北京1号小卫星图像噪声评估

从理论和试验方面对图像的噪声评估方法进行了分析。结合北京1号小卫星特性, 进行了该类方法应用效能的评价, 讨论了分块评估噪声方法的最佳参数设置。选取满足噪声评估环境的图像, 实现了综合不同地表覆盖条件的北京1号小卫星图像噪声的评估。噪声评估结果与在轨测试情况的对比表明, 北京1号小卫星经过近3年的运行, 仍保持了较好的性能。     

北京1号小卫星图像噪声评估

从理论和试验方面对图像的噪声评估方法进行了分析。结合北京1号小卫星特性, 进行了该类方法应用效能的评价, 讨论了分块评估噪声方法的最佳参数设置。选取满足噪声评估环境的图像, 实现了综合不同地表覆盖条件的北京1号小卫星图像噪声的评估。噪声评估结果与在轨测试情况的对比表明, 北京1号小卫星经过近3年的运行, 仍保持了较好的性能。     

北京1号小卫星遥感器性能在轨测试

北京1号小卫星是中国第一颗实用型对地观测微小卫星,也是"国际灾难监测星座(DMC)"的第五颗星,该卫星于2005年10月27日在俄罗斯发射成功,设计寿命5年.在北京1号小卫星发射成功后,中英双方开始对卫星进行在轨测控和调试.在分析光学遥感器成像模型基础上,参考国际典型卫星在轨测试内容和北京1号卫星的特点,提出了北京1号小卫星在轨测试的内容、指标体系和技术方法,全面评价了北京1号小卫星的辐射性能、几何性能、光谱性能和图像综合质量,评价结果表明北京1号小卫星具有良好的性能.     

植被指数在“北京一号”数据耕地提取中的应用研究

本文旨在研究探讨适合我国最新发射的高性能对地观测"北京一号"小卫星影像中耕地提取方法。通过分析"北京一号"小卫星数据的波段特征,以山东曲阜多光谱图像为试验数据,计算典型的6种植被指数,在Erdas中建立模型,进行了耕地提取试验,并以灰度图像融合数据人工判读的结果作为参考数据,进行了精度评定。将适合"北京一号"小卫星数据的最佳植被指数提取模型应用于整个山东省的耕地提取中,得到修正植被指数提取模型,从而在"北京一号"小卫星数据耕地提取应用领域做了有效尝试。     

DMC遥感小卫星数据预处理方法分析

DMC遥感小卫星1G级数据产品虽然经过了波段配准、辐射校正和系统几何校正处理,但尚不能作为海啸灾害解译和评估的基础图像。为了满足图像解译和目标几何量测的要求,研究DMC小卫星数据产品中噪声、拼接缝以及色调不均匀去除的方法,以提高DMC小卫星图像质量。通过对其形成原因和特性进行分析,提出了消除噪声、拼接缝和几何精校正,以及制作色调一致的真彩色三维影像图的技术方法,并给出了具体示例。     

北京一号小卫星多光谱图像波段配准和图像变形评价

北京一号小卫星是中国和英国联合研制的一颗实用型、对地观测微小卫星，星上携带中分辨率32m多光谱（近红外、红和绿波段）和4m全色两种有效载荷。为了提高多光谱图像的宽度和时间分辨率，北京一号小卫星的每个多光谱波段都是由两个相机独立成像然后拼接而成。由于这种成像方式很难保证6个相机的主光轴平行，导致图像配准精度较低。针对北京一号小卫星的这种成像特点，本文在图像灰度交叉相关匹配的基础上，发展了一种高精度波段配准算法来评价北京一号小卫星的波段配准精度，并在波段配准的基础上，评价北京一号小卫星多光谱图像的变形一致性。     

结合分形理论和自适应图像块划分的遥感图像噪声估计

针对场景复杂的光学遥感图像中加性噪声估计问题,提出了一种结合分形理论和自适应图像块划分的噪声估计方法。区别于传统的基于规则图像块划分的噪声估计方法,本文提出了一种自适应于图像局部信息的图像块划分算法,更大程度地保证了自适应图像块内部的平滑性。结合基于分形理论的图像低粗糙度纹理区域选取和基于统计分析的图像噪声标准差计算,实现了光学遥感图像加性噪声强度的自动估计。利用资源三号卫星图像进行定量试验分析,试验结果表明本文方法可以有效地适用于不同复杂程度、不同噪声强度的光学遥感图像。同时,本文中低粗糙度纹理区域选取和自适应图像块划分的方法经过改进后,还可以应用于雷达图像中乘性噪声的估计。     

北京1号小卫星多光谱影像全国镶嵌技术与制图研究

北京1号小卫星在轨运行一年多成功接收了覆盖中国各个行政区域的多光谱影像数据,为全国数字镶嵌图的研究提供了丰富的数据资料.针对北京1号小卫星特点进行关键技术和方法研究,形成了北京1号小卫星多光谱影像全国范围数据获取任务测控优化模式,解决了北京1号小卫星多光谱数据预处理中去条带、波段自动配准、MTF复原处理等关键技术,系统地、全面地阐述了全国镶嵌图制作的技术流程和方法.     

对地观测小卫星的相位噪声分析与控制

结合传输型对地观测小卫星一体化设计的特点，介绍了一种用于对地观测小卫星系统的锁相接收机的-构成及原理，并对系统的相位噪声性能进行了详尽的分析，提出了对其相位噪声进行技术控制的方法。通过文中的分析与研究，消除了由于对地观测小卫星相位噪声所引起的系统误码率的恶化，提高了系统的可靠性，为下一步对地观测小卫星的发展与应用打下了良好的技术基础。     

对地观测小卫星的相位噪声分析与控制

结合传输型对地观测小卫星一体化设计的特点,介绍了一种用于对地观测小卫星系统的锁相接收机的构成及原理,并对系统的相位噪声性能进行了详尽的分析,提出了对其相位噪声进行技术控制的方法.通过文中的分析与研究,消除了由于对地观测小卫星相位噪声所引起的系统误码率的恶化,提高了系统的可靠性,为下一步对地观测小卫星的发展与应用打下了良好的技术基础.     

基于局部标准差的遥感图像噪声评估方法研究

局部均值与局部标准差法是目前应用最广泛的遥感图像噪声评估方法之一。该方法利用了局部均值与局部标准差的概念,对含有加性噪声的遥感图像进行噪声评估。但该方法受地物覆盖类型影响很大,当遥感图像中地物覆盖复杂时,会得到异常的噪声估算结果。产生这一现象的主要原因是遥感图像中包含边缘和纹理的不均匀子块。为降低地物覆盖复杂性对算法的影响,本文提出了基于边缘块剔出的局部均值与局部标准差法和基于高斯波形提取的局部均值与局部标准差法,前一种方法是削弱图像中包含边缘的不均匀子块的影响,后一种方法是提取反映均匀子块数量特征的高斯波形。利用同一次航空试验中获取的两幅AVIRIS辐射图像对改进后的算法进行了检验,结果表明改进后算法的健壮性明显提高,且噪声估算结果更准确。     

基于RS与GIS的密云县生态环境效应分析

北京一号小卫星数据和Landsat卫星TM/ETM+数据进行生态环境效应遥感分析。首先,对三期遥感影像进行解译得到土地利 用状况图,并分析了其变化情况; 然后,应用GIS技术,结合景观生态学的方法分析了景观结构变化; 利用RS技术分析了密云县 植被及地表温度; 最后,分析了不同土地利用和不同生态区划的NDVI和地表温度的变化特点。综合上面的分析,指出了RS与GIS方 法在城市生态环境分析方面的优势。     

Application of a New Symmetry-Based Cluster Validity Index for Satellite Image Segmentation

An important approach for image segmentation is clustering pixels based on their spectral properties. In particular, satellite images contain land cover types, some of which cover significantly large areas, while some (e.g., bridges and roads) occupy relatively much smaller regions. Automatically detecting regions or clusters of such widely varying sizes presents a challenging task. In this letter, a symmetry-based cluster validity index, named Sym-index (Symmetry distance-based index), is proposed. It is able to correctly indicate the presence of clusters of different sizes as long as they are internally symmetrical. A genetic-algorithm-based clustering technique that optimizes the Sym-index is used for image segmentation where the number of clusters is determined automatically. The superiority of the proposed index, as compared to other indices, is established for automatically segmenting the land cover types from SPOT and Indian Remote Sensing satellite images of two different cities in India.     

利用区域辐射特性优化获取光学遥感数据

通过分析成像过程及其影响因素,提出了对成像积分时间进行控制的优化成像方法。首先建立成像参数模型,探讨了模型参数计算、成像过程中模型参数的选择,分析了图像后处理问题,并利用北京一号小卫星进行了遥感数据优化获取实验。实验结果表明,根据地物特性进行成像参数优化后获取的图像具有更宽的动态范围和更高的辐射分辨率,信息量和信噪比也大幅增强。     

Contribution of multispectral (optical and radar) satellite images to the classification of agricultural surfaces

The monitoring of different crops (cultivated plots) and types of surface (bare soils, etc.) is a crucial economic and environmental issue for the management of resources and human activity. In this context, the objective of this study is to evaluate the contribution of multispectral satellite imagery (optical and radar) to land use and land cover classification.Object-oriented supervised classifications, based on a Random Forest algorithm, and majority zoning post-processing are used. This study emerges from the experiment on multi-sensor crop monitoring (MCM'10, Baup et al., 2012) conducted in 2010 on a mixed farming area in the southwest of France, near Toulouse. This experiment enabled the regular and quasi-synchronous collection of multi-sensor satellite data and in situ observations, which are used in this study. 211 plots with contrasting characteristics (different slopes, soil types, aspects, farming practices, shapes and surface areas) were monitored to represent the variability of the study area. They can be grouped into four classes of land cover: 39 grassland areas, 100 plots of wheat, 13 plots of barley, 20 plots of rapeseed, and 2 classes of bare soil: 23 plots of small roughness and 16 plots of medium roughness. Satellite radar images in the X-, C- and L-bands (HH polarization) were acquired between 14 and 18 April 2010. Optical images delivered by Formosat-2 and corresponding field data were acquired on 14 April 2010.The results show that combining images acquired in the L-band (Alos) and the optical range (Formosat-2) improves the classification performance (overall accuracy = 0.85, kappa = 0.81) compared to the use of radar or optical data alone. The results obtained for the various types of land cover show performance levels and confusions related to the phenological stage of the species studied, with the geometry of the cover, the roughness states of the surfaces, etc. Performance is also related to the wavelength and penetration depth of the signal providing the images. Thus, the results show that the quality of the classification often increases with increasing wavelength of the images used.     

An approach to extracting information of residential areas from Beijing-1 image based on Gabor texture segmentation

Abstract

According to the features of high-resolution panchromatic imagery of Beijing-1 small satellite, an approach to extracting information of residential areas is proposed in this paper based on Gabor texture segmentation. The algorithm extracts the features in different directions and different scales by building the Gabor filter, uses cluster analysis of multiple features to segment the image, and performs the fusion processing based on morphological scale space. It solves the problems in image processing resulting from low contrast between remote sensing objects and background, the blurring of image edges and high noise. It has the benefits of direction selection and frequency selection with strong self-adaptive ability. Our experiments prove the effectiveness of the approach for extracting information of residential areas from Beijing-1 high-resolution imagery.     

利用雷达干涉数据进行城市不透水层百分比估算

人工不透水层是城市地区的重要特征.作为城市生态环境的关键指数,不透水层百分比(Impervious Surfaces Percentage, ISP)常用于城市水文过程模拟、水质面源污染及城市专题制图等研究中.本文利用ERS-1/2 重复轨道雷达干涉数据,采用分类与回归树(CART)算法探究了雷达遥感在城市ISP估算中的可行性和潜力,并与SPOT5 HRG光学遥感图像的估算结果进行了分析比较.香港九龙港岛实验区的初步研究结果表明,雷达干涉数据在城市不透水层研究中具有一定的应用潜力,特别是裸土和稀疏植被的ISP估算结果要好于光学遥感,这主要得益于雷达干涉数据(特别是长时间相干图像)在人工建筑物和裸土或稀疏植被之间具有很强的区分能力,另外,雷达干涉数据和光学遥感数据间的融合能够提高ISP估算精度.     

Intercomparison and quality assessment of MERIS,MODIS and SEVIRI FAPAR products over the Iberian Peninsula

The fraction of absorbed photosynthetically active radiation (FAPAR) is a key variable in productivity and carbon cycle models. The variety of available FAPAR satellite products from different space agencies leads to the necessity of assessing the existing differences between them before using into models. Discrepancies of four FAPAR products derived from MODIS, SEVIRI and MERIS (TOAVEG and MGVI algorithms), covering the Iberian Peninsula from July 2006 to June 2007 are here analyzed. The assessment is based on an intercomparison involving the spatial and temporal consistency between products and a statistical analysis across land cover types. In general, significant differences are found over the Iberian Peninsula concentrated on the temporal variation and absolute values. The MODIS and MERIS/MGVI FAPAR products clearly show the highest and lowest absolute values, respectively, along with the lowest intra-annual variation. When considering individual land cover types, the largest FAPAR disagreements among the analyzed products were found between MODIS-MERI/MGVI and MERIS/TOAVEG-MERIS/MGVI over broadleaf and needleaf forests, with discrepancies quantified by RMSE higher than 0.30 and absolute bias higher than 0.25. These discrepancies can lead to relative gross primary production differences up to 65%.