Defining the Limits of Spectrally Based Bathymetric Mapping on a Large River

Remote Sensing

RyanL. Fosness¹  CarlJ. Legleiter² 

[1] U.S. Geological Survey, Idaho Water Science Center, Boise, ID 83702, USA;U.S. Geological Survey, Integrated Modeling and Prediction Division, Golden, CO 80403, USA;

关键词: fluvial remote sensing;    river;    bathymetry;    depth;    calibration;    hyperspectral;    maximum detectable depth;    Kootenai river;   

DOI  :  10.3390/rs11060665

来源: DOAJ

【 摘 要 】

Remote sensing has emerged as a powerful method of characterizing river systems but is subject to several important limitations. This study focused on defining the limits of spectrally based mapping in a large river. We used multibeam echosounder (MBES) surveys and hyperspectral images from a deep, clear-flowing channel to develop techniques for inferring the maximum detectable depth, dm a x , directly from an image and identifying optically deep areas that exceed dm a x . Optimal Band Ratio Analysis (OBRA) of progressively truncated subsets of the calibration data provided an estimate of dm a xby indicating when depth retrieval performance began to deteriorate due to the presence of depths greater than the sensor could detect. We then partitioned the calibration data into shallow and optically deep (d >dm a x) classes and fit a logistic regression model to estimate the probability of optically deep water, P r ( O D ). Applying a P r ( O D ) threshold value allowed us to delineate optically deep areas and thus only attempt depth retrieval in relatively shallow locations. For the Kootenai River, dm a xreached as high as 9.5 m at one site, with accurate depth retrieval ( R 2= 0.94) in areas with d

【 授权许可】

Unknown