Remote Sensing - Process

The State of Michigan has more than 11,000 inland lakes; approximately 3,500 of these lakes are greater than 25 acres in size. Nearly all of these lakes greater than 25 acres have developed communities with permanent residences or vacation homes. The general public has access to launches or beaches at about 1,300 lakes in Michigan. The U. S. Geological Survey (USGS) and the Michigan Department of Environmental Quality (MDEQ)have been cooperatively monitoring the quality of inland lakes in Michigan through the Lake Water Quality Assessment (LWQA) monitoring program funded by the Clean Michigan Initiative. Knowledge of the biological productivity of unsampled inland lakes is needed to assist resource managers in their efforts to help protect and manage the quality in all of Michigan’s inland lakes. The USGS and the MDEQ monitor many inland lakes, but it is not economically feasible to monitor the quality of all 11,000 inland lakes in Michigan by use of conventional sampling techniques. Satellite imagery is a means to predict water quality for most of Michigan’s inland lakes by relating reference water-clarity samples to satellite imagery.

Secchi-disk transparency measurements were mainly used to compute trophic status. A secchi disk is a common tool for measuring the overall clarity of water. The Secchi disk is an 8-in. diameter circular disk painted black and white in alternating quadrants. The disk is lowered into the water, and the depth at which the disk is no longer visible is called the secchi depth.

Satellite data has been used from Landsat 7 ETM + and Landsat 5 TM satellites. Satellite imagery should have less then 10% cloud cover in order to see most inland lakes.

Landsat 5 Portion of Path 22 Row 31, August, 2003	Landsat 5 Portion of Path 20 Row 30, August, 2002

A geometric correction helped ensure that the image cells in the satellite imagery would correspond to the data-collection points as closely as possible. Radiometric corrections are needed because the brightness of each pixel in a satellite image is affected by the sun angle, atmospheric effects, and other factors.

An Area of Interest was drawn around each secchi disk measurement, and the average pixel values within the AOI for each band within the satellite imagery was recorded.

A regression model was developed for each satellite scene to relate the field data to the spectral data collected in each AOI. The following regression equation was found to relate Secchi disk samples to satellite imagery:
ln(SDT) = a(band1) + b(band2) + c(band3) + d

Predicted and actual secchi-disk transparency for Landsat 7 ETM+ path 21, row 30 August 2002

The regression equation must be applied to all lakes over 25 acres in the satellite scene, to predict the water-clarity characteristics at unmeasured locations.