A modern robust approach to remotely estimate chlorophyll in coastal and inland zones

The chlorophyll concentration of a water body is an important proxy for representing the phytoplankton biomass. Its estimation from multi or hyper-spectral remote sensing data in natural waters is generally achieved by using (i) the waveband ratioing in two or more bands in the blue-green or (ii) by using a combination of the radiance peak position and magnitude in the red-near-infrared (NIR) spectrum. The blue-green ratio algorithms have been extensively used with satellite ocean color data to investigate chlorophyll distributions in open ocean and clear waters and the application of red-NIR algorithms is often restricted to turbid productive water bodies. These issues present the greatest obstacles to our ability to formulate a modern robust method suitable for quantitative assessments of the chlorophyll concentration in a diverse range of water types. The present study is focused to investigate the normalized water-leaving radiance spectra in the visible and NIR region and propose a robust algorithm (Generalized ABI, GABI algorithm) for chlorophyll concentration retrieval based on Algal Bloom index (ABI) which separates phytoplankton signals from other constituents in the water column. The GABI algorithm is validated using independent in-situ data from various regional to global waters and its performance is further evaluated by comparison with the blue-green waveband ratios and red-NIR algorithms. The results revealed that GABI yields significantly more accurate chlorophyll concentrations (with uncertainties less than 13.5%) and remains more stable in different waters types when compared with the blue-green waveband ratios and red-NIR algorithms. The performance of GABI is further demonstrated using HICO images from nearshore turbid productive waters and MERIS and MODIS-Aqua images from coastal and offshore waters of the Arabian Sea, Bay of Bengal and East China Sea.     

国外高光谱遥感载荷发展分析

高光谱遥感是当前遥感领域发展的前沿。首先介绍了高光谱遥感的成像原理、典型成像方式及主要特点等基础理论,之后从机载和星载两个方面,系统梳理了美国、加拿大、欧洲、日本等主要国家高光谱遥感载荷的发展现状,分析了相关载荷的主要性能指标(以空间分辨率、频谱分辨率等为代表),总结、归纳了高光谱遥感在民用商用、国防安全及行星探测三个领域中的应用情况,最后从提升分辨率、优化探测模式及实现小型化三个方面,总结了高光谱遥感载荷的发展趋势。     

Assessment of the impact of dimensionality reduction methods on information classes and classifiers for hyperspectral image classification by multiple classifier system

Identification of the appropriate combination of classifier and dimensionality reduction method has been a recurring task for various hyperspectral image classification scenarios. Image classification by multiple classifier system has been evolving as a promising method for enhancing accuracy and reliability of image classification. Because of the diversity in generalization capabilities of various dimensionality reduction methods, the classifier optimal to the problem and hence the accuracy of image classification varies considerably. The impact of including multiple dimensionality reduction methods in the MCS architecture for the supervised classification of a hyperspectral image for land cover classification has been assessed in this study. Multi-source airborne hyperspectral images acquired over five different sites covering a range of land cover categories have been classified by a multiple classifier system and compared against the classification results obtained from support vector machines (SVM). The MCS offers acceptable classification results across the images or sites when there are multiple dimensionality reduction methods in addition to different classifiers. Apart from offering acceptable classification results, the MCS indicates about 5% increase in the overall accuracy when compared to the SVM classifier across the hyperspectral images and sites. Results indicate the presence of dimensionality reduction method specific empirical preferences by land cover categories for certain classifiers thereby demanding the design of MCS to support adaptive selection of classifiers and dimensionality reduction methods for hyperspectral image classification.     

A novel method for destriping of OCM-2 data and radiometric performance analysis for improved ocean color data products

Despite the capability of Ocean Color Monitor aboard Oceansat-2 satellite to provide frequent, high-spatial resolution, visible and near-infrared images for scientific research on coastal zones and climate data records over the global ocean, the generation of science quality ocean color products from OCM-2 data has been hampered by serious vertical striping artifacts and poor calibration of detectors. These along-track stripes are the results of variations in the relative response of the individual detectors of the OCM-2 CCD array. The random unsystematic stripes and bandings on the scene edges affect both visual interpretation and radiometric integrity of remotely sensed data, contribute to confusion in the aerosol correction process, and multiply and propagate into higher level ocean color products generated by atmospheric correction and bio-optical algorithms. Despite a number of destriping algorithms reported in the literature, complete removal of stripes without residual effects and signal distortion in both low- and high-level products is still challenging. Here, a new operational algorithm has been developed that employs an inverted gaussian function to estimate error fraction parameters, which are uncorrelated and vary in spatial, spectral and temporal domains. The algorithm is tested on a large number of OCM-2 scenes from Arabian Sea and Bay of Bengal waters contaminated with severe stripes. The destriping effectiveness of this approach is then evaluated by means of various qualitative and quantitative analyses, and by comparison with the results of the previously reported method. Clearly, the present method is more effective in terms of removing the stripe noise while preserving the radiometric integrity of the destriped OCM-2 data. Furthermore, a preliminary time-dependent calibration of the OCM-2 sensor is performed with several match-up in-situ data to evaluate its radiometric performance for ocean color applications. OCM-2 derived water-leaving radiance products obtained after calibration show a good consistency with in-situ and MODIS-Aqua observations, with errors less than the validated uncertainties of ±5% and ±35% endorsed for the remote-sensing measurements of water-leaving radiance and retrieval of chlorophyll concentrations respectively. The calibration results show a declining trend in detector sensitivity of the OCM-2 sensor, with a maximum effect in the shortwave spectrum, which provides evidence of sensor degradation and its profound effect on the striping artifacts in the OCM-2 data products.     

多敏感器联邦SSUKF融合姿态确定算法

针对四元数姿态估计问题,提出了一种分布式非线性滤波融合结构。通过引入基于超球面分布采样点变换(SSUT)技术的无迹卡尔曼滤波算法(SSUKF),以较低的计算量实现了高数据更新率、高精度的非线性滤波,并通过融合重构,保障系统无间断可靠工作,不受敏感器故障、视场盲区等因素影响。应用该算法对陀螺、磁强计、太阳敏感器、星敏感器构成的系统进行了具体设计并开展仿真研究,验证了算法的有效性。     

An object-level strategy for pan-sharpening quality assessment of high-resolution satellite imagery

Current satellite imaging systems offer a trade-off between high spatial and high spectral resolution providing panchromatic images at a higher spatial resolution and multispectral images at a lower spatial resolution but rich in spectral information while a wide range of applications need the highest level of this information, simultaneously. Image fusion techniques as means of enhancing the information content of initial panchromatic and multispectral images produce new images, titled pan-sharpened, which inherent the advantages of the initial images. Considering the impact of fusion accuracy on the quality of corresponding applications, it is necessary to evaluate the quality of these processed images. During the last decade, a lot of quality evaluation metrics have been proposed which are mostly inspired by traditional image quality metrics. These methods are mostly based on applying quality metrics at the pixel level and evaluating final quality value based on averaging of obtained metric values through the whole image. However, obtained results clearly show that the behaviour of image fusion quality is inconsistent amongst different image objects. In this article, by applying image fusion quality metrics (IFQMs) to image objects, an object-level strategy for quality assessment of the image fusion process is proposed. The proposed strategy is applied to different satellite imagery covering residential and agricultural areas. Experimental results show higher capabilities of object-level quality assessment strategy in the quality assessment of the fusion process. Evaluating fusion quality at the object level provides the potential of fusion quality assessment for each individual image object in compliance with different parameters such as the type of objects and the effective size of objects in data set.     

高光谱遥感地形影响建模与仿真

针对地形起伏对高光谱遥感图像几何变形和辐射变化的影响,建立高光谱遥感地形影响模型.该模型利用传感器位置、姿态和视场角建立模拟图像像元坐标和地面空间坐标之间的成像几何关系,利用地表反射率、数字高程模型等数据,考虑大气辐射传输过程,计算起伏地形下传感器入瞳辐亮度图像,并经过空间分辨率转换,生成最终遥感模拟图像,实现高光谱遥感地形影响精确建模.利用西藏驱龙地区Hyperion数据和其它相关数据进行仿真分析,将模拟图像和原始图像进行对比,结果比较吻合,表明该模型具有较好的模拟效果.     

Estimation of sediment settling velocity in estuarine and coastal waters using optical remote sensing data

A robust method has been developed for estimating sediment settling velocity (w_s) from high resolution optical remote sensing data in estuarine, coastal and harbor waters. This method estimates settling velocity as a function of the drag coefficient (C_d), Reynolds number (Re), grain size (D₅₀), specific gravity (Δ_SG) and grain shape (in terms of the Corey Shape Factor – CSF). These parameters were derived from the particulate inherent optical properties such as backscattering (b_bp), beam attenuation (c_p), suspended sediment concentration and turbidity using Landsat 8 OLI and HICO data. Preliminary results for the Gulf of Cambay in the eastern Arabian Sea and Yangtze river estuary in the East China Sea, showed that satellite-retrieved settling velocities (m?s^?1) varied from very low values in clear oceanic waters, intermediate values in coastal waters, to very high values in river plumes and sediment-laden coastal waters. The remote sensing retrievals of sediment properties and their settling velocities were generally consistent with the field and laboratory results, which indicate that the proposed methodology will have important implications in various coastal engineering, environmental and management studies.     

Spatial and temporal scales of the Brazil–Malvinas Current confluence documented by simultaneous MODIS Aqua 1.1-km resolution SST and color images

The moderate resolution imaging spectroradiometer (MODIS) on board the Aqua satellite measures visible and infrared radiation in 36 wavebands, providing simultaneous images of sea-surface temperature (SST) and chlorophyll-a (chl-a) concentration in the upper meters of the sea. For the first time, truly synoptic SST and chl-a- concentration images are available. These images are daily and of 1.1-km resolution.The strong contrasts in sea-surface temperature and surface chlorophyll-a concentration over the southwest Atlantic make satellite infrared and color images particularly appropriate tools for studying the Brazil–Malvinas (B/M) Current confluence. We examine two years (July, 2002–June, 2004) of Aqua/MODIS infrared and color images to document the precise structure of the B/M confluence simultaneously in SST and chl-a.We first compared MODIS weekly data with simultaneous independent satellite data. Spatial and temporal distributions are similar for both SST and color. Differences between MODIS and SeaWiFS (sea-viewing wide field-of-view sensor) are large in pigment-rich regions along the coast and shelf. Here, we focused on the offshore region where differences are small.For each season, exceptionally cloud-free 1.1-km resolution MODIS images showed two thermal fronts, one corresponding to the Brazil Current’s southernmost limit, the other, to the Malvinas Current’s northernmost limit. These two fronts remained quite close to each other (within 50 km) and were separated by water with an SST and chl-a concentration typical of the continental shelf waters. In spring, the water rich in chl-a from the platform is squeezed between the two currents and entrained away from the coast in between the two thermal fronts. In the frontal region, SST gradient maxima trace the contour of the chl-a-rich water.Enlargements of the frontal region and of the turbulent region downstream of the frontal collision are presented and analyzed. MODIS documents in an unprecedented way the SST and chl-a filaments as they are distorted and mixed by meso- and sub-mesoscale structures in the strain-dominated region of the B/M confluence. It is suggested that a substantial part of the chl-a local maximum in the Malvinas return flow is of continental-shelf origin.     

高光谱成像技术的应用与发展

介绍了国外先进高光谱成像载荷发展情况和国内以高分五号载荷为代表的高光谱成像技术发展水平,凭借在光谱分辨率、空间分辨率、成像质量等方面取得的长足进步,广泛应用于资源勘探和环境监测等多个重要领域。分析了Offner结构和Dyson结构的推扫型成像仪的特点,提出未来凝视型成像方式的发展前景,并介绍了目前基于AOTF分光方法的中红外高光谱成像仪,实现了较好的光谱成像效果。     

成像光谱技术超谱图像分类研究现状与分析

超谱遥感图像由于其高光谱分辨率的特点正受到国外内的广泛关注，在解决了前期的辐射校正及定标等剖以及，超谱图像的推广应用是当务之急。超谱遥感图像的分类研究对农作物生长状况的监测、矿物的识别、海洋水色分析以及其他方面的许多应用都是很有价值的。文章概述了国内外在成像光谱技术方面的发展，并首次以像元的构成成分的.纯像元和混合像元的角度对分类方法进行了论述，对超谱图像分类技术研究现状的归纳和分析，旨在寻找突破点，加强此领域的研究力度。     

基于多种空间信息的高光谱遥感图像分类方法

在高光谱遥感图像分类方法中,空间特征和光谱特征的融合可以有效地改善分类效果。针对单一空间特征的信息表达不充分问题,提出了一种联合多种空间特征的高光谱图像空谱分类方法。利用超像素信息对分类结果进行后处理去掉椒盐噪声,并创造性地将超像素信息应用于分类前处理,提出了一种利用超像素信息对像素点的特征向量进行线性加权融合的方法。试验结果表明,所提方法的性能优于目前的通常方法。     

利用青海湖对FY—1C、FY—2B气象卫星热红外通道进行在轨辐射定标

介绍利用青海湖辐射校正场对FY－1C、FY2B气象卫星热红外通道进行在轨辐射定标，先用CE312野外热红外辐射计在水面测量水表辐亮度，再经大气订正传递到卫星入瞳处，大气订正包括大气吸收削弱和大气产生热发射影响，这两部分对卫星信号的贡献通过辐射传输模式MODTRAN37计算出来，同时进行CE312与卫星通道光谱响应匹配，最终得到卫星入瞳处的表观辐亮度，这个辐亮度与卫星通道的计数值得到该通道绝对定标系数。我们对两颗卫星进行了多次定标，结果表明利用青海湖进行的在轨定标与星上定标系数相差5％左右，相当于3K的亮温差。     

Fractal signatures for multiscale processing of hyperspectral image data

A multiscale approach to hyperspectral image data analysis using fractal signatures was proposed and implemented in the Interactive Data Language (IDL). For 2-D hyperspectral curves, fractal signature measures the changes in curve length with changing scale. Using NASA’s Earth Observing-1 (EO-1) Hyperion image from a study area near Denton, Texas, USA, the capabilities of fractal signatures in discriminating different land cover types were presented in three different ways: (1) fractal signature curves, (2) distances between fractal signatures, and (3) fractal signature images. The asymmetry in length measurement was found to be effective in handling hyperspectral curves obtained from Hyperion radiance data. The contribution of fractal signature images was shown through comparison of image classification results. The results from the Hyperion radiance data suggest that fractal signatures at certain scales can reveal important differences in land cover types.     

Substitution of satellite-based land surface temperature defective data using GSP method

Land surface temperature (LST) as an important environmental variable provides valuable information for earth environmental system modelling. Currently, LST is obtained through satellite thermal sensors at various spatial and temporal resolutions. Although spatially continuous satellite-based LST measurements are intended to overcome the shortcomings of sparse ground-based LST measurements, LST images often contain anomalous values due to the existence of clouds or sensor malfunctioning. The problem becomes more serious where the users deal with high spatial resolution characterized by low temporal resolution. This study examines the capability of a newly developed graph signal processing (GSP) method using two-dimensional single-date thermal data. For this purpose, four Landsat/TIRS datasets are analyzed. The data of five elliptical regions on thermal images are eliminated and then reconstructed through the GSP method and using the LST values of the enclosing rectangles containing the ellipsoids. The results indicate that the temperature variation determined by the GSP method generally conforms to the original image LST values. According to a correlation test conducted on the original image LST and those obtained through the GSP method, the values vary from 58% to 95%, which is an above-the-average rate (RMSE from 0.69 to 2.27). The statistical analysis of the original image LST in both the elliptical regions and the enclosing rectangles containing the ellipsoids indicates that an increase in the variance of LST data causes an increased error in the calculation of temperature by the GSP method, and vice versa. The results of the analysis of variance (ANOVA) and Duncan test indicated that an increase in the number of the non-zero spectral bins would result in increased RMSE values for all the dates and the regions. Moreover, the model errors were significant at the 0.05 level across all the image date and five elliptical study regions. Based on the results, the use of this method is recommended for the reconstruction of LST missing values, where dissimilarity of atmospheric conditions limits the use of other methods that depend on the time series data of various dates and a great deal of data calculation.     

Manifold structure preservative for hyperspectral target detection

A nonparametric method termed as manifold structure preservative (MSP) is proposed in this paper for hyperspectral target detection. MSP transforms the feature space of data to maximize the separation between target and background signals. Moreover, it minimizes the reconstruction error of targets and preserves the topological structure of data in the projected feature space. MSP does not need to consider any distribution for target and background data. So, it can achieve accurate results in real scenarios due to avoiding unreliable assumptions. The proposed MSP detector is compared to several popular detectors and the experiments on a synthetic data and two real hyperspectral images indicate the superior ability of it in target detection.     

空间目标在天基光学探测中的特性分析与仿真

分析了空间目标的分布及几何特性,研究了空间目标光学特性与天基探测系统、太阳以及目标自身参数的关系,提出了空间目标光学特性仿真的思路,建立的天基空间目标光学特性分析系统可以计算并绘制相对距离、太阳相位角及目标星等变化曲线.由于很难获取准确的空间目标实际光度数据,文中提出了对仿真结果的验证方法.通过对仿真结果的分析,得出了天基空间目标光学探测的特点,为天基光学探测和识别的研究提供了参考.      

Deramp range migration processing for space-borne spotlight synthetic aperture radar

The deramp range migration algorithm (DRMA) for space-borne spotlight synthetic aperture radar (SAR) is presented, which is based on the two-step algorithm and range migration algorithm. The presented algorithm combines the advantages of SPECAN algorithm and range migration algorithm. Firstly, the presented algorithm performs a bulk azimuth raw data compression to achieve a pixel spacing no larger than the expected azimuth resolution of the fully focused image. Therefore, the azimuth spectral folding phenomenon is overcome. Secondly, the residual and precise focusing of the synthetic aperture radar data is achieved by applying the range migration algorithm. The space-borne SAR focusing parameters’ computation is also described in the paper. At the end of this paper, results are presented which confirm the validity of the presented algorithm.     

基于多重分形参数的高光谱数据特征提取

针对单一分形维数不能表征高光谱数据光谱局部吸收特征的问题,提出了基于光谱概率测度的多重分形参数特征提取方法.基于光谱信息度量进行光谱概率测度的计算,基于配分函数法估计得到尺度函数;通过对尺度函数求导计算出Holder指数,并对尺度函数勒让德Legendre变换计算出多重分形谱;从多重分形谱和Holder指数之间的函数关系提取表征多重分形谱形态的4个多重分形谱参数作为光谱特征参数;并应用于基于最小距离准则的航空推扫式高光谱成像仪(PHI,Prush-broom Hyperspectral Imager)图像监督分类.结果证明:利用基于光谱概率测度的多重分形参数特征提取方法提取的光谱特征参数进行分类得到的总体分类正确率达94.789%,分类精度明显高于利用信息量维数和多重分形谱特征提取方法进行分类的结果,证明了基于光谱概率测度的多重分形参数特征提取方法提取的多重分形参数的有效性和可靠性.