基于WorldView-2遥感影像的龙湾港浅海水深反演

Shallow water depth inversion in Longwan Port based on WorldView-2 Remote Sensing Image

根据遥感水深反演原理,利用海南岛龙湾港的World View-2多光谱卫星数据和海图水深资料,通过对水深进行0~2,2~5,5~10,10~15和15~20 m的分区处理、潮汐改正和海图水深数据与相应图像波段反射率值的相关性分析及回归分析,建立了浅海水深线性回归反演模型,开展了浅海水深的实际计算与精度分析。结果表明:对不同水深范围分别建立线性回归模型反演的水深精度要高于未分区建立的模型;分区模型中,多波段模型在0~5 m的反演精度最高,而双波段比值模型在5~20 m的反演精度最高,但是反演水深在最浅处的精度还有待提高。本文方法提取的水深与海图水深数据变化趋势基本相似,可以满足海洋科学研究对大范围浅水水下地形探测的要求。

According to the principle of remote sensing water depth inversion, WorldView-2 multi-spectral satellite data and chart depth data of Longwan Port in Hainan Island were used. The water depths in 0-2 m, 2-5 m, 5-10 m, 10-15 m and 15-20 m were partitively treated, tidal correction,the correlation analysis and regression analysis o{ chart water depth and the corresponding image band reflectivity values were also developed, and a piecewise linear model was built for shallow water bathymetry with which the actual calculation of shallow water depth and precision analysis were carried out. The results show that the depth accuracy of the partitioned linear regression model is higher than that of the non-partitioned model in different water depth ranges. In the partition model, the multi-band model has the highest inversion accuracy of 0-5 m, and the double-band ratio model has the highest inversion accuracy of 5-20 m, but inversion of the depth in the most shallow yet to be improved. The water depth extracted by this method is similar to that of chart water depth data, which can meet the requirements of marine scientific research on large-scale shallow underwater detection requirements.