Research on retrieval method of coastal water salinity based on optical satellite remote sensing
The salinity information of surface water in the coastal zone can reflect the ecological status of seawater invasion,coastline degradation and land salinization,which is of great significance to the research,protection,and resource development of marine and terrestrial ecosystems in the coastal region.However,its monitoring mainly relies on field tests,and the technical means are relatively simple.Since satellite remote sensing has the advantage of high efficiency and wide range,this paper adopts optical remote sensing satellite with high spatial resolution to carry out research on inversion method of surface water salinity in coastal zones.Based on analysis of single-band reflectance,band ratio,and correlation between commonly used spectral index and water salinity,the sensitive band of water salinity is determined.The empirical model,semi-empirical model,and random forest model are constructed,and the accuracy and results of salinity inversion are compared and analyzed.The results show that the random forest model has high accuracy,with the determination coefficient R2 of 0.81 and the RMSE of 193.01 μS/cm,and its accuracy is stable.The semi-empirical radiative transfer model has the determination coefficient R2 of 0.53 and the RMSE of 303.82 μS/cm.The empirical statistical model has the determination coefficient R2 of 0.16 and the RMSEof 407.46 μS/cm.This study provides an important technical approach to grasp the spatial characteristics of surface water quality in coastal zones,analyze the temporal changes of water quality,and evaluate the availability of water resources.It is of great significance to the investigation,monitoring,restoration,and management of coastal ecological environment.
coastal zone remote sensingwater salinityempirical statistical modelmachine learningSERT model
万方数据
维普
