Curve matching approaches to waveform classification: a case study using ICESat data

Light Detection and Ranging (LiDAR) waveforms are being increasingly used in many forest and urban applications, especially for ground feature classification. However, most studies relied on either discretizing waveforms to multiple returns or extracting shape metrics from waveforms. The direct use of the full waveform, which contains the most comprehensive and accurate information has been scarcely explored. We proposed to utilize the complete waveform to test its ability to differentiate between objects having distinct vertical structures using curve matching approaches. Two groups of curve matching approaches were developed by extending methods originally designed for pixel-based hyperspectral image classification and object-based high spatial image classification. The first group is based on measuring the curve similarity between an unknown waveform and a reference waveform, including curve root sum squared differential area (CRSSDA), curve angle mapper (CAM), and Kullback–Leibler (KL) divergence. The second group assesses the curve similarity between an unknown and reference cumulative distribution functions (CDFs) of their waveforms, including cumulative curve root sum squared differential area (CCRSSDA), cumulative curve angle mapper (CCAM), and Kolmogorov–Smirnov (KS) distance. When employed to classify open space, trees, and buildings using ICESat waveform data, KL provided the highest average classification accuracy (87%), closely followed by CCRSSDA and CCAM, and they all significantly outperformed KS, CRSSDA, and CAM based on 15 randomized sample sets.     

贺兰山及周边地区加里东运动研究

基于对贺兰山及周边地区下古生界详细的野外地质调查,通过碎屑锆石年龄谱的物源分析、地层接触关系追踪、岩性岩相突变特征分析、残留地层分布、古生物组合及亲缘性分析,讨论了阿拉善地块与华北地块和中祁连地块的亲缘关系,探讨了研究区加里东运动的幕次,认为早古生代阿拉善地块和华北地块相互独立,俯冲造山特征建造不清晰,两者之间可能为转换型陆缘。阿拉善地块和中祁连地块之间的加里东运动幕次清晰。加里东运动一幕发生在中-晚寒武世,香山群深水复理石沉积和张夏组浅水碳酸盐台地相沉积呈拼合式接触,生物组合为亲华北-亲祁连混合型,彼时中祁连地块从Rodinia大陆裂离,逐步靠近阿拉善地块;加里东运动二幕发生在早-中奥陶世,下奥陶统碳酸盐岩在全区稳定分布,与下伏香山群不整合接触,与阿不且亥组整合接触,生物相统一,生物组合为华北型,中祁连地块-阿拉善地块-华北地块平和成为一个统一的块体,整体为浅水台地沉积环境;加里东运动三幕发生在奥陶纪末,中-上奥陶统与泥盆系角度不整合接触,商丹洋闭合,扬子地块与阿拉善地块和华北地块靠近,商丹缝合带南部的宽坪洋打开,导致研究区中、晚奥陶世亲华北-亲扬子混合型生物组合类型。     

辽南金州拆离断层带中花岗质岩石的变形:显微构造、组构与年代学分析

花岗岩(脉)在中下地壳韧性剪切带中普遍发育,如何正确鉴别剪切带中剪切前、剪切期及剪切后花岗岩(脉)以及正确理解剪切过程中构造变形与岩浆作用之间的关系一直是一个重要课题。本文以辽南金州拆离断层带为研究对象,选取中部地壳伸展作用过程中具有不同变形表现的花岗岩(脉)开展宏观-微观构造观察、石英EBSD组构分析及锆石LA-ICP-MS年代学测试等工作,从而进一步丰富构造-岩浆关系判别准则。剪切前花岗岩(脉)多变形强烈且具有后期固态变形叠加在早期高温岩浆组构之上的特点,而剪切期的花岗岩由于侵位的时间不同,岩石的变形程度也会不同。剪切晚期侵入的岩脉遭受了较弱的晶内塑性变形,而剪切早期的岩脉可以显示岩浆流动或结晶后高温至中温固态变形。从组构特点上看,剪切前和剪切期花岗质岩石石英c轴组构大多表现为中高温组构叠加有低温组构的特点。剪切后的花岗质岩石仅发生微弱的晶内变形或未变形而显示低温或无规律的组构特征。对五个典型的样品进行年代学测试,其结果符合相应的期次划分类型。应用宏观构造、显微构造与组构分析,结合年代学测试综合分析,对于辽南变质核杂岩构造-岩浆活动性进行了精细划分,包括134~130Ma初始伸展阶段,130~115Ma峰期伸展与强烈岩浆活动阶段,以及115Ma前后伸展作用结束。     

四川会理天宝山矿床深部新发现铜矿与铅锌矿的成因关系探讨

天宝山矿床是川滇黔接壤铅锌矿集区内的代表性铅锌矿床之一,赋存于上震旦统灯影组白云岩中。近年来,该矿床深部发现了以铜为主的矿化,甚至形成铜矿体。目前,对铜矿成因及其与铅锌矿的关系尚不清晰。本文报道新发现铜矿的矿物学和同位素地球化学资料,以期揭示铜矿的成矿物质来源,结合铅锌矿的相关研究,探讨铜矿形成机制及其与铅锌矿的成因关系。镜下观察和扫描电镜分析显示,铜矿石中主要金属矿物为黄铜矿和银黝铜矿,其次为方铅矿和毒砂,含少量闪锌矿和黄铁矿;铅锌矿石中闪锌矿是主要金属矿物,方铅矿和黄铁矿次之,含少量黄铜矿和深红银矿。铜矿石中闪锌矿主要呈半自形-他形粒状,与黄铜矿共生或被其包裹,方铅矿主要呈细脉状充填在黄铜矿、银黝铜矿和毒砂的裂隙中或呈他形粒状分布在这些矿物中;铅锌矿石中黄铜矿主要呈浸染状分布于闪锌矿之中。两类矿石金属矿物的组构特征,显示铜矿物与铅锌矿物具有密切的共生、穿插和包裹关系,应属同期成矿。同位素地球化学数据显示,铜矿石中黄铜矿的δ34SCDT值为3.9‰~4.2‰(均值为4.1‰,n=3),铅锌矿石闪锌矿的δ34SCDT值为3.3‰~3.9‰(均值为3.5‰,n=3),十分相近,暗示它们具有相似的S源,应均属赋矿地层海相蒸发岩中硫酸盐热化学还原作用的产物。铜矿石中黄铜矿的~(206)Pb/~(204)Pb=18.441~18.476(均值为18.461,n=3),~(207)Pb/~(204)Pb=15.731~15.751(均值为15.741,n=3),~(208)Pb/~(204)Pb=38.809~38.873(均值为38.849,n=3),μ=9.72~9.76;铅锌矿石中方铅矿的~(206)Pb/~(204)Pb=18.442~18.480(均值为18.455,n=3),~(207)Pb/~(204)Pb=15.746~15.763(均值为15.752,n=3),~(208)Pb/~(204)Pb=38.793~38.892(均值为38.840,n=3),μ=9.75~9.78。两者具有相近的Pb同位素组成且其壳源特征明显,表明它们的成矿金属来源相似,均来自上地壳,与赋矿沉积岩有关。综上,矿物学和同位素地球化学证据表明,天宝山矿床深部新发现铜矿与铅锌矿具有明显的同期共生关系和相似的成矿物质来源,是同一成矿热液体系不同阶段演化的产物。天宝山铜铅锌矿床与MVT矿床的成矿特征不同,暗示其成矿作用(环境)特殊,可能与矿床所处的地质背景有关,其成因认识对川滇黔接壤区同类型矿床深部找铜矿具有重要的指导意义。     

春季我国不同纬度河口浮游动物群落变化趋势

根据2010-2012年春季由南向北河口海域：北仑河口、九龙江口、瓯江口、长江口和灌河口的浮游动物调查资料;通过比较不同纬度河口浮游动物群落的生物多样性指数（H''）、物种更替率（R）和群落相似系数（S）;探讨了河口浮游动物群落特征沿着不同纬度变化的趋势。结果表明;自南向北5个河口可以划分为3个不同的浮游动物区系。北仑河口和九龙江口为南部亚热带区系;位于亚热带海域;以亚热带种为主;H''分别为1.01和2.18;两河口之间R值为65.52%;S值为51.28%;瓯江口和长江口为中部过渡区系;位于亚热带和温带过渡海域;亚热带种和暖温带种是主要出现的种类;H''分别为1.31和1.86;两河口之间R值为58.33%;S值为58.82%;灌河口单独为北部温带区系;位于温带海域;暖温带种是主要出现的种类;H''值为1.19;与其余河口物种更替率均高于80.00%;群落相似系数均低于32.00%;表明群落结构由南到北的变化非常显著。线性回归结果表明：我国不同河口之间浮游动物的物种更替率与纬度差（两河口所处纬度的差值;δN）呈正相关关系（R=0.026ΔN+0.608;p=0.002）;群落相似系数与纬度差呈负相关关系（S=0.034ΔN+0.578;p=0.001）。春季;我国不同纬度河口浮游动物群落结构的变化;主要是因为影响各河口的水温和水团存在较大差别所致。     

Curvedness feature constrained map matching for low-frequency probe vehicle data

Map matching method is a fundamental preprocessing technique for massive probe vehicle data. Various transportation applications need map matching methods to provide highly accurate and stable results. However, most current map matching approaches employ elementary geometric or topological measures, which may not be sufficient to encode the characteristic of realistic driving paths, leading to inefficiency and inaccuracy, especially in complex road networks. To address these issues, this article presents a novel map matching method, based on the measure of curvedness of Global Positioning System (GPS) trajectories. The curvature integral, which measures the curvedness feature of GPS trajectories, is considered to be one of the major matching characteristics that constrain pairwise matching between the two adjacent GPS track points. In this article, we propose the definition of the curvature integral in the context of map matching, and develop a novel accurate map matching algorithm based on the curvedness feature. Using real-world probe vehicles data, we show that the curvedness feature (CURF) constrained map matching method outperforms two classical methods for accuracy and stability under complicated road environments.     

鲁西隆起和济阳拗陷耦合关系分析

通过分析鲁西隆起和济阳拗陷的地壳结构特征,结合二者的空间分布、时间演化及构造上的相关性,发现同处于伸展构造环境且相邻的鲁西隆起和济阳拗陷在地壳结构特征存在明显不同.济阳拗陷表现为地壳均衡的镜像结构特征,不同于地壳呈向上隆起状的鲁西隆起,说明鲁西隆起和济阳拗陷在成因上存在明显差异.济阳拗陷的伸展过程并非由地幔物质主动上涌造成,应是鲁西隆起在隆升过程对济阳拗陷地壳的拖拽作用,鲁西隆起和济阳拗陷的地壳结构特征反映出它们在成因上具有明显的耦合性.     

基于改进K-SVD字典学习方法的地震数据去噪

为实现更好的地震数据去噪技术,笔者引入一种新的算法:快速迭代收缩阀值法(FISTA),通过FISTA和K-奇异值分解(K-SVD)不断迭代更新K-SVD字典,利用更新得到的K-SVD字典对地震数据进行稀疏表示,去除稀疏系数中较小的数值,使数据中的随机噪声得到压制。对层状模型合成地震记录,Marmousi模型合成地震记录以及实际地震数据进行对比实验,得出FISTA算法较OMP算法能更好地提高地震数据的信噪比,同时有效地保护了反射信号。     

Geometric-constrained multi-view image matching method based on semi-global optimization

Targeting at a reliable image matching of multiple remote sensing images for the generation of digital surface models, this paper presents a geometric-constrained multi-view image matching method, based on an energy minimization framework. By employing a geometrical constraint, the cost value of the energy function was calculated from multiple images, and the cost value was aggregated in an image space using a semi-global optimization approach. A homography transform parameter calculation method is proposed for fast calculation of projection pixel on each image when calculating cost values. It is based on the known interior orientation parameters, exterior orientation parameters, and a given elevation value. For an efficient and reliable processing of multiple remote sensing images, the proposed matching method was performed via a coarse-to-fine strategy through image pyramid. Three sets of airborne remote sensing images were used to evaluate the performance of the proposed method. Results reveal that the multi-view image matching can improve matching reliability. Moreover, the experimental results show that the proposed method performs better than traditional methods.     

A geometric-based approach for road matching on multi-scale datasets using a genetic algorithm

Object matching is used in various applications including conflation, data quality assessment, updating, and multi-scale analysis. The objective of matching is to identify objects referring to the same entity. This article aims to present an optimization-based linear object-matching approach in multi-scale, multi-source datasets. By taking into account geometric criteria, the proposed approach uses real coded genetic algorithm (RCGA) and sensitivity analysis to identify corresponding objects. Moreover, in this approach, any initial dependency on empirical parameters such as buffer distance, threshold of spatial similarity degree, and weights of criteria is eliminated and, instead, the optimal values for these parameters are calculated for each dataset. Volunteered geographical information (VGI) and authoritative data with different scales and sources were used to assess the efficiency of the proposed approach. According to the results, in addition to an efficient performance in various datasets, the proposed approach was able to appropriately identify the corresponding objects in these datasets by achieving higher F-Score.