Liquefied vs stratified sediment mobilization processes: Insight from the South of the Barbados accretionary prism

This paper discusses the nature and origin of subsurface sediment mobilization processes in deep marine clay-rich environments. In the studied area of the southern Barbados accretionary prism, new geophysical acquisitions have emphasized the spectacular widespread development of mud volcanoes that are well-developed along ramp anticlines and along sigmoidal rises with trends that are oblique to the axes of the main folds of the accretionary wedge. On some active mud volcanoes, heat-flow measurements show high positive anomalies related to high fluxes of mud transfer. The mobilized solid fraction expelled by the mud volcanoes does not originate from a unique source bed but from various formations pierced by the mud conduits and is driven by the water phase. The area studied also exhibits trends of structures corresponding to sub-circular massive local uplifts of deformed but well-preserved stratified sediments (turbidites and hemipelagics). No piercing shale diapirs have been encountered in this area. Some of these local uplift structures are complicated by the development of collapses, calderas, and superimposed mud volcanoes. Mud volcanism corresponds fundamentally to fluid displacement (water and gas), whereas massive sedimentary uplift corresponds to large vertical displacements of stratified solid levels but for which the deep cause could be partly the intrusion of mud plugs. Both are dynamic phenomena controlled by the development of overpressure at depth, contributing to sedimentary mobilizations.     

基于移动通信/GPS/GIS技术的智能公交系统技术和功能

本文针对国内公共交通拥堵、效率低的现状,提出了基于移动通信/GPS/GIS技术的智能公交系统的解决方案,该系统能在很大程度上缓解目前公共交通拥堵的现状。本文主要介绍了智能公交系统的关键技术以及系统构成。     

机载LiDAR的特点及其用于西南高山峡谷地区大比例尺测绘工作的可行性探讨

本文通过分析目前主流机载LiDAR的各项指标及其实际意义,从多个方面证明了机载LiDAR能够有效解决西南高山峡谷地区大比例尺地形测绘工作所面临的困难。     

无人机多光谱和LiDAR的红树林精细识别与生物量估算

红树林是生长在热带和亚热带海岸潮间带、受到海水周期性浸淹的木本植物群落,被公认为是海陆边缘重要的蓝色碳汇,但由于其地处海岸带区域,受人类开发利用活动的影响严重。本文选择广西茅尾海红树林保护区为研究区,以无人机多光谱和激光雷达影像为数据源,利用支持向量机分类方法对红树林优势种类进行分类;提出了单木分层分区距离判别聚类分割方法,准确提取了红树林的单木结构信息;估算了研究区红树林地上生物量。得出以下结论：（1）综合利用无人机多光谱和激光雷达数据,对研究区红树林种间类型识别总体精度可达90.69%;（2）基于分层分区距离判别聚类方法能够较好的提取红树林单木结构特征,树高的提取精度优于冠幅;（3）构建了红树林高度、冠幅与地上生物量回归模型,其中桐花树生物量回归模型的决定系数R2最高,达0.83;（4）研究区内红树林地上生物量主要分布范围为1.24—3.6 kg/m²,其中无瓣海桑最高,老鼠簕最低。     

CMMB信号抗多径性能的分析与仿真

从CMMB（中国移动多媒体广播）体系结构入手,研究了CMMB信号抗多径性能。以信号中有、无循环前缀（CP）为例给出了抗多径性能的详细推导,通过Matlab 7．1对该系统在典型动态多径信道情况下的性能进行了仿真。结果表明：该系统有很强的抗多径能力,在信噪比为30dB时接收CMMB信号与接收普通OFDM（正交频分复用）信号相比,误码率有2个量级的改善,有利于提高导航定位的精度。     

An object-based approach for mapping forest structural types based on low-density LiDAR and multispectral imagery

Mapping forest structure variables provides important information for the estimation of forest biomass, carbon stocks, pasture suitability or for wildfire risk prevention and control. The optimization of the prediction models of these variables requires an adequate stratification of the forest landscape in order to create specific models for each structural type or strata. This paper aims to propose and validate the use of an object-oriented classification methodology based on low-density LiDAR data (0.5 m^?2) available at national level, WorldView-2 and Sentinel-2 multispectral imagery to categorize Mediterranean forests in generic structural types. After preprocessing the data sets, the area was segmented using a multiresolution algorithm, features describing 3D vertical structure were extracted from LiDAR data and spectral and texture features from satellite images. Objects were classified after feature selection in the following structural classes: grasslands, shrubs, forest (without shrubs), mixed forest (trees and shrubs) and dense young forest. Four classification algorithms (C4.5 decision trees, random forest, k-nearest neighbour and support vector machine) were evaluated using cross-validation techniques. The results show that the integration of low-density LiDAR and multispectral imagery provide a set of complementary features that improve the results (90.75% overall accuracy), and the object-oriented classification techniques are efficient for stratification of Mediterranean forest areas in structural- and fuel-related categories. Further work will be focused on the creation and validation of a different prediction model adapted to the various strata.     

机载激光雷达及高光谱的森林乔木物种多样性遥感监测

利用机载LiDAR和高光谱数据并结合37个地面调查样本数据,基于结构差异与光谱变异理论,通过相关分析法分别筛选了3个最优林冠结构参数和6个最优光谱指数,在单木尺度上利用自适应C均值模糊聚类算法,在神农架国家自然保护区开展森林乔木物种多样性监测,实现了森林乔木物种多样性的区域成图。研究结果表明,(1)基于结合形态学冠层控制的分水岭算法可以获得较高精度的单木分割结果(R~2=0.88,RMSE=13.17,P0.001);(2)基于LiDAR数据提取的9个结构参数中,95%百分位高度、冠层盖度和植被穿透率为最优结构参数,与Shannon-Wiener指数的相关性达到R~2=0.39—0.42(P0.01);(3)基于机载高光谱数据筛选的16个常用的植被指数中,CRI、OSAVI、Narrow band NDVI、SR、Vogelmann index1、PRI与Shannon-Wiener指数的相关性最高(R~2=0.37—0.45,P0.01);(4)在研究区,利用以30 m×30 m为窗口的自适应模糊C均值聚类算法可预测的最大森林乔木物种数为20,物种丰富度的预测精度为R~2=0.69,RMSE=3.11,Shannon-Wiener指数的预测精度为R~2=0.70,RMSE=0.32。该研究在亚热带森林开展乔木物种多样性监测,是在区域尺度上进行物种多样性成图的重要实践,可有效补充森林生物多样性本底数据的调查手段,有助于实现生物多样性的长期动态监测及科学分析森林物种多样性的现状和变化趋势。     

机载激光雷达森林垂直结构剖面参数的沿海平原人工林林分特征反演

中国是世界上人工林面积最大的国家,实时、定量、精确地获取人工林林分特征对于人工林资源监测、管理以及全球碳循环具有重要意义。以北亚热带沿海平原人工林为研究对象,借助机载激光雷达LiDAR(Light Detection And Ranging)点云数据并结合地面实测的55个样地来反演人工林林分特征。首先,构建冠层高度分布剖面CHD(Canopy Height Distribution)和枝叶剖面FP(Foliage Profile);然后,通过Weibull函数分别对CHD和FP进行拟合并提取Weibull参数作为特征变量(第1组);同时,还直接基于点云提取了LiDAR高度变量HRM(HeightRelated Metrics)和冠层密度变量DRM(Density-Related Metrics)(第2组);最后,结合地面实测数据和两组特征变量构建了多元回归模型用于预测各林分特征(即林分密度、平均胸径、胸高断面积、Lorey’s树高、蓄积量和地上生物量)。结果表明:(1)与只使用基于点云的特征变量(即第2组)相比,结合点云特征变量(第2组)和冠层垂直结构剖面特征变量(第1组)的各林分特征预测精度均有所提升(ΔAdjusted R2=0—0.13,ΔrRMSE=0.08—3.65%);(2)对各林分特征预测的结果中,Lorey’s树高(Adjusted R2=0.85, rRMSE=7.66%)和蓄积量(Adjusted R2=0.84,rRMSE=14.27%)的预测精度最高,地上生物量(Adjusted R2=0.78, rRMSE=14.15%)、胸高断面积(Adjusted R2=0.73, rRMSE=14.70%)和平均胸径(Adjusted R2=0.64, rRMSE=15.05%)次之,林分密度(Adjusted R2=0.58,rRMSE=26.16%)的预测精度最低;(3)Weibull函数较准确地反映了亚热带人工林垂直冠层结构,可以有效提高林分特征反演精度。     

三家北斗地基增强系统的高精度定位服务性能对比分析

北斗地基增强系统是推广高精度“北斗+”应用的重要基础设施。本文首次研究千寻位置、六分科技及中国移动3家覆盖全国的北斗地基增强系统的定位服务性能,通过对2021-07-21~22采集的2次8~9 h观测数据进行分析,得到以下结论： 1） 千寻位置和中国移动的官方推荐挂载点支持BDS-2三频信号和BDS-3双频信号（B1I、B3I）,六分科技支持BDS-2和BDS-3双频信号（B1I、B3I）; 2） 3家北斗地基增强系统都能提供100%的北斗数据完整率; 3） 静态基线结果表明,3家北斗地基增强系统虚拟基站组成的闭合环相对误差均小于2×10^-6; 4） 单历元RTK解算结果表明,3家北斗地基增强系统均能够提供水平向优于3 mm、垂直向优于9 mm的内符合精度,但不同北斗地基增强系统之间存在cm~dm级的定位结果偏差,因此不建议在RTK作业时使用不同的北斗地基增强系统。     

机载LiDAR点云的Delaunay三角网快速生成算法

为了提高机载激光点云的Delaunay三角网生成效率及稳定性,基于分块算法的思想,改进了点云数据的分块方式,利用点云的凸包及重心点进行数据分块,并结合子块中激光点个数阈值进行三角形子块的细分,从而避免了传统子块合并过程中复杂的相邻三角形搜索及优化处理,仅需简单的一步优化即可完成相邻子块的合并,大大提高了算法的效率。经实验证明,该算法简单、高效且稳定性好,尤其对于大数据量的机载LiDAR点云Delaunay三角网生成具有明显的优势。