The late-1970s saw the continuation of SMS into the GOES satellite series (U.S.), and
also the launch of other geostationary satellite series that have continued to the
present: GMS (Japan; now MTSAT) and METEOSAT (Europe; now Meteosat Second Generation, MSG). With the more recent additions of the Electro series (Russia,
1994–1998, 2011) and Kalpana-1 (India, 2002) there is the potential, through data
sharing arrangements, for overlapping coverage of SST and other environmental
parameters from geostationary satellites orbiting at longitudes 135°W, 75°W, 60°W,
0°, 57.5°E, 74°E and 76.8°E. It is of note that the Feng Yun 2 GEO satellite of the
China Meteorological Administration briefly operated at 105°E in 1997–1998.
11.2.4 Thermal Processing Requirements
Satellite-borne instruments measure the radiation from the target in specified wavelength channels, which can then be converted to an apparent temperature by way of
Planck’s law (Eq. 11.1). This assumes perfect emissivity (unity), which is inaccurate
for Earth emissions and must be corrected. As such, the physical temperature can be
extracted through empirical relationships developed during sensor calibration using
temperature-brightness relationships derived from multiple bands (split-window
algorithm). Most algorithms rely upon a reference temperature, often based on lowerresolution data, to provide an initial estimate of the temperature. With improvements
in measurements and modeling of the atmosphere and related impacts on absorption
and scattering of emissions, so-called ‘‘physical retrievals’’ of temperature can now
be determined using local conditions rather than global calibration parameters.
Processing necessarily also includes geo-registration to reference data to the
Earth’s surface through modeling of the satellite location and correlation of image
features (e.g., coastlines). Limitations of onboard storage capacity may require
sub-sampling of data prior to download (e.g., the AVHRR Global Area Coverage
stores the average of measured values from four of every five cross-track pixels
and every third scan line, resulting in a 4 9 4 km pixel value derived from an
approximately 1.1 9 4 km area). For the coral reef user, it is important to recognize the constraints (and associated uncertainties) that impact the accuracy of
measured values and reported location.
It is of note that microwave emissions also include information on sea surface
salinity, whereas infrared emissions do not. Because of this, comparison of
observations from these different bands leads to salinity measurement. Changes in
salinity can result in stress to corals. However, satellite observations of sea surface
salinity are relatively nascent and do not have spatial resolution that is currently
applicable to coral reef management.
Sea surface temperature derived from satellite is widely available for use by
coral reef stakeholders. Significant research into ecosystem impacts related to
thermal variation has been undertaken and has resulted in management tools that
are distributed via the internet. Chapter 12 outlines these efforts and provides
examples of their applicability for coral reef management.
11 Thermal and Radar Overview
297
also the launch of other geostationary satellite series that have continued to the
present: GMS (Japan; now MTSAT) and METEOSAT (Europe; now Meteosat Second Generation, MSG). With the more recent additions of the Electro series (Russia,
1994–1998, 2011) and Kalpana-1 (India, 2002) there is the potential, through data
sharing arrangements, for overlapping coverage of SST and other environmental
parameters from geostationary satellites orbiting at longitudes 135°W, 75°W, 60°W,
0°, 57.5°E, 74°E and 76.8°E. It is of note that the Feng Yun 2 GEO satellite of the
China Meteorological Administration briefly operated at 105°E in 1997–1998.
11.2.4 Thermal Processing Requirements
Satellite-borne instruments measure the radiation from the target in specified wavelength channels, which can then be converted to an apparent temperature by way of
Planck’s law (Eq. 11.1). This assumes perfect emissivity (unity), which is inaccurate
for Earth emissions and must be corrected. As such, the physical temperature can be
extracted through empirical relationships developed during sensor calibration using
temperature-brightness relationships derived from multiple bands (split-window
algorithm). Most algorithms rely upon a reference temperature, often based on lowerresolution data, to provide an initial estimate of the temperature. With improvements
in measurements and modeling of the atmosphere and related impacts on absorption
and scattering of emissions, so-called ‘‘physical retrievals’’ of temperature can now
be determined using local conditions rather than global calibration parameters.
Processing necessarily also includes geo-registration to reference data to the
Earth’s surface through modeling of the satellite location and correlation of image
features (e.g., coastlines). Limitations of onboard storage capacity may require
sub-sampling of data prior to download (e.g., the AVHRR Global Area Coverage
stores the average of measured values from four of every five cross-track pixels
and every third scan line, resulting in a 4 9 4 km pixel value derived from an
approximately 1.1 9 4 km area). For the coral reef user, it is important to recognize the constraints (and associated uncertainties) that impact the accuracy of
measured values and reported location.
It is of note that microwave emissions also include information on sea surface
salinity, whereas infrared emissions do not. Because of this, comparison of
observations from these different bands leads to salinity measurement. Changes in
salinity can result in stress to corals. However, satellite observations of sea surface
salinity are relatively nascent and do not have spatial resolution that is currently
applicable to coral reef management.
Sea surface temperature derived from satellite is widely available for use by
coral reef stakeholders. Significant research into ecosystem impacts related to
thermal variation has been undertaken and has resulted in management tools that
are distributed via the internet. Chapter 12 outlines these efforts and provides
examples of their applicability for coral reef management.
11 Thermal and Radar Overview
297