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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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