Please wait a minute...
img

官方微信

遥感技术与应用  2015, Vol. 30 Issue (3): 504-509    DOI: 10.11873/j.issn.1004-0323.2015.3.0504
图像与数据处理     
基于无人机影像的山地人工林景观DEM构建
柴子为1,康峻2,3,王力2,赵昕3,乔海浪2,3
(1.广东省环境监测中心,广东 广州 510045;
2.中国科学院遥感与数字地球研究所,遥感科学国家重点实验室,北京 100101;
3.中国科学院大学,北京 100049)
The Construction of DEM in Mountain Plantation Landscape based on UAV Images
Chai Ziwei1,Kang Jun2,3,Wang Li2,Zhao Xin3,Qiao Hailang1
(1.Guangdong Environmental Monitoring Center,Guangzhou 510045,China;
2.The State Key Laboratory of Remote Sensing Science,Institute of Remote Sensing and Digital Earth,
Chinese Academy of Sciences,Beijing 100101,China;
3.University of Chinese Academy of Sciences,Beijing 100049,China)
 全文: PDF(2035 KB)  
摘要:

山地人工林景观的DEM构建是对景观地形信息进行描述的基础的研究内容,也是人工林景观面积、结构和蓄积量等信息提取的重要因子,具有重要的研究意义。通过无人机平台获取影像,采用立体像对拼接的方式生成正射影像并提取DEM信息,并与GPS测量数据、ASTER GDEM和SRTM数据进行比较分析。结果表明:在该区域无人机影像构建的DEM与实测高程差距最小(RMSE=8.96),具有比ASTER GDEM(RMSE=13.68)和SRTM(RMSE=11.81)更高的精度;在每个样方内的最大高程差值与最大树高最为接近(RMSE=1.813),说明无人机DEM能够反映出更多的冠层与地面分层信息,在山地人工林景观DEM构建中表现出较大潜力。

关键词: DEM无人机人工林景观正射影像    
Abstract:

The construction of DEM in mountain plantation landscape,is the basic content of describing landscape topography,plays an important role in extracting information of plantation landscape such as size,structure and living stock volume,the study has important significance.In this paper,orthophotos and DEM were extracted based on images captured by UAV platform by means of splicing stereo pairs,and were compared with GPS measured data,ASTER GDEM data and SRTM data.The result shows that,the DEM extracted based on UAV images has the closest difference with GPS measured result (RMSE=8.96),which has higher precision than ASTER GDEM (RMSE=13.68) and SRTM (RMSE=11.81) data;The closest result(RMES=1.813) of max tree heights and max elevation differences in each sample plot,shows that UAV DEM has an ability to reflect more hierarchical information between canopy and ground,which shows a greater potential in the construction of DEM in mountain plantation landscape.


Key words: DEM    UAV    Plantation    Landscape    Orthophotos
收稿日期: 2014-12-28 出版日期: 2015-08-14
:  P 231  
基金资助:

国家863计划项目(2014AA06A511,2012AA12A304),中国科学院遥感与数字地球研究所研究生所长基金(Y4SY0900CX)。

通讯作者: 康峻(1990-),男,山东青岛人,博士研究生,主要从事生态环境与全球变化研究。Email:kangjun@pku.edu.cn。    
作者简介: 柴子为(1982-),女,甘肃兰州人,工程师,主要从事生态环境监测与评价研究。Email:ziweich@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  
柴子为
康峻
王力
赵昕
乔海浪

引用本文:

柴子为,康峻,王力,赵昕,乔海浪. 基于无人机影像的山地人工林景观DEM构建[J]. 遥感技术与应用, 2015, 30(3): 504-509.

Chai Ziwei,Kang Jun,Wang Li,Zhao Xin,Qiao Hailang. The Construction of DEM in Mountain Plantation Landscape based on UAV Images. Remote Sensing Technology and Application, 2015, 30(3): 504-509.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2015.3.0504        http://www.rsta.ac.cn/CN/Y2015/V30/I3/504

[1]FAO (Food and Agricultural Organisation of the United Nations).State of the World’s Forests[M].Rome:FAO,2014.

[2]Paquette A,Messier C.The Role of Plantations in Managing the World’S Forests in the Anthropocene[J].Frontiers in Ecology and the Environment,2010,8(1):27-34.

[3]Ni W J,Sun G Q,Zhang Z Y,et al.A Heuristic Approach to Reduce Atmospheric Effects in InSAR Data for the Derivation of Digital Terrain Models or for the Characterization of Forest Vertical Structure[J].IEEE Geoscience and Remote Sensing Letters,2014,11(1):268-272.

[4]Hvidegaard S M,Sandberg S L,Forsberg R.ASTER GDEM Validation Using LiDAR Data Over Coastal Regions of Greenland[J].Remote Sensing Letters,2011,3(1):85-91.

[5]Li Deren,Li Ming.Research Advance and Application Prospect of Unmanned Aerial Vehicle Remote Sensing System[J].Geomatics and Information Science of Wuhan University,2014,39(5):505-540.[李德仁,李明.无人机遥感系统的研究进展与应用前景[J].武汉大学学报·自然科学版,2014,39(5):505-540.]

[6]Li Longfang,Zhang Zhuhao,Deng Xiaoli,et al.The 3D Modeling Method based on UAV Images[J].Engineering of Surveying and Mapping,2013,22(4):85-89.[李隆方,张著豪,邓晓丽,等.基于无人机影像的三维模型构建技术[J].测绘工程,2013,22(4):85-89.]〖HJ2mm〗

[7]Peng Peisheng,Wang Yixiang,Wu Jianqiang,et al.Three-Dimensional Visualization of Forest Landscape based on UAV Remote Sensing Images[J].Journal of North-East Forestry University,2013,41(6):61-65.[彭培盛,王懿祥,吴建强,等.基于无人机遥感影像的三维森林景观可视化[J].东北林业大学学报,2013,41(6):61-65.]

[8]Zarco-Tejada P J,Diaz-Varela R,Angileri V,et al.Tree He-ight Quantification Using Very High Resolution Imagery Acquired from an Unmanned Aerial Vehicle (UAV) and Automatic 3D Photo-reconstruction Methods[J].European Journal of Agronomy,2014,55:89-99.

[9]Rabus B,Eineder M,Roth A,et al.The Shuttle Radar Topography Mission——A New Class of Digital Elevation Models Acquired by Spaceborne Radar[J].Isprs Journal of Photogrammetry and Remote Sensing,2003,57(4):241-262.

[10]Reuter H I,Nelson A,Strobl P,et al.A First Assessment of Aster Gdem Tiles for Absolute Accuracy,Relative Accuracy and Terrain Parameters[C]//IEEE International Geoscience and Remote Sensing Symposium,2009,1-5:3665-3668.

[11]Remondino F,El-Hakim S.Image-based 3D Modelling:A Review[J].The Photogrammetric Record,2006,21:269-291.

[12]Verhoeven G.Taking Computer Vision Aloft-Archaeological Thr-ee-dimensional Reconstructions from Aerial Photographs with PhotoScan[J].Archaeological Prospection,2011,18(1):67-73.

[13]Tavani S,Granado P,Corradetti A,et al.Building a Virtual Outcrop,Extracting Geological Information from It,and Sharing the Results in Google Earth via Open Plot and Photoscan:An Example from the Khaviz Anticline (Iran)[J].Computers & Geosciences,2014,63:44-53.

[14]Chen Jiading,Zheng Zhongguo.Probability and Statistics[M].Beijing:Peking University Press,2007.[陈家鼎,郑忠国.概率与统计[M].北京:北京大学出版社,2007.]

[1] 李晨伟,张瑞丝,张竹桐,曾敏 . 基于多源遥感数据的构造解译与分析—以西藏察隅吉太曲流域为例[J]. 遥感技术与应用, 2018, 33(4): 657-665.
[2] 赵云,谢东海,邓磊,闫亚男,李博旭. 利用多角度影像计算BRDF的方法与系统实现[J]. 遥感技术与应用, 2018, 33(4): 741-749.
[3] 卢惠敏,李飞,张美亮,杨刚,孙伟伟. 景观格局对杭州城市热环境年内变化的影响分析[J]. 遥感技术与应用, 2018, 33(3): 398-407.
[4] 何艺,周小成,黄洪宇,许雪琴. 基于无人机遥感的亚热带森林林分株数提取[J]. 遥感技术与应用, 2018, 33(1): 168-176.
[5] 赵梦雨,薛亮. 咸阳市生境质量变化遥感监测研究[J]. 遥感技术与应用, 2017, 32(6): 1171-1180.
[6] 曹晓晨,尤红建,刘佳音,王峰. 基于误差建模的SRTM高程精度提升方法研究[J]. 遥感技术与应用, 2017, 32(5): 801-808.
[7] 郑飞,张殿发,孙伟伟,杨刚. 基于ASTER遥感的杭州城市热/冷岛的景观特征分析[J]. 遥感技术与应用, 2017, 32(5): 938-947.
[8] 周在明,杨燕明,陈本清. 基于无人机影像的滩涂入侵种互花米草植被信息提取与覆盖度研究[J]. 遥感技术与应用, 2017, 32(4): 714-720.
[9] 王琳,武虹. 基于DEM的遗址域定量算法及可获取耕地统计[J]. 遥感技术与应用, 2017, 32(2): 274-281.
[10] 褚洪亮,肖青,柏军华,程娟. 基于无人机遥感的叶面积指数反演[J]. 遥感技术与应用, 2017, 32(1): 140-148.
[11] 李爱农,边金虎,张正健,赵伟,南希,孙志宇,唐明坤,俄尕. 若尔盖高原区域碳收支参量多尺度遥感综合观测试验:科学目标与试验设计[J]. 遥感技术与应用, 2016, 31(3): 405-416.
[12] 张正健,李爱农,边金虎,赵伟,南希,雷光斌,谭剑波,夏浩铭,汪阳春,杜小林,林家元. 基于无人机的山地遥感观测平台及可靠性分析—以若尔盖试验为例[J]. 遥感技术与应用, 2016, 31(3): 417-429.
[13] 满卫东,李春景,王宗明,贾明明,毛德华,刘明月,路春燕. 基于面向对象分类方法的乌苏里江流域中俄跨境区域湿地景观动态研究[J]. 遥感技术与应用, 2016, 31(2): 378-387.
[14] 张正健,李爱农,边金虎,赵伟,南希,靳华安,谭剑波. 基于无人机影像可见光植被指数的若尔盖草地地上生物量估算研究[J]. 遥感技术与应用, 2016, 31(1): 51-62.
[15] 张洋华,刘慧平,杨晓彤. 基于像元与对象分类的景观指数差异性分析[J]. 遥感技术与应用, 2016, 31(1): 119-125.