| 基于小型无人机可见光遥感的蓝藻识别研究 |
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| 引用本文： | 李鑫,孙伟,李林.基于小型无人机可见光遥感的蓝藻识别研究[J].测绘与空间地理信息,2017(4). |
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| 作者姓名： | 李鑫 孙伟 李林 |
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| 作者单位： | 信息工程大学地理空间信息学院,河南郑州,450001 |
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| 摘 要： | 以无人机航拍获取的可见光影像为数据源,研究小面积水域中蓝藻的提取方法。首先采用无人机获取可见光影像,运用4种可见光植被指数对图像进行运算,提出了用于蓝藻识别的可见光归一化差异植被指数与增强型红绿差值植被指数,以人工目视解译统计得到的蓝藻面积作为判别依据。结果表明:利用增强型红绿差值植被指数对湖泊中蓝藻的分类及提取,精度可达95.89%,Kappa系数为97.03,质量稳定,精度较高。
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| 关 键 词： | 无人机 可见光 蓝藻 植被指数 支持向量机 |
Study on the Recognition of Spirulina Based on Visible Light Remote Sensing of the Small UAV |
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| LI Xin,SUN Wei,LI Lin.Study on the Recognition of Spirulina Based on Visible Light Remote Sensing of the Small UAV[J].Geomatics & Spatial Information Technology,2017(4). |
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| Authors: | LI Xin SUN Wei LI Lin |
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| Abstract: | Based on the UAV (unmanned aerial vehicle) of aerial visible light images as the data source,researching the small scope of cyanobacteria extract methods in water.First,Using UAV for optical images.The article used4 kinds of visible light vegetation index,then through the comprehensive analysis,the new index is proposed based on the normalized difference vegetation index and enhanced visible light red,green,difference vegetation index,to the blue-green area of artificial visual interpreting statistics serve as discriminant basis.The results show that the use of enhanced red and green difference vegetation index classification and extraction of blue-green algae bloom in lake,algae extraction accuracy can reach 95.89％,Kappa coefficient is 97.03,stable quality,high precision. |
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| Keywords: | UAV visible light blue-green algae vegetation index support vector machine |
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