A novel approach for bathymetry of shallow rivers based on spectral magnitude and shape predictors using stepwise regression

Milad Niroumand-Jadidi; Francesca Bovolo; Alfonso Vitti; Lorenzo Bruzzone

doi:10.1117/12.2325560

9 October 2018 A novel approach for bathymetry of shallow rivers based on spectral magnitude and shape predictors using stepwise regression

Milad Niroumand-Jadidi, Francesca Bovolo, Alfonso Vitti, Lorenzo Bruzzone

Author Affiliations +

Proceedings Volume 10789, Image and Signal Processing for Remote Sensing XXIV; 107890O (2018) https://doi.org/10.1117/12.2325560
Event: SPIE Remote Sensing, 2018, Berlin, Germany

Abstract

Spatial heterogeneities of substrate type, water-surface roughness and also inherent optical properties (IOPs) of the water column can pose substantial challenges to optical remote sensing of fluvial bathymetry. Development of robust techniques with respect to the optical complexities of riverine environments is then central to produce accurate bathymetry maps over large spatial extents. The empirical (regression-based) techniques (e.g., Lyzenga’s model) have widely been applied for estimation of bathymetry from optical imagery in inland/coastal waters. The models in the literature are built upon only magnitude-related predictors derived from spectral radiances/reflectances at different bands. However, optically complicating factors such as variations in bottom type and water column constituents can change not only the magnitude but also the shape of water-leaving spectra. This research incorporates spectral derivatives as shaperelated predictors in order to enhance the description of spectra through the regression-based depth retrieval. A stepwise regression is utilized to select the optimal predictors among all the possible Lyzenga (i.e., magnitude-related) and derivative (i.e., shape-related) predictors. Radiative transfer simulations are used to examine the bathymetry models in optically-complex shallow rivers by considering variable bottom-types and IOPs. The methods are also applied to a WorldView-3 image of the Sarca River located in Italian Alps and resultant bathymetry estimates are assessed using insitu measurements. The results indicate the effectiveness of spectral derivatives in improving the accuracies of depth retrievals particularly for optically-complex waters.

Conference Presentation

Citation Download Citation

Milad Niroumand-Jadidi, Francesca Bovolo, Alfonso Vitti, and Lorenzo Bruzzone "A novel approach for bathymetry of shallow rivers based on spectral magnitude and shape predictors using stepwise regression", Proc. SPIE 10789, Image and Signal Processing for Remote Sensing XXIV, 107890O (9 October 2018); https://doi.org/10.1117/12.2325560

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available