298
J.C. Ritchie and ER. Schiebe
results in turbid impoundments being cooler than its clear water neighbor (Schiebe
et al. 1976).
Seasonal changes in the temperature of surface waters can be expected. Such seasonal changes of sea surface temperatures have been routinely monitored using
A VHRR and other satellite platforms (Njoku and Brown 1993). Large scale remotely
sensed mapping of sea surface temperatures has led to new insights into the role
which oceans play in regulating weather and climate (i.e., El Nino). Such measurements also provide a basis for explaining biological activity in ocean and large
freshwater systems. Bolgrien et al (1995) used A VHRR to monitor seasonal temperature in Lake Baikai (Fig. 13.6).
Miller and Millis (1989) used Heat Capacity Mapping Mission (HCMM) and
Landsat TM to estimate surface water temperatures for the Great Salt Lake in Utah.
They used statistical correlations to determine the relationship between surface
temperature and evaporation. They concluded that satellite-derived surface water
temperature along with some ancillary data could be use to estimate evaporation rates.
Miller and Rango (1984) used emitted thermal energy measured by HCMM to map
algal concentration in the Great Salt Lake. They found a positive correlation during
the day and a negative correlation at night between emitted energy and algal concentration. Landsat TM data was used to estimate surface temperatures of an oxbow lake
along the Mississippi River (Ritchie et al. 1990).
Thermal remote sensing is a useful tool for monitoring freshwater systems to detect
thermal changes that can affect biological productivity. These techniques allow the
development of management plans to reduce the effect of man-made thermal releases.
13.4.4 Oils
Oil spills are a common occurrence in the aquatic environment that require significant
time and funds to clean up. Public concerns about these spills require that they be
monitored and cleaned up as quickly and efficiently as possible. Remote sensing can
play an important role in developing strategies for monitoring and cleaning up oil
spills. A wide range of sensors has been used to remotely sense oils. Sensors on
aircraft are commonly used to monitor oil spills to get the spatial and temporal
resolution needed to monitor oil spill patterns in a timely manner. While large oil
spills have been monitored with satellite data (Fingas et al. 1996), frequency of
overpasses and the limited spatial and spectral resolution of sensors on current
satellites limit the use of data from satellite sources. Fingas et al. (1996) published a
series of papers comparing different sensors and remote sensing techniques for oils.
Therefore, only an overview will be given here of commonly used sensors.
Optical sensors using cameras, scanners, and video on aircraft are the most common
techniques used in monitoring oil spills. Oils increase the reflectance of surface waters
in the visible and near infrared spectrum. The increase in reflectance is general across
the spectrum with no single spectral feature to distinguish oil from the background
(Taylor 1992). The use of visible spectrums is related to human pattern recognition
rather than to automated detection by spectral algorithms. Visible techniques are used
most often to document patterns because of lack of algorithms to quantify oil levels
J.C. Ritchie and ER. Schiebe
results in turbid impoundments being cooler than its clear water neighbor (Schiebe
et al. 1976).
Seasonal changes in the temperature of surface waters can be expected. Such seasonal changes of sea surface temperatures have been routinely monitored using
A VHRR and other satellite platforms (Njoku and Brown 1993). Large scale remotely
sensed mapping of sea surface temperatures has led to new insights into the role
which oceans play in regulating weather and climate (i.e., El Nino). Such measurements also provide a basis for explaining biological activity in ocean and large
freshwater systems. Bolgrien et al (1995) used A VHRR to monitor seasonal temperature in Lake Baikai (Fig. 13.6).
Miller and Millis (1989) used Heat Capacity Mapping Mission (HCMM) and
Landsat TM to estimate surface water temperatures for the Great Salt Lake in Utah.
They used statistical correlations to determine the relationship between surface
temperature and evaporation. They concluded that satellite-derived surface water
temperature along with some ancillary data could be use to estimate evaporation rates.
Miller and Rango (1984) used emitted thermal energy measured by HCMM to map
algal concentration in the Great Salt Lake. They found a positive correlation during
the day and a negative correlation at night between emitted energy and algal concentration. Landsat TM data was used to estimate surface temperatures of an oxbow lake
along the Mississippi River (Ritchie et al. 1990).
Thermal remote sensing is a useful tool for monitoring freshwater systems to detect
thermal changes that can affect biological productivity. These techniques allow the
development of management plans to reduce the effect of man-made thermal releases.
13.4.4 Oils
Oil spills are a common occurrence in the aquatic environment that require significant
time and funds to clean up. Public concerns about these spills require that they be
monitored and cleaned up as quickly and efficiently as possible. Remote sensing can
play an important role in developing strategies for monitoring and cleaning up oil
spills. A wide range of sensors has been used to remotely sense oils. Sensors on
aircraft are commonly used to monitor oil spills to get the spatial and temporal
resolution needed to monitor oil spill patterns in a timely manner. While large oil
spills have been monitored with satellite data (Fingas et al. 1996), frequency of
overpasses and the limited spatial and spectral resolution of sensors on current
satellites limit the use of data from satellite sources. Fingas et al. (1996) published a
series of papers comparing different sensors and remote sensing techniques for oils.
Therefore, only an overview will be given here of commonly used sensors.
Optical sensors using cameras, scanners, and video on aircraft are the most common
techniques used in monitoring oil spills. Oils increase the reflectance of surface waters
in the visible and near infrared spectrum. The increase in reflectance is general across
the spectrum with no single spectral feature to distinguish oil from the background
(Taylor 1992). The use of visible spectrums is related to human pattern recognition
rather than to automated detection by spectral algorithms. Visible techniques are used
most often to document patterns because of lack of algorithms to quantify oil levels