Geography Reference
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the longer and more expensive the image acquisition
will become.
Another important consideration for airborne data
acquisition is that the images do not provide a truly
synoptic assessment, or 'snapshot', of water temperature
at a specific time if the images are collected sequen-
tially along the river course. Thus, diurnal changes in
water temperature should be considered in planning air-
borne data collection. See further discussion of this topic
in Section 5.5.2.1 on helicopter versus fixed-wing air-
craft, and Section 5.6 on the validation of temperature
measurements.
The selection of an airborne platform/TIR-imaging-
sensor depends on project-specific details such as the river
characteristics (size, sinuosity, etc.), temporal constraints,
desired spatial and thermal resolutions and accuracies,
and map accuracy specifications. TIR imaging systems
have evolved continuallywith advances in technology, and
there are a number of TIR imaging sensors available on
the market suitable for use on airborne-platforms. These
TIR imaging sensors have unique technical characteristics
such as physical size, temperature resolution, integration
times, detector types and sizes, and optics. However, there
are also common features that make these TIR imaging
sensors suitable for TIR remote sensing of water.
TIRimagingsystemsmustbeabletostorerawDN
that can be converted either internally or during post-
processing to a measure of radiant energy. Manufacturers
differ in how this is accomplished, but in most cases
the detectors are calibrated in the laboratory environ-
ment against a black-body source and this information
is stored (either internally or externally) as a conver-
sion curve that is unique to the sensor. Because airborne
remote sensing typically involves collecting sequential
frames, another important sensor system characteristic
is its ability to retain internal radiometric consistency
throughout the data acquisition. Although conditions
such as ambient temperature change, the TIR imaging
system must be able to control or minimise internal
drift such that frame-to-frame measurements are con-
sistent. TIR imaging sensor manufacturers accomplish
this in a number of ways such as using internal tem-
perature references or cooling mechanisms which retains
stability in the detector array. Finally, the TIR imag-
ing system must account for radiometric distortion due
to variability in individual detector response and lens
optics (in the case of frame based TIR imaging sen-
sors). This is referred to as uniformity correction and
can be accomplished either internally or during the post
processing.
A wide variety of TIR imaging sensors have been used
for airborne applications. For example, in one study
(Handcock et al., 2006) the MODIS/ASTER (MASTER)
sensor (Hook et al., 2001) was flown on a King Air
B200 fixed-wing aircraft at altitudes of
∼
2000 and
∼
6000
m, which gives approximate pixel sizes of 5 and 15m,
respectively. The MASTER sensor has ten TIR bands
(10.15-11
.
45
μ
m) with an NE
Δ
T that ranges from 0.46
43
◦
from nadir. In another
example, on Prince Edward Island (Canada), a FLIR
Systems SC-3000 TIR imaging sensor mounted on a
Cessna 172 fixed-wing aircraft was used to acquire images
of the Trout River. These data were successfully used
to detect and quantify ground water discharge to the
estuary (Danielescu et al., 2009). The SC-3000 sensor has
a single TIR band of 8-9μm with a NE
Δ
Tof0
.
02
◦
C.
The sensor has a fixed horizontal FOV of
71
◦
C, and can scan
to 0
.
±
10
◦
from
nadir and a detector array of 320
×
240 pixels. In this
study, the aircraft was flown at an altitude of 1000m to
give a ground sample distance (GSD, i.e. the pixel size
of the imaging sensor expressed in ground units) of 1m.
Although the term GSD is often used interchangeably
with pixel size, it is sometimes expressed explicitly when
the ground distance represented by a pixel changes across
the image, which is common for aerial imaging and
oblique view geometries. In Northern Utah, a helicopter-
mounted Space Instruments Firemapper 2.0 was used to
collect TIR images with a 3m GSD to identify areas of
thermal refugia in the 9.6 km
2
Cutler Reservoir (Dahle
2009). The Firemapper 2.0 system has a single TIR band
of 8-12
±
07
◦
C. The imaging sensor
μ
mwith an NE
Δ
Tof0
.
1
◦
from nadir and a detector
has horizontal FOV of
±
22
.
array of 320
240 pixels.
Early work with airborne TIR imaging in riverine
environments focused primarily on detecting cold water
sources and longitudinal temperature patterns (Torgersen
et al., 1999, 2001) with data geo-referenced to specific
locations along the longitudinal extent of the river (i.e.
tributary junctions, springs geo-referenced according to
their distance upstream). Over the past decade, creating
continuous image mosaics with specified mapping accu-
racy has increasingly become a requirement so that the
image data can be accurately combined with other spa-
tially explicit data layers and accurately geo-referenced
field data. Although some of the early TIR images were
from ground-based imaging sensors mounted on an
aerial platform, more recent TIR sensor systems such
as the ITRES TASI 600 (USA) push-broom hyperspectral
thermal imaging sensor system are specifically designed
for airborne operations. Such imaging sensors provide
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