Abstract

The Baltic Sea represents an optically complex case 2 water type, where high concentrations of water column constituents limit acquisition of benthic information. Different preprocessing steps were applied to the hyperspectral compact airborne spectrographic imager (CASI) image to extract as much useful benthic information as possible. Atmospheric correction, minimum noise fraction transform, and sun-glint correction were performed to acquire water surface reflectance data. Additionally, a water column removal procedure was applied to acquire bottom reflectance data. Although retrieved CASI water surface reflectance spectra generally matched the magnitudes and shapes of in situ measured spectra, then the applied water column correction algorithm did not yield accurate bottom reflectance spectra. Therefore, both benthic habitat and bathymetry maps were retrieved from the CASI sea surface image data set. An image-based supervised classification method produced a good quality benthic habitat map from the shallow Pakri study area (depth R 2 value of 0.88 and a root-mean-square error of 0.32 m. The assessment of the benthic substrate detectability limits in the Baltic Sea revealed that, at the wavelength of deepest light penetration (near 570 nm), the depth restriction for CASI benthic substrate detection was 7.6 m for sand, 5.0 m for green macroalgae, 3.0 m for higher order vegetation, and 3.1 m for brown macroalgae. The depth limit to which bathymetric mapping is practical in our study site was estimated to be around 3.5 to 4.0 m.

Highlights

  • Remote sensing is a widely used method for studying shallow marine and fresh water benthic environments

  • Sea surface reflectance was retrieved from the compact airborne spectrographic imager (CASI) hyperspectral sensor after completing three image correction steps: atmospheric correction, minimum noise fraction (MNF) transform, and glint correction

  • Reflectance spectra derived from the CASI sensor captured the overall spectral shapes of spectra measured with the Ramses spectrometer

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Summary

Introduction

Remote sensing is a widely used method for studying shallow marine and fresh water benthic environments. Thematic benthic habitat maps are fundamental to characterizing marine systems.[2] For mapping purposes, habitats are defined as spatially recognizable areas where the physical, chemical, and biological environment is distinctly different from surrounding areas.[3] The majority of remote sensing studies conducted in optically shallow waters have aimed at mapping the distribution of either single benthic habitat, such as monodominant seagrass beds,[4,5] or several different benthic habitats, such as heterogeneous communities of seagrasses, coral reefs, and macroalgae.[6,7,8,9,10,11,12,13,14,15,16,17,18] In addition to the spatial distribution, it is important to investigate the temporal dynamics of benthic habitats as changes in the benthic vegetation distribution pattern may indicate changes in the environmental conditions.

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