Geography Reference
In-Depth Information
Table 5.1
(
continued
).
c)
Conventional Measurements
TIR Remote Sensing
•
T
k
can be measured directly,
which is both of interest
biologically and applicable to
management objectives.
•
Repeatable, spatially extensive, and systematic measurements.
•
Can quantify spatial patterns of water temperature in streams, rivers, and
floodplains at scales ranging from less than 1m to over 100 km.
•
Can view the entire thermal landscape of the river, not just point locations.
•
Consistent data source for entire floodplains and can be used to calibrate
stream temperature models.
•
TIR image data and concurrent visible and NIR images (where available) can
be used to assess both the water surface and adjacent riparian areas.
•
Repeat flights can be used to assess habitat degradation.
•
Difficult to collect spatially
extensive data to use to calibrate
stream temperature models for
entire watersheds.
•
T
r
is measured at the surface layer of the water and may not be representative
of T
k
in the water column, which is of interest biologically.
•
Trade-off between pixel-size (i.e. to identify spatial patterns and reduce
mixing with bank materials) and the cost of conducting broad-scale surveys.
bulk, or kinetic, temperature of the water (T
k
)atspecific
locations. For example, the State of Washington (USA)
recordedwater quality conditions at 76 stations within the
Puget Lowlands eco region, which contains 12,721 km of
streams and rivers (Washington Department of Ecology,
1998). Such gages are sparsely distributed, are typically
located only in larger streams and rivers, and give lim-
ited information about the spatial distribution of water
temperature (Cherkauer et al., 2005).
Although hydrologists, ecologists, and resource
managers are ultimately interested in T
k
in the water
column - because this is both biologically important and
also the definition of temperature used for management
purposes - measurements of radiant temperature (T
r
)
made at the water's surface using thermal infrared (TIR)
remote sensing provide an attractive alternative to
in situ
measurement of T
k
,ifT
r
measurements can be deter-
mined with suitable and known quality and detail. A key
advantage of TIR remote sensing of T
r
over conventional
measurements of T
k
is that it is possible to quantify spatial
patterns of water temperature in rivers, streams, and
floodplains, at multiple spatial scales throughout entire
watersheds. However, remote sensing of water tempera-
ture can be time-consuming and costly due to the difficul-
ties inobtaining images and the complexities of processing
raw data to produce calibrated temperature maps. As will
be explored in this chapter, understanding these benefits
and limitations is necessary to determine whether
thermal remote sensing of water temperature is suitable
for water resource management applications (Table 5.1).
The goal of this chapter is to show how TIR mea-
surements can be used for monitoring spatial patterns
of water temperature in streams and rivers for practical
applications in water resources management. We use
the term 'water temperature' to refer specifically to
water temperature of lotic systems ranging in size from
streams to rivers. The chapter is divided into three
parts. First, we examine the state of the science and
application of TIR remote sensing of streams and rivers
Section 5.2. Second, we explore the theoretical basis of
TIR measurements of water temperature, data sources
suitable for observing riverine landscapes, the required
processing steps necessary to obtain accurate estimates of
water temperature from TIR data, and the validation of
such temperature estimates (Sections 5.3 to 5.6). Third,
we show two examples of using TIR data to monitor
water temperature in rivers of varying sizes (Sections
5.7 and 5.8). To illustrate the utility of TIR data for
quantifying thermal heterogeneity over a range of spatial
scales, we show very fine resolution (0.2-1m) images
of fine-scale hydrologic features such as groundwater
springs and cold-water seeps. We also expand the scope
to entire floodplains and river sections (1-150 km) to
show characteristic patterns of lateral and longitudinal
thermal variation in riverine landscapes. For TIR pixel
sizes, we use the following terminology across a range
of sensors and platforms: 'ultra-fine resolution' for pixel
sizes of less than 1m, 'very fine resolution' for pixel sizes
of 1 to 5m, 'fine resolution' for pixel sizes of 5 to 15m,
'medium resolution' for pixel sizes of 15 to 100m, and
'coarse resolution' for pixel sizes of greater than 100m.
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