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| 基于无人机多光谱影像的城市河道水质反演 |
| Inversion of Urban River Water Quality Based on UAV Multispectral Image |
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| DOI： |
| 中文关键词: 氨氮 多光谱影像 反演模型 无人机 水质 |
| 英文关键词: Ammonia nitrogen Multispectral image Inverse model Unmanned aerial vehicle Water quality |
| 基金项目:国家重点研发计划基金资助项目（No2020YFC1807402）；南京市水务科技基金资助项目（202307） |
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| 中文摘要: |
| 利用无人机多光谱反射率影像和同步实测水质数据，建立基于机器学习的水质参数反演模型，并将该模型应用于张家港河。结果表明，基于XGBoost和随机森林的特征变量重要性分析方法选择氨氮反演的最佳波段组合，确定用随机森林进行氨氮反演精度较高，其测试集决定系数为091，平均绝对百分比误差为2357%；反演结果能从空间上精细地反映张家港河光明村段支流水质的特点，并直观展示水质超标重点区域。 |
| 英文摘要: |
| A water quality parameter inversion model was established based on machine learning and by using UAV multispectral reflectance image to detect water quality. Applying this model to inverting the water quality of Zhangjiagang River， the results indicated that random forest algorithm had high accuracy in inverting ammonia nitrogen on the optimal band combination selected by feature variable importance analysis based on XGBoost and random forest. The determination coefficient of the test set was 0.91， and the average absolute percentage error was 23.57%. The inversion results could accurately reflect the water quality characteristics of the tributaries in Guangmingcun section of Zhangjiagang River in space， and visually displayed the key areas where water quality exceeding the standard. |
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