The invention relates to the technical field of optical line protection, and discloses a river water quality monitoring method based on an unmanned aerial vehicle hyperspectral remote sensing image and machine learning, which combines the unmanned aerial vehicle hyperspectral remote sensing image with a machine learning algorithm to construct a river water quality parameter inversion model. Comprising the following steps: collecting a water sample, obtaining an unmanned aerial vehicle hyperspectral image and preprocessing; extracting an image of the river part and selecting the reflectivity of each wave band of the image; performing spectrum transformation on the original spectrum of the image, establishing an inversion data set through feature screening, and constructing a water quality parameter inversion model by using a machine learning algorithm; and simulating the water quality parameters of the river through the water quality parameter inversion model, and visualizing the simulation result. According to the method, urban inland small river water quality monitoring can be rapidly achieved at low cost, the dual problem that the time resolution and the space resolution are limited in urban small river monitoring based on satellite remote sensing images is solved, and a scientific basis is provided for urban river intelligent inversion.
本发明涉及光线路保护技术领域,公开了一种基于无人机高光谱遥感影像和机器学习的河流水质监测方法,本发明的方法将无人机高光谱遥感影像与机器学习算法相结合,构建河流水质参数反演模型,包括:采集水样、获取无人机高光谱影像并进行预处理;提取河流部分的影像并选取影像各波段的反射率;对影像的原始光谱进行光谱变换,通过特征筛选建立反演数据集,利用机器学习算法构建水质参数反演模型;通过水质参数反演模型模拟河流的水质参数,并将模拟结果可视化。本发明的方法能够快速、低成本实现城市内陆小河流水质监测,解决了基于卫星遥感影像在城市小河流监测中存在时间、空间分辨率受限的双重问题,为城市河流智能化反演提供科学依据。
River water quality monitoring method and system based on hyperspectral remote sensing of unmanned aerial vehicle
一种基于无人机高光谱遥感的河流水质监测方法及系统
2024-12-24
Patent
Electronic Resource
Chinese
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