| 摘要: |
| 浒苔在近岸搁浅后会破坏海岸景观，干扰水上运动，给滨海旅游业造成严重影响。本文使用无人机搭载的多光谱和可见光传感器对山东半岛的海阳、乳山和文登的三个海滩搁浅的浒苔进行航拍监测，并结合地物光谱测量数据，分别选择归一化植被指数（NDVI）、差值植被指数（DVI）和虚拟基线高度浮藻指数（VB-FAH）对海滩搁浅浒苔与岸边植被及非植被（海水、沙滩）进行识别评估，并分别估算了三个研究区搁浅浒苔的生物量。研究结果表明：NDVI可以识别植被和非植被，但无法区分潮间带上部和潮间带下部分布的浒苔；DVI和VB-FAH对植被和非植被的区分度不高，但对不同分布的搁浅浒苔具有一定的区分度，其中，DVI对潮间带上部和潮间带下部分布浒苔的识别能力优于VB-FAH。因此，通过对岸边植被进行腌膜，利用DVI构建海滩搁浅浒苔生物量估算模型，实现了海滩搁浅浒苔生物量的估算。海阳、乳山和文登三个海滩搁浅浒苔的生物量分别为1468t、745t和5034t，本文提出的方法可以为搁浅浒苔的清理和资源合理分配提供技术支持。 |
| 关键词: 无人机遥感 绿潮 搁浅生物量 多光谱 |
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| 基金项目:国家自然科学基金项目（41876107）；山东省联合基金项目（U1706219）；中国科学院海洋大科学研究中心重点部署项目（COMS2019J02）；中国科学院前沿科学重点研究计划（ZDBS-LY-7010)；中国科学院海洋生态与环境科学重点实验室（中国科学院海洋研究所）开放基金资助（KLMEES202005）；国家重点研发计划“蓝色粮仓科技创新” 项目(2019YFD0900705) |
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| Estimation of green tide stranded biomass in the Yellow Sea based on Unmanned Aerial Vehicle(UAV) remote sensing |
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shangweitao1, gaozhiqiang1, jiangxiaopeng1, tianxinpeng1, guoshaofang2
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1.Yantai Institute of Coastal Zone Research,Chinese Academy of Sciences;2.Yantai Institute of Science and Technology Information Research
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| Abstract: |
| Ulva prolifera stranded near the shore will damage the coastal landscape, interfere with water sports, and seriously affect coastal tourism. In this paper, the multispectral and visible light sensors carried by unmanned aerial vehicle (UAV) were used to monitor the stranded Ulva prolifera on the beaches of Haiyang, Rushan and Wendeng in Shandong Peninsula. Normalized difference vegetation index (NDVI) , difference vegetation index (DVI) and the virtual baseline height floating algae index (VB-FAH) were selected to identify and evaluate beach stranded Ulva prolifera and shore vegetation and non-vegetation (sea water and sand), respectively, the biomass of stranded Ulva prolifera in three research areas were estimated. The results show that the NDVI can identify vegetation and non-vegetation, but it cannot distinguish Ulva prolifera distributed in the upper and lower tidal zones. DVI and VB-FAH do not distinguish between vegetation and non-vegetation, but they can distinguish Ulva prolifera distributed in the upper and lower tidal zones, in which the DVI is superior to the VB-FAH in identifying the distribution of Ulva prolifera in the upper and lower tide zones. Therefore, the biomass estimation model of beach stranded Ulva prolifera was established by masking shore vegetation and using DVI, the biomass of beach stranded Ulva prolifera were estimated. The biomass of stranded Ulva prolifera was 1468t, 745t and 5034t in the beaches of Haiyang, Rushan and Wendeng. The method proposed in this paper can provide technical support for the cleaning up of stranding Ulva prolifera and rational allocation of resources. |
| Key words: UAV remote sensing green tide stranded biomass multispectral |