Please wait a minute...
img

官方微信

遥感技术与应用
数据与图像处理     
基于机载激光雷达数据的海岸带水域提取方法
梁茜茜1,3,张汉德1,2,孙根云1,3,王鹏1,3
(1.中国石油大学(华东)地球科学与技术学院测绘系,山东 青岛-266580;
2.中国海监北海航空支队,山东 青岛-266061;
3.海洋国家实验室海洋矿产资源评价与探测技术功能实验室,山东 青岛-266071 )
Water Regions Extraction from LiDAR Data in Coast
Liang Qianqian1,3,Zhang Hande1,2,Sun Genyun1,3,Wang Peng1,3
(1.College of Geo-resources and Information,China University of Petroleum (East China),Qingdao 266580,China;
2.Air-Borne Detachment of China Marine Surveillance,Qingdao 266061,China;
3.Laboratory for Marine Mineral Resources,Qingdao National Laboratoryfor Marine Science and Technology,Qingdao 266071,China)
 全文: PDF(10507 KB)  
摘要:
利用遥感影像提取海岸带地区水域点,容易受不同水域特征差异较大的影响。针对这一问题,考虑到机载激光雷达数据能够提供高程、强度、密度等信息,提出综合利用水域激光脚点的密度、高程、强度特征提取水域点的方法。首先利用局部水域点的密度特征得到初始水域点,然后用高程和强度特征进行约束,得到可靠水域点,并构建水域高程趋势面;进而利用点云相对于水域高程趋势面的相对高程提取出所有水域点。实验结果显示,利用该方法区分海岸带水域点精度达到了91%以上,能够快速提取较大范围的海岸带区域内的水域点。
 
关键词: 机载激光雷达(LiDAR)水域提取点云特征分析    
Abstract: Water regions extraction is of great significance to monitoring,research,planning and development of coastal zones.The conventional method of water regions extraction based on remote sensing image often has poor accuracy in coast because there are large differences among spectral character of different water regions which often change over time as well.To solve this problem,the elevation,intensity and point-density information from the highly accurate 3D mass points of airborne LiDAR was exploited to extract water regions.Firstly,a part of water points were extracted by the characteristics of low density,and then were constrained by the elevation and intensity threshold which came from Statistical table.Secondly,A triangulation network surface model was established based on the water points got from the previous step to describe the elevation trend of water surface.Lastly,all the points which near or behind the surface model was extracted as water points.The result of the accuracy evaluation indicates that the recogniton accuracy of water points is more than 91%.
Key words: Airborne LiDAR    Water regions extraction    Point cloud    Feature analysis
收稿日期: 2017-01-10 出版日期: 2018-03-16
:  TP 79  
基金资助: 海洋公益性课题“机载多维探测系统在海监执法中的应用示范”(201305025).

作者简介: 梁茜茜(1992-),女,山东东营人,硕士研究生,主要从事激光雷达数据处理与分类方面的研究。E-mail:qian_7759@163.com.
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
梁茜茜
张汉德
孙根云
王鹏

引用本文:

梁茜茜,张汉德,孙根云,王鹏. 基于机载激光雷达数据的海岸带水域提取方法[J]. 遥感技术与应用, 10.11873/j.issn.1004-0323.2018.1.0136.

Liang Qianqian,Zhang Hande,Sun Genyun,Wang Peng. Water Regions Extraction from LiDAR Data in Coast. Remote Sensing Technology and Application, 10.11873/j.issn.1004-0323.2018.1.0136.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2018.1.0136        http://www.rsta.ac.cn/CN/Y2018/V33/I1/136

[1] 王濮,邢艳秋,王成,习晓环,骆社周. 机载LiDAR数据提取山区道路方法研究[J]. 遥感技术与应用, 2017, 32(5): 851-857.
[2] 何原荣,郑渊茂,潘火平,陈鉴知. 基于点云数据的复杂建筑体真三维建模与应用[J]. 遥感技术与应用, 2016, 31(6): 1091-1099.
[3] 王向玉,谢东辉,汪艳,陈一铭,漆建波,阎广建,张吴明. 基于地面激光雷达点云数据的单木三维重建[J]. 遥感技术与应用, 2015, 30(3): 455-460.
[4] 曾祥钊,李传荣,张正,周梅. 面向海量点云快速显示的叠加型金字塔索引结构研究[J]. 遥感技术与应用, 2015, 30(3): 534-539.
[5] 化蕾,黄洪宇,陈崇成,黄淑华.  基于激光点云数据的客家土楼三维建模[J]. 遥感技术与应用, 2015, 30(1): 115-122.
[6] 骆社周,习晓环,王成. 激光雷达遥感在文化遗产保护中的应用[J]. 遥感技术与应用, 2014, 29(6): 1054-1059.
[7] 臧立娟,姜琦刚,李远华,汤卫畅. ZY-3东北界河地区影像特征分析[J]. 遥感技术与应用, 2014, 29(5): 861-865.
[8] 王方建,习晓环,万怡平,钟开田,王成 . 大型建筑物数字化及三维建模关键技术分析[J]. 遥感技术与应用, 2014, 29(1): 144-150.
[9] 黎荆梅,周梅,李传荣. 阵列推扫式机载激光雷达三维点云解算方法研究[J]. 遥感技术与应用, 2013, 28(6): 1033-1038.
[10] 王金亮,陈联君. 激光雷达点云数据的滤波算法述评[J]. 遥感技术与应用, 2010, 25(5): 632-638.
[11] 杨存建,杨建祥,李春燕,任国业. 云南省腾冲县几种蔬菜反射光谱特征的初步分析[J]. 遥感技术与应用, 2008, 23(6): 639-642.
[12] 周淑芳,李增元,范文义,庞 勇,陈尔学,李晓松. 基于机载激光雷达数据的DEM获取及应用[J]. 遥感技术与应用, 2007, 22(3): 356-360.
[13] 陈南峰,田良虎,黄智才,林国富. 多金属矿区遥感成矿预测初探[J]. 遥感技术与应用, 1994, 9(1): 18-23.