基于TerrSolid对机载雷达DEM重提取方法研究     

王瑚  周光耀  周海龙 《测绘与空间地理信息》2020,(3):127-130

DEM的提取是激光雷达数据采集的重要用途之一,但由于目前算法的局限性,无法高精度地自动分类,如何在算法分类的基础上重新进行人工分类,以一定的原则和标准进行重提取从而得到更高精度的DEM,仍然是专业领域的一大难题。本文对某.LAS数据重提取,极大提高了其DEM的精度,为今后相关单位和个人使用TerrSolid软件对机载雷达DEM重提取提供一些经验。  相似文献   

Jason-2高度计电离层GIM误差分析及修正研究     

黄霞凤  苗洪利  苗翔鹰  薛文文 《海洋学报》2019,41(7):143-148

基于Jason-2高度计2015年地球物理数据集(GDR)38个周期太平洋海域的全球电离层图(GIM)电离层校正值和双频校正值的数据，分不同季度和不同纬度区域比较二者的差异，结果表明:GIM值与双频校正值之间存在明显的差异，GIM校正值普遍高于双频校正值，说明GIM高估了电离层路径延迟，GIM校正值与双频校正值的差异与季节和纬度区间有关。用梯度下降法得到GIM值的修正方程，将修正方程应用于2016年Jason-2的全年数据，修正后的GIM值与双频校正值十分接近，在各年份中均具有良好的适用性。在单频高度计不能使用电离层双频校正算法的情况下，可以利用不同季度和不同纬度区域的修正方程对同等高度的高度计GIM值进行修正以达到双频校正值的精度水平。  相似文献   

Lidar-aided analysis of boreal forest backscatter at Ku band     

《International Journal of Applied Earth Observation and Geoinformation》2020

This paper analyzes the backscatter of the microwave signal in a boreal forest environment based on a Ku -band airborne Frequency-Modulated Continuous Waveform (FMCW) profiling radar—Tomoradar. We selected a half-managed boreal forest in the southern part of Finland for a field test. By decomposing the waveform collected by the Tomoradar, the vertical canopy structure was achieved. Based on the amplitude of the waveform, the Backscattered Energy Ratio of Canopy-to-Total (BERCT) was calculated. Meanwhile, the canopy fraction was derived from the corresponding point cloud recorded by a Velodyne VLP-16 LiDAR mounted on the same platform. Lidar-derived canopy fraction was obtained by counting the number of the first/ the strongest returns versus the total amount of returns. Qualitative and quantitative analysis of radar-derived BERCT on lidar-derived canopy fraction and canopy height are investigated. A fitted model is derived to describe the Ku-band microwave backscatter in the boreal forest to numerically analyze the proportion contributed by four factors: lidar-derived canopy fraction, radar-derived canopy height, the radar-derived distance between trees and radar sensor and other factors, from co-polarization Tomoradar measurements. The Root Mean Squared Error (RMSE) of the proposed model was 0.0958, and the coefficient of determination R2 was 0.912. The fitted model reveals that the correlation coefficient between radar-derived BERCT and lidar-derived canopy fraction is 0.84, which illustrates that lidar surface reflection explains the majority of the profiling /waveform radar response. Thus, vertical canopy structure derived from lidar can be used for the benefit of radar analysis.  相似文献   

SAR影像中叠掩与阴影区域的识别 ——以湖北巴东为例   总被引：2，自引：0，他引：2  

张同同  杨红磊  李东明  李永杰  刘俊男 《测绘通报》2019,(11):85-88

SAR影像中叠掩和阴影区域的识别是滑坡监测中的首要工作，本文针对这一工作利用雷达卫星成像时的几何模型与图像处理中形态学方法综合识别叠掩与阴影区域，以ALOS-2数据为例，对比该地区雷达强度图像，验证了本文试验方法的可靠性。  相似文献   

平原地区机载激光雷达数据的抽稀算法分析   总被引：1，自引：0，他引：1  

杨明军  苏春梅  康冰锋  张珣  曹殿才 《测绘通报》2019,(1):101-107

目前，机载激光雷达点云数据在测绘行业中的应用还存在较多的瓶颈。为了使机载激光雷达点云数据更好地服务等值线等数据的生产，发挥其高效和高精度的优势，本文归纳、总结了国内外现有的LiDAR点云数据抽稀算法，并通过对比分析现有LiDAR点云数据抽稀算法存在的优缺点，如系统抽稀、格网抽稀、TIN抽稀和坡度抽稀等算法，结合平原地区激光点云在实际生产中的应用，研究了更适合平原地区点云数据的抽稀方法，通过大量的数据测试和试生产。结果表明，该方法可以在应用项目精度约束下保证数据质量，减少了后期数据处理应用的难度，提升了后续成果数据的质量，提高了作业生产效率，对机载激光雷达点云数据在测绘行业中的应用推广具有重要的现实意义。  相似文献   

Prograded coastal barriers provide paleoenvironmental records of storms and sea level during late Quaternary highstands          下载免费PDF全文

Amy J. Dougherty 《第四纪科学杂志》2018,33(5):501-517

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Character and origin of De Geer moraines in the Seacoast region of New Hampshire,USA          下载免费PDF全文

Samantha N. Sinclair  Joseph M. Licciardi  Seth W. Campbell  Brian M. Madore 《第四纪科学杂志》2018,33(2):225-237

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基于D-InSAR技术的金沙江地区滑坡形变监测与分析     

齐麟  孔祥意  袁鑫  姜岩 《测绘与空间地理信息》2020,(2):175-177,181

滑坡是发生在我国山区的主要地质灾害类型,金沙江地区由于地势较高、地形复杂、多云多雨的特点,给传统的滑坡监测增加了难度。合成孔径雷达差分干涉测量技术(Differential interferometry synthetic aperture radar,D-InSAR)已在滑坡地面沉降监测中得到了广泛应用。本文选取金沙江上游沿岸作为研究区域,基于2018年8月11日与9月28日的Sentinel-1A影像及SRTM1数据,利用GAMMA软件及D-InSAR技术监测到金沙江地区的地表形变,成功识别出金沙江右岸的一处滑坡灾害。研究结果显示,在此滑坡的坡顶部分出现了约2.5 cm的沉降,而在坡底部分由于崩塌物的累积,地面出现了约3 cm的抬升。从实验结果可以得出,InSAR技术是一种有效的滑坡变形监测手段,利用Sentinel-1A卫星的SAR数据对滑坡区域进行形变监测,可以得到较好的干涉结果。  相似文献   

基于核函数NPSSB模型的HY-2A卫星雷达高度计海况偏差研究     

张洁  田杰  王兆徽 《海洋预报》2020,37(1):1-10

利用机器学习的方法,对14个周期HY-2A卫星高度计数据:风速、有效波高和海面高度差值进行训练,探究海况偏差和风速、有效波高之间的关系,创建海况偏差核函数非参数模型(NPSSB),并与参数模型中具有代表性的BM3、BM4模型进行对比。研究表明:(1)核函数NPSSB模型能够很好的反映SSB与U、SWH之间的关系,SSB与U呈二次函数关系,SSB与SWH呈反比例函数关系;(2)核函数NPSSB模型对SSB的模拟能力与训练数据集相关,数据量越多,模拟能力越好;(3)核函数NPSSB模型与BM3、BM4模型都存在0^-0.03 m的差值,随着风速和有效波高的增加,差值的绝对值越大。  相似文献   

Identification of Convective and Stratiform Clouds Based on the Improved DBSCAN Clustering Algorithm     

Yuanyuan ZUO  Zhiqun HU  Shujie YUAN  Jiafeng ZHENG  Xiaoyan YIN  Boyong LI 《大气科学进展》2022,39(12):2203-2212

A convective and stratiform cloud classification method for weather radar is proposed based on the density-based spatial clustering of applications with noise (DBSCAN) algorithm. To identify convective and stratiform clouds in different developmental phases, two-dimensional (2D) and three-dimensional (3D) models are proposed by applying reflectivity factors at 0.5° and at 0.5°, 1.5°, and 2.4° elevation angles, respectively. According to the thresholds of the algorithm, which include echo intensity, the echo top height of 35 dBZ (ET), density threshold, and ε neighborhood, cloud clusters can be marked into four types: deep-convective cloud (DCC), shallow-convective cloud (SCC), hybrid convective-stratiform cloud (HCS), and stratiform cloud (SFC) types. Each cloud cluster type is further identified as a core area and boundary area, which can provide more abundant cloud structure information. The algorithm is verified using the volume scan data observed with new-generation S-band weather radars in Nanjing, Xuzhou, and Qingdao. The results show that cloud clusters can be intuitively identified as core and boundary points, which change in area continuously during the process of convective evolution, by the improved DBSCAN algorithm. Therefore, the occurrence and disappearance of convective weather can be estimated in advance by observing the changes of the classification. Because density thresholds are different and multiple elevations are utilized in the 3D model, the identified echo types and areas are dissimilar between the 2D and 3D models. The 3D model identifies larger convective and stratiform clouds than the 2D model. However, the developing convective clouds of small areas at lower heights cannot be identified with the 3D model because they are covered by thick stratiform clouds. In addition, the 3D model can avoid the influence of the melting layer and better suggest convective clouds in the developmental stage.  相似文献