2篇
您的检索式：作者名="Ruqing Tong"
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| 1 | Monitoring water color anomaly of lakes based on an integrated method using Landsat-8 OLI images显示文摘Water color is a crucial optical indicator of water quality,polluted water bodies often show water color anomalies.To comprehensively understand the occurrence of water color anomalies in inland lakes,an integrated method was designed using the hue angle based on the Forel-Ule Index(FUI)model,and other remote sensing indices,including the Turbid Water Index(TWI),Floating Algae Index(FAI),and Cyanobacteria and Macrophytes Index(CMI).Based on all available Landsat-8 OLI images from 2013 to 2020,continuous monitoring was conducted in three different lakes in the middle of the Yangtze River,China.The results demonstrated that:(1)The proposed method can accurately identify algal blooms,high sediment loads,and eutrophication from the abnormal water color areas;(2)The calculated hue angles of sediment-dominated water were significantly higher than those of algal blooms and aquatic vegetation,providing a noticeable visual discoloration of water;(3)These water color anomalies exhibited significant correlations with the water quality and environmental conditions.This study serves as an example for accurate and spatially continuous assessment of water color anomaly and supports practical information to facilitate local water environment conservation. | Xiaoqin Yang Ruqing Tong Li Ma Jian Li Siqi Wang Liqiao Tian | 2022 | International Journal of Digital Earth2022，15，1： | 1 |
| 2 | Atmospheric correction for HY-1C CZI images using neural network in western Pacific region显示文摘With a spatial resolution of 50 m,a revisit time of three days,and a swath of 950 km,the coastal zone imager(CZI)offers great potential in monitoring coastal zone dynamics.Accurate atmo-spheric correction(AC)is needed to exploit the potential of quantitative ocean color inversion.However,due to the band setting of CZI,the AC over coastal waters in the western Pacific region with complex optical properties cannot be realized easily.This research introduces a novel neural network(NN)AC algorithm for CZI data over coastal waters.Total 100,000 match-ups of HY-1 C CZI-observed reflectance at the top-of-atmosphere and Operational Land Imager(OLI)-retrieved high-quality remote sensing reflectance(Rrs)at the CZI bands are built to train the NN model.These reflectance data are obtained from the standard AC algorithm in the SeaDAS.Results indicate that the distributions of the CZI retrieved Rrs were consistent with the quasi-synchronous OLI data,but the spatial information from the CZI is more detailed.Then,the accuracy of the CZI data for AC is evaluated using the multi-source in-situ data.Results further show that the NN-AC can successfully retrieve Rrs for CZI and the coefficients of determination in the blue,green,red,and near-infrared bands were 0.70,0.77,0.76,and 0.67,respectively.The NN algorithm does not depend on shortwave-infrared bands and runs very fast once properly trained. | Jilin Men Jianqiang Liu Guangping Xia Tong Yue Ruqing Tong Liqiao Tian Kohei Arai Linyu Wang | 2022 | Geo-Spatial Information Science2022，25，3： | 0 |
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