Step-by-Step:
Mapping Lake Water
Clarity
Step
1: Collect ground
samples
To
extract useful
information from
satellite images
about any land
feature, we need
to gather some
information on
the ground. This
information is
commonly referred
to as ground samples,
reference data,
or field data.
These data or
samples provide
information to
verify what exactly
the satellite
sensors are detecting,
and they should
be collected close
in time to when
the satellite
sensor passes
over.
There
are several ways
to gather ground
samples depending
on what water
resource aspect
is being studied. For
lake water clarity,
we use Secchi
disk readings
of sample lakes. Because
the Minnesota
Pollution Control
Agency and its
Citizen Lake
Monitoring Program
regularly makes
Secchi disk
readings on about
800 lakes in
Minnesota,
collecting ground
samples was
simply a matter
of obtaining
the data from
the MPCA.
Step
2: Acquire satellite
imagery
Currently,
there are several
satellites in orbit
with sensors capturing
images of the earth. Select
one of the satellite
sensors below
to view the spatial
coverage and spectral
resolution of
the images that
they capture. If
you would like
to learn more
about
the science and
technology behind
satellite remote
sensing, visit
the Classroom section.
Satellite
image coverage is
simply the area
on the ground which
the satellite sensor
records. In
the illustration
above, IKONOS has
the smallest image
coverage (6.8 miles)
and MODIS has the
largest image coverage
(1,146 miles).
Image
resolution refers
to the finest of
spatial detail that
can be seen in an
image. High
resolution satellite
sensors, such as
IKONOS and QuickBird,
have spatial resolutions
as high as about
one meter, but they
cover a relatively
small geographic
area. Landsat, the
sensor that has
been used for most
of our lake water
clarity work, has
medium resolution
while covering relatively
large areas. MODIS,
which is a sensor
on the Terra and
Aqua satellites,
covers a much larger
area, but at a coarse
resolution.
Step
3: Process satellite
imagery
Once
the imagery is acquired,
analysists typically
go through a series
of steps to prepare
the imagery for
analysis.
1.
Depending on its
use and quality,
sometimes satellite
imagery needs to
be pre-processed
which means that
cloud, haze and
sun effects must
be digitally removed.
See an example of
imagery with haze
effects to the right.
2.
When mapping water
features, all non-water
areas, such as agricutlural
land, urban land
and forests, are
masked out of images
used to map water
clarity. Click on
the image below
to see what a section
of a Landsat image
looks like after
land has been masked
out to make a map
of water clarity.
Click
on map to mask out
land surrounding
Lake Minnetonka.
Click
again to return to non-mask image.
3.
After the imagery
has been pre-processed,
the relationships
between lake clarity
and their spectral-radiometric
responses (in the
simplest sense -
colors) are determined
for a small, representative
sample of each class. This
is typically accomplished
with high-end image
processing computer
software such as
ERDAS Imagine.
4. The
relationship then
is applied to all
the lakes in the
image, providing
a census of lake
clarity.
We
have found a strong
relationship between
lake water clarity
and the responses
in the blue and
red spectral bands.
Click on the graph
in the right column
to view this relationship.
Step
4: Create a map
Once
the mathematical
relationship between
the satellite data
and the field data
has been developed,
the relationship
is applied to all
pixels in the imagery
to create a map
of water resources.
Once
pixels are classified
into discrete classes
like clarity level
or vegetation type,
they can be put
into a Geographic
Information System
(GIS).
To
view a sample of
water resource
maps derived from
satellite imagery,
visit our Map
Gallery.
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