基于自适应经验半解析模型的无控水深反演方法—以中国南海为例

Bathymetry Inversion Method Based on Adaptive Empricial Semi-Analytical Model without in situ Data-A Case Study in South China Sea

卫星水深反演作为声学测量的一种补充手段在争议岛礁区发挥着重大作用。但由于实测水深数据的缺失和多光谱影像可见光波段数的限制,传统经验模型和半解析模型都无法使用。为此针对只有3个可见光波段的遥感影像,提出一种不需要实测水深数据的自适应经验半解析模型。新模型根据联合半解析模型和两种经验模型得到的部分像素水深,协同自适应线性比值模型可以确定出最终结果。使用Sentinel-2影像(空间分辨率为10 m)在甘泉岛和浪花礁对AESM、Log_ratio模型和L-S(Log-ratio and Semianalytical)模型展开测试,将计算结果与水深数据进行比对。结果表明,新模型的均方根误差(RMSE)在甘泉岛和浪花礁分别为1.14 m和1.55 m,反演精度稍优于使用200个水深数据训练的Log_ratio模型,相比于同样不需要水深数据的L-S模型,RMSE分别减少了0.12 m和1.25 m。

As a supplementary means of acoustic measurement,satellite depth inversion plays an important role in disputed islands and reefs.However,due to the lack of measured water depth data and the limitation of the number of visible light segments in multi-spectral images,the traditional empirical model and semi-analytical model can not be used.Aiming at the remote sensing images with only three visible bands,an adaptive empirical semi-analytical model without measured water depth data is proposed.The new model is based on the partial pixel water depth obtained by the joint semi-analytical model and two empirical models,and the cooperative adaptive linear ratio model can determine the final result.The Sentinel-2 image(spatial resolution is 10 m)is used to test the AESM model,Log_ratio model and Log-ratio and Semianalytical(L-S)model in Ganquan island and Langhua reef,and the calculated results are compared with the water depth data.The results show that the root mean square error(RMSE)of the new model is 1.14 m in Ganquan island and 1.55 m in Langhua reef,respectively.The inversion accuracy of the new model is slightly better than that of the Log_ratio model trained with 200 water depth data.Compared with the L-S model,which also does not require water depth data,the RMSE of the new model is reduced by 0.12 m and 1.25 m,respectively.