机载LiDAR点云数据与影像数据融合     

尚大帅  马东洋  高振峰  赵羲 《测绘工程》2012,21(1):18-20,24

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。  相似文献   

融合航空影像的LiDAR地物点云分类     

龚亮  李正国  包全福 《测绘工程》2012,21(1):34-38

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。  相似文献   

联合机载LiDAR数据和潮汐数据自动提取潮位线     

张良  马洪超  邬建伟 《遥感学报》2012,16(2):405-416

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。  相似文献   

基于GPGPU的全波形并行分解算法     

王宗跃  马洪超  明洋 《遥感学报》2014,18(6):1217-1222

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。  相似文献   

集成Landsat OLI和机载LiDAR条带数据的亚热带森林生物量制图   总被引：1，自引：0，他引：1  

曹林  徐婷  申鑫  佘光辉 《遥感学报》2016,20(4):665-678

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。  相似文献   

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

Jenna Duffin  Richard A. Carmichael  Elowyn M. Yager  Rohan Benjankar  Daniele Tonina 《地球表面变化过程与地形》2021,46(5):1026-1040

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.  相似文献   

Climate-change driven increased flood magnitudes and frequency in the British uplands: Geomorphologically informed scientific underpinning for upland flood-risk management     

David J. Milan  Arved C. Schwendel 《地球表面变化过程与地形》2021,46(15):3026-3044

Upland river systems in the UK are predicted to be prone to the effects of increased flood magnitudes and frequency, driven by climate change. It is clear from recent events that some headwater catchments can be very sensitive to large floods, activating the full sediment system, with implications for flood risk management further down the catchment. We provide a 15-year record of detailed morphological change on a 500-m reach of upland gravel-bed river, focusing upon the geomorphic response to an extreme event in 2007, and the recovery in the decade following. Through novel application of two-dimensional (2D) hydrodynamic modelling we evaluate the different energy states of pre- and post-flood morphologies of the river reach, exploring how energy state adjusts with recovery following the event. Following the 2007 flood, morphological adjustments resulted in changes to the shear stress population over the reach, resulting in higher shear stresses. Although the proportion of shear stresses in excess of those experienced using the pre-flood digital elevation model (DEM) varied over the recovery period, they remained substantially in excess of those experienced pre-2007, suggesting that there is still potential for enhanced bedload transport and morphological adjustment within the reach. Although volumetric change calculated from DEM differencing does indicate a reduction in erosion and deposition volumes in the decade following the flood, we argue that the system still has not fully recovered to the pre-flood state. We further argue that Thinhope Burn, and other similarly impacted catchments in upland environments, may not recover under the wet climatic phase currently being experienced. Hence systems like Thinhope Burn will continue to deliver large volumes of sediment further down river catchments, providing new challenges for flood risk management into the future.  相似文献   

基于随机森林的光子计数激光雷达点云滤波     

陈博伟  庞勇  李增元  卢昊  梁晓军 《地球信息科学学报》2019,21(6):898-906

新一代星载激光雷达卫星ICESat-2首次采用了微脉冲光子计数激光雷达技术,由于单光子探测的灵敏性导致数据在大气和地表下层产生了大量噪声,因此对光子计数激光雷达点云数据实现信号和噪声的分离是开展进一步应用研究的前提和基础。本文选择美国俄勒冈州和弗吉尼亚州2个研究区,采用MATLAS数据,根据光子点云数据的特点构造了12个光子点云特征,对所构造的特征利用随机森林进行变量筛选,用机器学习方法对光子点云进行分类,并将建立好的模型推广到整个研究区。研究结果表明,本文构建的分类器分类总精度达到了96.79%,Kappa系数为0.94,平均生产者精度和用户精度分别为97.1%和96.8%。在相对弱噪声、平坦地形区域和强噪声、复杂地形区域都取得较好的分类结果。本文结果显示了基于少量样本通过机器学习的方法构建模型,可以推广到较大范围区域的光子点云分类应用中。  相似文献   

Quantifying terrain controls on runoff retention and routing in the Northern Prairies     

Igor Pavlovskii  Saskia L. Noorduijn  Jessica E. Liggett  Jeanette Klassen  Masaki Hayashi 《水文研究》2020,34(2):473-484

The role of hummocky terrain in governing runoff routing and focussing groundwater recharge in the Northern Prairies of North America is widely recognised. However, most hydrological studies in the region have not effectively utilised information on the surficial geology and associated landforms in large-scale hydrological characterization. The present study uses an automated digital elevation model (DEM) analysis of a 6500-km² area in the Northern Prairies to quantify hydrologically relevant terrain parameters for the common types of terrains in the prairies with different surficial deposits widespread in the prairies, namely, moraines and glaciolacustrine deposits. Runoff retention (and storage) capacity within depressions varies greatly between different surficial deposits and is comparable in magnitude with a typical amount of seasonal snowmelt runoff generation. The terrain constraint on potential runoff retention varies from a few millimetres in areas classified as moraine to tens of millimetres in areas classified as stagnant ice moraine deposits. Fluted moraine and glaciolacustrine deposits have intermediate storage capacity values. The study also identified the probability density function describing a number of immediate upstream neighbours for each depression in a fill-and-spill network. A relationship between depression parameters and surficial deposits, as well as identified depression network structure, allows parametrisation of hydrologic models outside of the high-resolution DEM coverage, which can still account for terrain variation in the Prairies.  相似文献   

Integration of hyperspectral and LiDAR data for mapping small water bodies     

《International Journal of Applied Earth Observation and Geoinformation》2020

Inland water bodies are globally threatened by environmental degradation and climate change. On the other hand, new water bodies can be designed during landscape restoration (e.g. after coal mining). Effective management of new water resources requires continuous monitoring; in situ surveys are, however, extremely time-demanding. Remote sensing has been widely used for identifying water bodies. However, the use of optical imagery is constrained by accuracy problems related to the difficulty in distinguishing water features from other surfaces with low albedo, such as tree shadows. This is especially true when mapping water bodies of different sizes. To address these problems, we evaluated the potential of integrating hyperspectral data with LiDAR (hereinafter “integrative approach”). The study area consisted of several spoil heaps containing heterogeneous water bodies with a high variability of shape and size. We utilized object-based classification (Support Vector Machine) based on: (i) hyperspectral data; (ii) LiDAR variables; (iii) integration of both datasets. Besides, we classified hyperspectral data using pixel-based approaches (K-mean, spectral angle mapper). Individual approaches (hyperspectral data, LiDAR data and integrative approach) resulted in 2–22.4 % underestimation of the water surface area (i.e, omission error) and 0.4–1.5 % overestimation (i.e., commission error).The integrative approach yielded an improved discrimination of open water surface compared to other approaches (omission error of 2 % and commission error of 0.4 %). We also evaluated the success of detecting individual ponds; the integrative approach was the only one capable of detecting the water bodies with both omission and commission errors below 10 %. Finally, the assessment of misclassification reasons showed a successful elimination of shadows in the integrative approach. Our findings demonstrate that the integration of hyperspectral and LiDAR data can greatly improve the identification of small water bodies and can be applied in practice to support mapping of restoration process.  相似文献