Generalized Lyzenga's Predictor of Shallow Water Depth for Multispectral Satellite Imagery

Abstract

Multispectral satellite remote sensing can predict shallow-water depth distribution inexpensively and exhaustively, but it requires many in-situ measurements for calibration. To extend its feasibility, we improved and employed a recently developed technique, for the first time, to obtain a generalized predictor of depth. We used six WorldView-2 images and obtained a predictor that yielded a 0.648 m root-mean-square error against a dataset with a 5.544 m standard deviation of depth. The predictor can be used with as few as two pixels with known depth per image, or with no depth data whatsoever, if only relative depth is needed. (98 words) Subject termsBathymetry, multispectral, satellite remote sensing, coral reef 4 Main Text

A Simple Method for Extracting Water Depth From Multispectral Satellite Imagery in Regions of Variable Bottom Type

“…Lyzenga, (1978Lyzenga, ( , 1981 proposed a basic algorithm for calculating water depth from satellite imagery based on the Beer-Lambert Law of Absorption, which specifies a log-linear relationship between reflectance and water depth. Due to its efficacy and simplicity, the Lyzenga method has been adapted and widely applied to the bathymetric mapping of shallow marine environments (Bierwirth & Burne, 1993;Clark et al, 1987;Dierssen et al, 2003;Figueiredo et al, 2016;Hogrefe, Wright, & Hochberg, 2008;Hogrefe et al, 2008;Kanno et al, 2013;Liang et al, 2017;Lyons et al, 2011;Lyzenga, 1985;Lyzenga et al, 2006;Manessa et al, 2014;Misra et al, 2018;Mumby et al, 1998;O'Neill & Miller, 1989;Paredes & Spero, 1983;Philpot, 1989;Polcyn et al, 1970;Spitzer & Dirks, 1987).…”

Satellite Derived Bathymetry Using Machine Learning and Multi-Temporal Satellite Images

“…Another method that is currently in use for bathymetric measurement is depth estimation via remote sensing, using multi-spectral or hyper-spectral sensors. Many studies have been conducted using this method since the 1970s [3][4][5][6][7][8][9][10][11][12][13][14]. The use of satellite images helps to obtain information about areas that are difficult to access by boat or airplane.…”

“…With regard to multi-spectral sensors, studies have used satellite images with a high spatial resolution greater than 30 m, such as those of the Landsat, SPOT, IKONOS, and WorldView satellites [3,[6][7][8][9][10][12][13][14]. As analysis methods, an empirical method [8] and physics-based semi-empirical methods [3,9] have been developed and used in SDB studies.…”

Determination of the Best Methodology for Bathymetry Mapping Using Spot 6 Imagery: A Study of 12 Empirical Algorithms

“…A decade after, for the first time used a commercial satellite data LANDSAT TM to extract the depth of using a linearized regression of single band (Lyzenga 1985), this method was based on previous publication (Lyzenga 1978). Since that time the algorithm has been redeveloped and applied to the newest multispectral image: LANDSAT-TM and ETM (Clark et al 1987;Van Hengel and Spltzer 1991;Bierwirth et al 1993;Daniell 2008), SPOT 4 and SPOT 5 (Melsheimer and Chin 2001;Lafon et al 2002;Liu et al 2010;Sánchez-Carnero et al 2014), IKONOS (Stumpf et al 2003;Hogrefe et al 2008;Su et al 2014), QuickBird (Conger et al 2006;Mishra et al 2006;Lyons et al 2011), LANDSAT-OLI (Pacheco et al 2015;Vinayaraj et al 2016;Kabiri 2017;Pushparaj and Hegde 2017), and Worldview-2 (Lee and Kim 2011;Deidda and Sanna 2012;Doxani et al 2012;Bramante et al 2013;Kanno et al 2013;Yuzugullu and Aksoy 2014;Eugenio et al 2015;Manessa et al 2016b;Guzinski et al 2016;Hernandez and Armstrong 2016;Kibele and Shears 2016;Manessa et al 2016a).…”