基于HSV与PCA集成的高分影像高大地物阴影检测方法

针对水体、偏蓝色地物会影响高分影像阴影检测精度,本文提出了一种适用于GF-1影像的城市高大地物阴影检测方法。首先,在统计分析GF-1影像中阴影、水体及深色地物等典型地物光谱特征的基础上,利用主成分变换方法分割阴影与非阴影区域,分离后的阴影区域含有水体、深色地物信息;其次,对HSV色彩空间的V分量利用阈值法分割阴影和非阴影区域,分离后结果含有暗色植被,但不含有水体跟深色地物信息。最后,对两次计算结果进行逻辑与运算,从而剔除混合阴影区域中水体、深色地物以及暗色植被等信息,获得高精度阴影区信息。实验表明,该方法具有较好的普适性和可操作性,既能够削弱水体、偏蓝色地的影响,又能够高效、准确地提取出GF-1影像中的阴影信息。     

Comparison of sampling strategies for object-based classification of urban vegetation from Very High Resolution satellite images

Vegetation monitoring is becoming a major issue in the urban environment due to the services they procure and necessitates an accurate and up to date mapping. Very High Resolution satellite images enable a detailed mapping of the urban tree and herbaceous vegetation. Several supervised classifications with statistical learning techniques have provided good results for the detection of urban vegetation but necessitate a large amount of training data. In this context, this study proposes to investigate the performances of different sampling strategies in order to reduce the number of examples needed. Two windows based active learning algorithms from state-of-art are compared to a classical stratified random sampling and a third combining active learning and stratified strategies is proposed. The efficiency of these strategies is evaluated on two medium size French cities, Strasbourg and Rennes, associated to different datasets. Results demonstrate that classical stratified random sampling can in some cases be just as effective as active learning methods and that it should be used more frequently to evaluate new active learning methods. Moreover, the active learning strategies proposed in this work enables to reduce the computational runtime by selecting multiple windows at each iteration without increasing the number of windows needed.     

线阵卫星遥感影像外方位元素对偶四元数求解法

基于对偶四元数可统一描述位置与姿态的特点,提出了利用对偶四元数求解线阵卫星遥感影像外方位元素的方法。该方法使用对偶四元数的实部描述传感器的姿态,并利用对偶部和实部共同描述成像传感器的位置。通过对位置和姿态的内插建立了基于对偶四元数的外方位元素模型。为减少运算,将球面线性插值进行化简,进而建立了基于线性插值的成像几何模型。为求解外方位元素,首先对共线条件方程进行了线性化,然后通过矩阵微分运算推导了线元素的虚拟观测方程,并根据误差传播定律确定其权值,最终采用具有约束条件的参数平差法求解外方位元素。试验结果表明本文方法正确可靠,与采用欧拉角和单位四元数的外方位元素求解方法相比,有更高的参数解算精度,同时也表明了准确的初值和虚拟观测方程对外方位元素求解的必要性。     

控制点布设对无人机影像空三精度的影响

针对无人机航测按照传统的摄影测量布点方式,不仅需要较多的控制点,而且实施起来不太便利的缺点,提出了一种适合无人机航测的最优布点方案。通过对6种无人机控制点布设方案(传统的摄影测量布点方案和5种适合无人机航测的布点方案)进行空三精度对比实验,试验表明,该布点方案精度最高,与传统的摄影测量布点方式相比,其不仅实施方便,而且需要的控制点数量要少,大大减少了内、外业工作量。该方法的意义在于较好地解决了无人机航测因像幅小、重叠度不规则而导致的外业和内业工作量大的难题。     

Optimal fusion of optical and SAR high-resolution images for semiautomatic building detection

Building detection from different high-resolution aerial and satellite images has been a notable research topic in recent decades. The primary challenges are occlusions, shadows, different roof types, and similar spectral behavior of urban covers. Integration of different data sources is a solution to supplement the input feature space and improve the existing algorithms. Regarding the different nature and unique characteristics of optical and radar images, there are motivations for their fusion. This paper is aimed to identify an optimal fusion of radar and optical images to overcome their individual shortcomings and weaknesses. For this reason, panchromatic, multispectral, and radar images were first classified individually, and their strengths and weaknesses were evaluated. Different feature-level fusions of these data sets were then assessed followed by a decision-level fusion of their results. In both the feature and decision levels of integration, artificial neural networks were applied as the classifiers. Several post-processing methods using normalized different vegetation index, majority filter, and area filter were finally applied to the results. Overall accuracy of 92.8% and building detection accuracy of 89.1% confirmed the ability of the proposed fusion strategy of optical and radar images for building detection purposes.     

SAR主从影像的几何配准

对于SAR主影像(master)和从影像(slave)的几何配准,文中采用三次基本多项式与斜距-多普勒定位模型,解算出主影像中心像素点在从影像中的同名点,最后得出主从影像中心像素点的初级配准偏移量。本文以上海地区ERS-1影像数据为例,在Matlab环境下,对SAR主从影像的几何配准偏移量进行解算。实验结果表明,采用文中初级配准方法,初级配准相对精度可达到0.1%~0.9%。     

Regional geologic environs and natural resources of Badia Sector, Jordan

 This paper summarizes the information on the geology and natural resources of the Jordan Badia Research and Development Programme. The research focused on the issue of the environment in arid lands as an aid to provide practical options for sustainable development. This paper presents results of field studies in the following areas related to the sustainable development of the Safawi area in the northern Jordan Badia; geomorphology, including landform, soil, lands, processes and hazards, geology and physical resources and surface water hydrology. Tertiary-Quaternary continental basalt flows and tuffs cover approximately 11 000 km², the majority of the Safawi area. In addition to extensive basalt lava flows, the programme area includes a variety of geological outcrops and potential sources of economic products that include the following: Tuff/Scoria, Zeolite/Olivine, Porcellanite, potential sources of aggregate/construction materials, ornamental stone, building stone, basalt for manufacturing of rock wool, and materials suitable for producing lightweight aggregate. The whole of the eastern Badia exhibits major fault systems, many of which were identified from Landsat TM images. The system of wadis which drains the Badia is extensive, with the general flow from the north to the south and south-west. A noticeable geomorphic surficial deposit occuring throughout much of the Badia is fine-grained, water-lain sediments that vary in size and character. The local designation for the fine sediment deposits is Qaa. An MSS scene for the area under consideration has been studied. Twelve major geomorphic subdivisions or zones can be identified. Individual land system units have been identified by traversing the programme area. Key sites have been visited based on Landsat TM image interpretation. To a large extent, key areas were subdivided after their initial identification on the Landsat scene and corroboration in the field. The surface drainage of the Badia region can be broadly divided into wadi systems, areas of distinct channelized flow, and Qaa, predominantly fine-grained sedimentary basins of low relief. Spatial variability in infiltration rates across the wadi-Qaa system were determined from field experiments. Infiltration rates were found to be medium-high in the wadi channels but decrease rapidly for the Qaa materials. Apparently runoff from wadi side slopes will be high, and water storage occurs along the wadi channels while ponding occurs in the Qaa areas. Received: 13 March 1997 · Accepted: 13 January 1998     

五家渠猛进水库及周边地区地物光谱遥感数据分析

要充分利用多光谱遥感数据,地面资料是必不可少的,其中最重要的是需要有具有代表性的地表光谱数据库。作者通过对研究区实地测量,初步建立了地表光谱数据库,并且利用猛进水库地物反射光谱季节的观测资料和TM影像资料获取的地面反射率数据构成的归一化植被指数(NDVI)等进行分析,结果显示:水体、草滩和水泥路的反射光谱各有特点,易于从波段组合来区别各种地物。     

激光拉曼、阴极荧光研究对蜕晶化锆石及其U-Pb年龄解释的指示意义

通过对3个不同程度蜕晶化锆石样品的激光拉曼光谱,阴极荧光图像（CL）和U-Pb年龄特征进行对比分析,笔者发现锆石CL图像和激光拉曼光谱测试对蜕晶化锆石及其U—Pb年龄解释有很好的指示作用,因此强调加强矿物内部结构的研究,建议锆石激光拉曼测试、阴极荧光观察及锆石U—Pb同位素测试相结合分析锆石U—Pb年龄数据。     

红青三维立体地形地质图的制作及其地质应用

应用红青滤色三维立体图对制作立体地形图是一个十分重要而简单的方法。文中简述了红青滤色立体图的原理,应用SRTM-DEM数据制作红青滤色三维立体地形图,结合地质图获得红青滤色三维立体地形地质图。立体地形地质图是地质填图成果的直观形象,是活动构造地貌研究的重要工具。