suitable bands for use in empirical and semi-analytic methods for estimating the
depth of the water column in each pixel (Stumpf et al. 2003; Dekker et al. 2011);
however, the limitations associated with these approaches should be clearly noted in
terms of depth restrictions and errors introduced by heterogeneous benthic features.
1.2.5 Hyperspectral Imaging Systems
Hyperspectral airborne and satellite systems typically have 10–1,000 spectral
bands per pixel, resulting in detailed spectral reflectance signatures (Figs. 1.3 and
1.5). This increased level of precision in the spectral dimension allows small
deviations in reflectance signatures to be detected and the magnitude of different
absorption and reflectance features to be quantified. Like multispectral systems,
the pixel size of an image will also control the types and number of features that
can be mapped. Hyperspectral data allow more detailed mapping of benthic cover
types since the differences in the structure or chemistry of coral reef features can
be better detected. Hence, mapping of benthic communities to the level of live
coral, different coral structural forms, dead coral, and macro- and micro-algae is
possible (Mumby et al. 1998; Hochberg and Atkinson 2000, 2003; Goodman and
Ustin 2003; Hochberg et al. 2003; Andréfouët et al. 2004b; Mumby et al. 2004a).
Although a significant amount of work has been completed on field spectrometry
to more explicitly relate hyperspectral signatures of coral reefs to pigment content
and other functional properties, little work has been published scaling that up to
image-based mapping (Brock et al. 2006; Hochberg and Atkinson 2008).
1.3 Image Processing
When using remotely sensed data on coral reefs it is essential to understand how
the image or image-based map was produced. Chapters 2– 4 outline the types of
processing applied to multispectral and hyperspectral images to produce thematic
or quantitative maps of coral reef properties. Understanding the suitability and
quality of these map products requires knowledge of both the forms of remote
sensing data and the processing steps used to generate the maps. As an example of
this process, Fig. 1.6 illustrates an overview of the different steps used for generating a benthic cover map from multispectral QuickBird imagery.
1.3.1 Image Preprocessing
Image data sets directly output from airborne or satellite imaging systems are first
subjected to a series of image preprocessing operations where algorithms are
1 Visible and Infrared Overview
17
depth of the water column in each pixel (Stumpf et al. 2003; Dekker et al. 2011);
however, the limitations associated with these approaches should be clearly noted in
terms of depth restrictions and errors introduced by heterogeneous benthic features.
1.2.5 Hyperspectral Imaging Systems
Hyperspectral airborne and satellite systems typically have 10–1,000 spectral
bands per pixel, resulting in detailed spectral reflectance signatures (Figs. 1.3 and
1.5). This increased level of precision in the spectral dimension allows small
deviations in reflectance signatures to be detected and the magnitude of different
absorption and reflectance features to be quantified. Like multispectral systems,
the pixel size of an image will also control the types and number of features that
can be mapped. Hyperspectral data allow more detailed mapping of benthic cover
types since the differences in the structure or chemistry of coral reef features can
be better detected. Hence, mapping of benthic communities to the level of live
coral, different coral structural forms, dead coral, and macro- and micro-algae is
possible (Mumby et al. 1998; Hochberg and Atkinson 2000, 2003; Goodman and
Ustin 2003; Hochberg et al. 2003; Andréfouët et al. 2004b; Mumby et al. 2004a).
Although a significant amount of work has been completed on field spectrometry
to more explicitly relate hyperspectral signatures of coral reefs to pigment content
and other functional properties, little work has been published scaling that up to
image-based mapping (Brock et al. 2006; Hochberg and Atkinson 2008).
1.3 Image Processing
When using remotely sensed data on coral reefs it is essential to understand how
the image or image-based map was produced. Chapters 2– 4 outline the types of
processing applied to multispectral and hyperspectral images to produce thematic
or quantitative maps of coral reef properties. Understanding the suitability and
quality of these map products requires knowledge of both the forms of remote
sensing data and the processing steps used to generate the maps. As an example of
this process, Fig. 1.6 illustrates an overview of the different steps used for generating a benthic cover map from multispectral QuickBird imagery.
1.3.1 Image Preprocessing
Image data sets directly output from airborne or satellite imaging systems are first
subjected to a series of image preprocessing operations where algorithms are
1 Visible and Infrared Overview
17