Abstract
The coastal shallow water zone can be a challenging and costly environment in which to acquire bathymetry and other oceanographic data using traditional survey methods. Much of the coastal shallow water zone worldwide remains unmapped using recent techniques and is, therefore, poorly understood. Optical satellite imagery is proving to be a useful tool in predicting water depth in coastal zones, particularly in conjunction with other standard datasets, though its quality and accuracy remains largely unconstrained. A common challenge in any prediction study is to choose a small but representative group of predictors, one of which can be determined as the best. In this respect, exploratory analyses are used to guide the make-up of this group, where we choose to compare a basic non-spatial model versus four spatial alternatives, each catering for a variety of spatial effects. Using one instance of RapidEye satellite imagery, we show that all four spatial models show better adjustments than the non-spatial model in the water depth predictions, with the best predictor yielding a correlation coefficient of actual versus predicted at 0.985. All five predictors also factor in the influence of bottom type in explaining water depth variation. However, the prediction ranges are too large to be used in high accuracy bathymetry products such as navigation charts; nevertheless, they are considered beneficial in a variety of other applications in sensitive disciplines such as environmental monitoring, seabed mapping, or coastal zone management.
Highlights
The term, “remote sensing” encompasses a series of well established procedures for bathymetric surveys of the seabed [1,2], but these procedures are not without limitations in terms of both the sensors and those imposed by the environment [3]
This relationship is global reflecting the bay as a whole. In investigating this relationship locally, it was found to vary across the bay, where the relationship weakened according to increasing water depth. This heterogeneity in the satellite derived relative depth (SDRD).T to WD relationship was accounted for in three of the five study predictors (GWR, GWRK and kriging with an external drift (KED)-LN), whilst the relationship is naively assumed to be homogeneous in the remaining predictors (MLR and KED-GN)
RapidEye multispectral sensors were primarily designed for land applications, in this study they are used satisfactorily for bathymetric mapping in a representative coastal embayment
Summary
The term, “remote sensing” encompasses a series of well established procedures for bathymetric surveys of the seabed [1,2], but these procedures are not without limitations in terms of both the sensors and those imposed by the environment [3]. Active remote sensing for bathymetry is generally represented by ship borne multi-beam echo sounding (MBES) sensor arrays [4]. A second non-imaging method known as satellite altimetry can be used to measure the geoidal height and marine gravity field which, in turn, can be used to determine the water depth from the linear relationship between the gravity anomaly and square of the depth [7]. This method is only suitable for deep sea, for example, surveying large sea mounts [8]. LiDAR is not ideal for all water types, as experience gained in Irish waters from the INFOMAR [9]
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