1.2 Physical and Technical Principles
1.2.1 Imaging Sensor Dimensions
As discussed in the introductory section of this chapter, remote sensing data can be
differentiated by the dimensions of the imaging sensor used to capture the image
data (Table 1.1). These dimensions are outlined below and are critical for
understanding the relationship to the environmental feature being mapped, as the
dimensions control the type and level of detail of information able to be extracted
from images.
• Spectral: the location, width and number of spectral bands used to record light.
• Spatial: pixel size and image extent.
• Radiometric: levels of brightness detected.
• Temporal: the time and repetition frequency at which image data are acquired.
The spectral dimension of remotely sensed data is the primary control of the
type(s) of information able to be measured and mapped. You will notice that the
chapters in this book correspond to remote sensing instruments differentiated by
their spectral dimensions. In this chapter we introduce two primary forms of
passive or optical data: multispectral and hyperspectral. Note that aerial photography in its film-based and more recent digital format is considered to be a multispectral system. All of these sensors can be mounted on boats, underwater ROVs
and AUVs, people (e.g., divers, snorkelers), aircraft and satellites. The primary
differences between multispectral and hyperspectral image data are shown in
Fig. 1.3, where a comparison of reflectance signatures clearly shows the improved
ability of the hyperspectral band-set to discriminate different reef features, such as
bleached versus un-bleached corals.
The other fundamental control on the mapping and monitoring of coral reefs
using remote sensing is spatial dimension. This includes pixel size and image
extent (Fig. 1.4), as well as the size of the target features. Generally speaking,
image pixel size must be smaller than the length or breadth of the target feature
you wish to map. For example, to detect small coral patches, pixels \1 m are
required, while geomorphic zones can be mapped with image pixels of 10–30 m
(Fig. 1.4). Spatial and spectral dimensions also interact to define the features able
to be discriminated on reefs, where given the same spectral resolution more
information can be derived using higher spectral resolution.
Radiometric dimensions relate to the level of precision used to record light
reaching a sensor (e.g., recording 256 vs. 1,024 levels of brightness). A higher
radiometric resolution (e.g., 1,024 brightness levels) is required for detecting
subtle changes in reflection or absorption of sunlight by coral reef features.
Temporal dimension refers to the frequency with which an imaging sensor can
revisit or re-image the same location. For more dynamic reef features you may
need daily acquisitions, while yearly images may be sufficient for longer term
changes.
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S. R. Phinn et al.
1.2.1 Imaging Sensor Dimensions
As discussed in the introductory section of this chapter, remote sensing data can be
differentiated by the dimensions of the imaging sensor used to capture the image
data (Table 1.1). These dimensions are outlined below and are critical for
understanding the relationship to the environmental feature being mapped, as the
dimensions control the type and level of detail of information able to be extracted
from images.
• Spectral: the location, width and number of spectral bands used to record light.
• Spatial: pixel size and image extent.
• Radiometric: levels of brightness detected.
• Temporal: the time and repetition frequency at which image data are acquired.
The spectral dimension of remotely sensed data is the primary control of the
type(s) of information able to be measured and mapped. You will notice that the
chapters in this book correspond to remote sensing instruments differentiated by
their spectral dimensions. In this chapter we introduce two primary forms of
passive or optical data: multispectral and hyperspectral. Note that aerial photography in its film-based and more recent digital format is considered to be a multispectral system. All of these sensors can be mounted on boats, underwater ROVs
and AUVs, people (e.g., divers, snorkelers), aircraft and satellites. The primary
differences between multispectral and hyperspectral image data are shown in
Fig. 1.3, where a comparison of reflectance signatures clearly shows the improved
ability of the hyperspectral band-set to discriminate different reef features, such as
bleached versus un-bleached corals.
The other fundamental control on the mapping and monitoring of coral reefs
using remote sensing is spatial dimension. This includes pixel size and image
extent (Fig. 1.4), as well as the size of the target features. Generally speaking,
image pixel size must be smaller than the length or breadth of the target feature
you wish to map. For example, to detect small coral patches, pixels \1 m are
required, while geomorphic zones can be mapped with image pixels of 10–30 m
(Fig. 1.4). Spatial and spectral dimensions also interact to define the features able
to be discriminated on reefs, where given the same spectral resolution more
information can be derived using higher spectral resolution.
Radiometric dimensions relate to the level of precision used to record light
reaching a sensor (e.g., recording 256 vs. 1,024 levels of brightness). A higher
radiometric resolution (e.g., 1,024 brightness levels) is required for detecting
subtle changes in reflection or absorption of sunlight by coral reef features.
Temporal dimension refers to the frequency with which an imaging sensor can
revisit or re-image the same location. For more dynamic reef features you may
need daily acquisitions, while yearly images may be sufficient for longer term
changes.
12
S. R. Phinn et al.