A Multiband Model With Successive Projections Algorithm for Bathymetry Estimation Based on Remotely Sensed Hyperspectral Data in Qinghai Lake

Lake bathymetry plays a pivotal role in environmental monitoring, ecological management, water quality protection, etc. Hyperspectral remote sensing technology can provide large-scale coverage and more detailed spectral information for estimation than traditional measurements or multispectral imagery techniques. In this study, multiband linear model with successive projections algorithm (SPA-MLM) was developed to retrieve the of Qinghai Lake, which is largest inland saltwater lake China. The three most sensitive bands were first selected by SPA, established least squares method combined situ measured depth. Zhuhai-1 hyperspectral remotely sensed employed as data source. all, 98 matched obtained images during surveys performed May, September, October 2020. results demonstrated that retrieval be used accurately estimate depth study area, an accuracy exceeding approximately 90%, suggests proposed performs better those previous studies employing imagery. correlation coefficient reaches 0.92, root-mean-square error 1.26 m. This demonstrates using effective detection large-scale, rapid monitoring relevant decision-making departments.