances obtained not only at different times, but also at different places and with different sensors     

A feedback based modification of the NDVI to minimize canopybackground and atmospheric noise

The Normalized Difference Vegetation Index (NDVI) equation has a simple, open loop structure (no feedback), which renders it susceptible to large sources of error and uncertainty over variable atmospheric and canopy background conditions. In this study, a systems analysis approach is used to examine noise sources in existing vegetation indices (VIs) and to develop a stable, modified NDVI (MNDVI) equation. The MNDVI, a closed-loop version of the NDVI, was constructed by adding 1) a soil and atmospheric noise feedback loop, and 2) an atmospheric noise compensation forward loop. The coefficients developed for the MNDVI are physically-based and are empirically related to the expected range of atmospheric and background “boundary” conditions. The MNDVI can be used with data uncorrected for atmosphere, as well as with Rayleigh corrected and atmospherically corrected data. In the field observational and simulated data sets tested, the MNDVI was found to considerably reduce noise for any complex soil and atmospheric situation. The resulting uncertainty, expressed as vegetation equivalent noise, was ±0.11 leaf area index (LAI) units, which was 7 times less than encountered with the NDVI (±0.8 LAI). These results indicate that the MNDVI may be satisfactory in meeting the need for accurate, long term vegetation measurements for the Earth Observing System (EOS) program     

Atmospheric correction against algorithm for NOAA-AVHRR products:theory and application

Investigation of the effect of atmospheric constituents on NOAA Advanced Very High Resolution Radiometer (AVHRR) visible and near-infrared data is presented. The general remote sensing equation, including scattering, absorption, and bidirectional reflectance effects for the AVHRR solar bands, is described. The magnitude of the atmospheric effects for AVHRR solar bands with respect to their impact on the normalized difference vegetation index (NDVI) and the surface bidirection reflectance is examined. Possible approaches for acquiring atmospheric information are discussed, and examples of atmospheric correction of surface reflectance and NDVI are given. Invariant effects (ozone absorption and molecular scattering) and variant effects (water vapor absorption and aerosol scattering) are shown to dominate the atmospheric effects in the AVHRR solar bands