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基于DJI精灵4多光谱版无人机的红树林精细分类
作者姓名:王青青  朱俊利  任广波  刘善伟  许明明
作者单位:1.中国石油大学(华东) 青岛 266580;2.山东鲁邦地理信息工程有限公司 济南 250102;3.自然资源部第一海洋研究所 青岛 266061
基金项目:国家自然科学基金(41776182);自然资源卫星遥感业务支持服务体系(121168000000190033)
摘    要:本文基于DJI(大疆)精灵4多光谱版无人机能够同时获取地表可见光照片和多光谱影像的特点,提出了使用摄影测量技术构建冠层高度模型(CHM)的方法,并结合多光谱影像应用于红树林分类。将上述方法应用于广东省湛江红树林国家级自然保护区高桥镇研究区,结果表明:基于无人机摄影测量技术构建的红树林CHM与多光谱影像结合后能够大幅提高红树林的分类精度,可替代传统的机载激光雷达数据;DJI精灵4多光谱版无人机数据获取效率高,能够实现高精度的红树林分类,在红树林监测业务工作中具有推广应用价值。

关 键 词:无人机  多光谱  冠层高度模型  红树林分类
收稿时间:2022/12/5 0:00:00
修稿时间:2023/1/17 0:00:00

Fine classification of mangroves based on DJI Phantom 4 multispectral drone
Authors:WANG Qingqing  ZHU Junli  REN Guangbo  LIU Shanwei  XU Mingming
Institution:1.China University of Petroleum (East China), Qingdao 266580, China;2.Shandong LuBang Geographic Information Engineering Corporation, Jinan 250102, China;3.First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China
Abstract:Based on the characteristic that DJI Phantom 4 multispectral version can obtain surface optical photos and multispectral images simultaneously, this paper introduces a method, using photogrammetry technology to construct a canopy height model(CHM), and combines multispectral images to apply mangrove classification. The above method was applied to the research area of Gaoqiao Town, Zhanjiang Mangrove National Nature Reserve, Guangdong Province. The results show that the combination of mangrove and it´s CHM constructed based on UAV photogrammetry technology and multispectral imagery can greatly improve the classification accuracy of mangrove, which can replace the traditional airborne lidar data greatly; the DJI Phantom 4 multispectral version has high data acquisition efficiency, and can achieve high-precision mangrove classification, and has a very good application prospects in mangrove monitoring field.
Keywords:Unmanned aerial vehicle  Multispectral  Canopy height model  Mangrove classification
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