基于GF5-AHSI遥感数据的横沙浅海水深反演

高光谱遥感水深反演是一种对传统水深测量方法的补充，具有方便、快捷、经济等突出优势。本文研究区位于上海横沙，属于典型滩涂浅水区，研究数据包括GF5-AHSI高光谱遥感数据和同时期的水深数据。通过数据变换和相关分析等方法提取建模参数，利用单波段比值模型、多元线性回归模型、最优标度回归模型和BP神经网络模型实现该区域水深反演，并对4种模型反演结果的准确性进行了验证和比较。研究发现：最优标度回归模型优于其他3种模型，R2达到了0.972，RMSE为0.47 m，适用于横沙浅海水深反演。

Inversion of shallow water depth in Hengshabased on GF5-AHSI remote sensing data

Hyperspectral remote sensing water depth inversion which has many advantages such as convenience, quickness, and economy is a supplement to traditional measurement methods of water depth, and is worth studying. The research area of this study is located in Hengsha, Shanghai, which is a typical shallow water area of tidal flats. The research data was obtained from GF5-AHSI hyperspectral remote sensing and measurement of water depth at the same time. The modeling parameters were extracted through data transformation and correlation analysis. The single-band ratio model, multivariate linear regression model, optimal scale regression model and BP neural network model were used for water depth inversion in this area. By comparing and verifying the accuracy of the four models, it is found that the optimal scale regression model is better than the other three models, with R2 reaching 0.972 and RMSE of 0.47 m, which is suitable for inversion of shallow water depth in Hengsha.