其他题名Information extraction of Ulva Prolifera from coastal landscape using UAV m ultispectral remote sensing images
李冬雪; 高志强
; 尚伟涛; 姜晓鹏; 宋德彬; 张媛媛发表期刊海洋环境科学
ISSN1007-6336
2020-05-26
卷号39期号:03页码:438-446
关键词浒苔海滨景区无人机植被指数生物量
产权排序(1) 中国科学院烟台海岸带研究所; (2) 中国科学院大学
作者部门海岸带信息集成与综合管理实验室
英文摘要Since 2007,green tides（also called Ulva prolifera） occurred every summer in the Yellow Sea,causing ecological problems in the coastal environment of Shandong Peninsula.A large number of Ulva prolifera on shore will rot and stink if not handled in time,which seriously affects the tourism and the health of residents in coastal landscape.In order to improve the accuracy of monitoring green tide disasters,and to improve the efficiency of the cleaning up and disposal of Ulva prolifera at key prevention and control area,In this study,the high-precision image of UAV is used to monitor the green tide disaster in Yintan landscape of Rushan City.With the spectral characteristics of Ulva prolifera and coastal vegetation measured by spectroradiometer,four vegetation indices were used to analyze and identify the Ulva prolifera and coastal vegetation,and to verify the extraction of Ulva prolifera and coastal vegetation under different vegetation indices,and based on this extraction method,the biomass of coastal green tide algae was estimated.The results show that in the red-edge band,Ulva prolifera and coastal vegetation can be distinguished. MTCI（MERIS terrestrial chlorophyll index） is more suitale,with the accuracy of 91.3%,followed by SRredge,NDVIredge and MSRredge,with the accuracy of 85.3%,83.8% and 81.2%,respectively; Estimation model of biomass based on MTCI index showed that about 600 tons of Ulva prolifera were estimated in 300 m study area.An effective method for dynamic monitoring and cleaning up of green tide disaster is provided.
中文摘要2007年以来,黄海绿潮(浒苔)灾害连年大规模暴发,对山东半岛近岸海域生态环境造成严重影响,大量靠岸浒苔若处置不及时会腐烂发臭,严重影响海滨景区旅游业及附近居民健康。为了提高绿潮灾害重点区域遥感监测的精度、提升靠岸浒苔预警的准确性和浒苔清理的工作效率,本研究利用无人机航拍的高精度影像对乳山市银滩海滨景区绿潮灾害进行监测,结合地物光谱仪实地测量浒苔和岸边植被的光谱特征,通过四种植被指数对浒苔和岸边植被进行光谱分析和识别对比,验证不同植被指数下浒苔和岸边植被的提取情况,并基于提取方法对靠岸浒苔生物量进行估算。研究表明:在红边波段,浒苔和岸边植被具有明显的可区分性,使其可以利用MTCI(MERIS terrestrial chlorophyll index)、NDVI_(redge)、SR_(redge)、MSR_(redge)四种植被指数与岸边植被进行区分,MTCI区分提取效果最好,精度可达91.3%,其次是SR_(redge)、NDVI_(redge)、MSR_(redge),提取精度分别为85.3%,83.8%,81.2%;利用MTCI指数建立的生物量估算模型,估算的300 m研究区内靠岸浒苔约600 t,为海滨景区绿潮灾害动态监测及清理工作提供有效方法。
文章类型期刊论文
资助机构国家自然科学基金项目(41876107); 山东省联合基金项目(U1706219); 科技部基础支撑项目(2014FY210600); 青岛海洋科学与技术国家实验室鳌山科技创新计划项目(2016ASKJ02)
收录类别CSCD
语种中文
引用统计
文献类型期刊论文
条目标识符http://ir.yic.ac.cnhttp://ir.yic.ac.cn/handle/133337/25172
专题中科院海岸带环境过程与生态修复重点实验室
中科院海岸带环境过程与生态修复重点实验室_海岸带信息集成与战略规划研究中心
作者单位1.中国科学院烟台海岸带研究所;
2.中国科学院大学
推荐引用方式
GB/T 7714李冬雪,高志强,尚伟涛,等. 基于无人机多光谱影像的海滨景区浒苔信息提取研究[J]. 海洋环境科学,2020,39(03):438-446.
APA李冬雪,高志强,尚伟涛,姜晓鹏,宋德彬,&张媛媛.(2020).基于无人机多光谱影像的海滨景区浒苔信息提取研究.海洋环境科学,39(03),438-446.
MLA李冬雪,et al."基于无人机多光谱影像的海滨景区浒苔信息提取研究".海洋环境科学 39.03(2020):438-446.
PDF全文下载地址:
点我下载PDF
