摘要
以丹江口水库为例,采用Sentinel-1A合成孔径雷达(SAR)和Sentinel-2A/B多光谱成像仪(MSI)联合提取水域面积,通过建立多源传感器(SAR和MSI)所提取水域面积差异的定量函数关系,修正二者水域面积之间的差异,并将修正后的水域面积与Sentinel-3A雷达高度计(RA)所提取的水位相结合,开展水库蓄水量反演研究,最后以“全国水雨情网”公布的实测数据等为参考,评估水库特征参数的反演精度。结果表明:由RA数据提取的遥测水位与实测水位相比,R^(2)达到0.99以上,RMSE达到0.0933,遥测水位与实测水位的平均误差仅有9.33 cm;相对于单一MSI影像或SAR影像所提取的水域面积,二者水域面积联合参与建立的“遥测水位-多源遥感水域面积”模型的R^(2)和RMSE均有所优化,其中,R^(2)分别提高了0.26%和0.60%,RMSE分别降低了2.63和1.29;由遥测水位和多源遥感水域面积结合水库蓄水量模型反演的蓄水量与标准蓄水量相比,R^(2)达到0.99,RMSE达到1.177,相对误差平均为1.8%。研究结果表明:利用多源遥感技术开展水库特征参数的反演研究,能够更加准确地反映水库的运行状态。
Take Danjiangkou Reservoir as an example,the water area was extracted by using the Sentinel-1A Synthetic Aperture Radar(SAR)and Sentinel-2A/B Multi-Spectral Imager(MSI),the difference of water areas by SAR and by MSI was corrected by establishing a quantitative function relation of these areas,and the revised water area was combined with the inverted water level of Sentinel-3A Radar Altimeter(RA)to calculate the reservoir volume.Finally,the retrieval precision of the reservoir parameters was evaluated according to the measured data published by the National Water and rain regime network.The results showed that R^(2) was above 0.99 and RMSE was 0.0933,which meant that the average error between inverted water level and measured water level was only 9.33 cm.Compared with the water area extracted from single MSI image or SAR image,the R^(2) and RMSE of the"remote sensing water level-Multi-Source Remote Sensing water area"model were optimized,especially R^(2) increased by 0.26%and 0.60%,while RMSE decreased by 2.63 and 1.29,respectively.Compared with the standard water storage,for the novel model,R^(2) reached 0.99 and RMSE reached 1.177,respectively,and the relative error was 1.8%on average.The result shows that the reservoir characteristic parameters inversion using multi-source remote sensing technology can more accurately reflect the operation of the reservoir.
作者
李闯
李兵
王宁
LI Chuang;LI Bing;WANG Ning(College of Computer and Information Engineering,Henan University,Kaifeng 475004,China;Henan Key Laboratory of Big Data Analysis and Processing,Kaifeng 475004,China;Henan Engineering Research Center of Intelligent Technology and Application,Kaifeng 475004,China;College of Information and Communication Engineering,North University of China,Taiyuan 030051,China;College of Information Engineering,Zhengzhou University,Zhengzhou 450001,China)
出处
《人民长江》
北大核心
2021年第11期92-99,共8页
Yangtze River
基金
国家自然科学基金项目(U1604145)。
关键词
水库特征参数
多源遥感
雷达高度计
多光谱成像仪
合成孔径雷达
reservoir characteristic parameters
multi-source remote sensing
Rader Altimetry
Multi-Spectral Instrument
Synthetic Aperture Radar
