基于区域多次回波点密度分析的城区LiDAR建筑物提取

以正确提取城区Li DAR点云中建筑物为目标,综合利用不同类别目标点云的回波特征以及地形信息,提出了一种基于区域多次回波密度分析的Li DAR点云建筑物提取方法。首先,将点云构建不规则三角网(triangulated irregular network,TIN),获取封闭的等高线;然后,利用等高线间的拓扑关系得到等高线族区域;最后,统计每一区域的多次回波点云密度信息,通过建筑物和树木区域多次回波点云在区域密度上的巨大差异来识别建筑物点云和树木点云。研究结果表明:该方法既充分利用了建筑物表面与植被间多次回波特性的差异,又不否定建筑物边缘同样存在多次回波的现象;通过封闭的等高线自适应地检测出地物目标的轮廓,弥补了传统Li DAR建筑物提取方法的不足;该方法能够较其他方法更准确地提取建筑物。     

Intergenerational relations and the power of the cell phone: Perspectives on young people’s phone usage in sub-Saharan Africa

Cell phones present new forms of sociality and new possibilities of encounter for young people across the globe. Nowhere is this more evident than in sub-Saharan Africa where the scale of usage, even among the very poor, is remarkable. In this paper we reflect on the inter-generational encounters which are embedded in young people’s cell phone interactions, and consider the wider societal implications, not least the potential for associated shifts in the generational balance of power. An intriguing feature of this changing generational nexus is that while many young people’s phone-based interactions, from their mid-teens onwards, are shifting away from the older generation towards friendship networks in their own age cohort, at the same time they are repositioning themselves – or becoming repositioned – as family information hubs, as a consequence of their phone expertise. The paper draws on mixed-methods research with young people aged c. 9–25 years and in-depth interviews with older age-groups in 24 sites (ranging from high density poor urban to remote rural) across Ghana, Malawi and South Africa.     

一种基于分割的机载LiDAR点云数据滤波

针对当前滤波算法在处理地形不连续区域或存在复杂建筑物区域时容易过分＂腐蚀＂地形并难以去除一些低矮植被的不足,提出了一种基于分割的机载LiDAR点云滤波算法。首先,对原始点云基于地表连续性进行分割;然后,在移除点数目较小的粗差点集之后采用对分割点集建立缓冲区的方法,区分地面和非地面点集;在较大地物经过迭代分割基本移除之后,使用约束平面的方法移除高度较小的地表附着物以实现滤波。实验结果表明,与经典滤波算法相比,该算法提高了地面点的分类精度,在滤除地物信息的同时能有效地保留地形特征。     

基于移动GIS的城乡规划监察执法信息系统

分析了目前城乡规划监察执法工作存在的问题及信息化需求,提出了利用移动GIS技术研发城乡规划监察执法信息系统的方法;着重阐述了系统的业务模式、设计框架、数据组织、系统实现;最后总结了在移动GIS技术辅助下的城乡规划监察执法系统在实际工作的应用。     

机载LiDAR点云数据与影像数据融合

分析机载LiDAR系统获取的点云数据与影像数据的优缺点,从而取长补短,将二者进行叠加融合,并成功地将航空影像的光谱信息赋给相对应的LiDAR点云,弥补了LiDAR点云在光谱信息方面的缺陷,为LiDAR点云数据的后续处理提供重要的信息支持。     

融合航空影像的LiDAR地物点云分类

点云滤波分类是LiDAR后续应用的基础工作,在点云滤波的基础上,以航空影像为辅助条件,结合点云高程信息,设计一套地物点云的分类方法。该方法首先融合航空影像与LiDAR数据,将对应RGB值赋予每个点,根据植被的光谱特征提取出部分植被点云;然后再根据文中定义的点云高程纹理,在剩余地物点云中提取出建筑物点,最后根据回波次数信息分离出剩余植被点,完成地物点云的分类。采用北京凤凰岭地区一组机载LiDAR数据进行实验。实验结果表明,该方法能够有效地将地物点云进行分类并且满足一定的精度要求,具有一定的实用价值。     

联合机载LiDAR数据和潮汐数据自动提取潮位线

首先,联合机载激光雷达(LiDAR)数据提取的海岸带数字表面模型(DSM)与验潮站数据提取的高、低潮面进行相交运算,生成"水陆二值图像",然后对其以提取边缘的方式提取高、低潮潮位线;针对LiDAR光束无法穿透水体导致低潮线附近DSM为无效值的缺陷,采取移动趋势面拟合法外推概略低潮线附近DSM,在此基础上重新提取更精确的低潮潮位线。实验表明,该方法能在较少人工干预的情况下有效提取高、低潮潮位线。     

基于GPGPU的全波形并行分解算法

针对EM(Expectation Maximization)波形分解算法具有多次迭代和大量乘、除、累加等高密集运算的特点,提出一套将EM算法在通用计算图形处理器GPGPU上并行化的方案。针对通用并行计算架构CUDA的存储层次特点,设计总体的并行方案,充分挖掘共享存储器、纹理存储器的高速访存的潜能;根据波形采样值采用字节存储的特征,利用波形采样值的直方图求取中位数,从而降低求噪音阈值的计算复杂度;最后,采用求和规约的并行策略提高EM算法迭代过程中大量累加的计算效率。实验结果表明,当设置合理的并行参数、EM迭代次数大于16次、数据量大于64 M时,与单核CPU处理相比,GPU的加速比达到了8,能够显著地提高全波形分解的效率。     

集成Landsat OLI和机载LiDAR条带数据的亚热带森林生物量制图

以亚热带天然次生林为研究对象,借助一个条带的少量LiDAR点云数据和覆盖整个研究区的免费Landsat OLI多光谱数据,并结合地面实测数据,探索森林生物量低成本高精度制图方法。首先,提取了OLI和LiDAR特征变量,并与地上和地下生物量进行相关分析以筛选变量;然后,借助LiDAR数据覆盖区的样地和条带LiDAR数据构建"LiDAR生物量模型";再从LiDAR反演生物量的结果中进行采样,结合OLI特征变量构建"LiDAR-OLI模型";最后,与单独使用OLI多光谱数据建立的"OLI估算模型"结果进行比较,分析精度并验证新方法的效果。结果表明,"LiDAR-OLI模型"对地上和地下生物量的模型拟合效果较好且均优于"OLI模型",且其交叉验证的精度也较高并优于"OLI模型",从而证明了新方法的可靠性及有效性。本研究为主、被动遥感技术在中小尺度上协同反演森林参数提供了实验基础,也为基于全覆盖免费OLI多光谱数据及条带LiDAR数据的低成本森林生物量制图探索了技术路线。     

Detecting multi-scale riverine topographic variability and its influence on Chinook salmon habitat selection

Quantifying geomorphic conditions that impact riverine ecosystems is critical in river management due to degraded riverine habitat, changing flow and thermal conditions, and increasing anthropogenic pressure. Geomorphic complexity at different scales directly impacts habitat heterogeneity and affects aquatic biodiversity resilience. Here we showed that the combination of continuous spatial survey at high resolution, topobathymetric light detection and ranging (LiDAR), and continuous wavelet analysis can help identify and characterize that complexity. We used a continuous wavelet analysis on 1-m resolution topobathymetry in three rivers in the Salmon River Basin, Idaho (USA), to identify different scales of topographic variability and the potential effects of this variability on salmonid redd site selection. On each river, wavelet scales characterized the topographic variability by portraying repeating patterns in the longitudinal profile. We found three major representative spatial wavelet scales of topographic variability in each river: a small wavelet scale associated with local morphology such as pools and riffles, a mid-wavelet scale that identified larger channel unit features, and a large wavelet scale related to valley-scale controls. The small wavelet scale was used to identify pools and riffles along the entire lengths of each river as well as areas with differing riffle-pool development. Areas along the rivers with high local topographic variability (high wavelet power) at all wavelet scales contained the largest features (i.e., deepest or longest pools) in the systems. By comparing the wavelet power for each wavelet scale to Chinook salmon redd locations, we found that higher small-scale wavelet power, which is related to pool-riffle topography, is important for redd site selection. The continuous wavelet methodology objectively identified scales of topographic variability present in these rivers, performed efficient channel-unit identification, and provided geomorphic assessment without laborious field surveys.