Monitoring and protecting the quality of Minnesota lakes and streams is a major concern for many state and local agencies. However, because of expense and time requirements for ground-based monitoring, it is impractical to monitor more than a small fraction of this large resource by conventional field methods. The use of remote sensing is a cost-effective way to gather the information needed for water quality assessments in lake-rich areas.
Researchers from the University the Remote Sensing and Geospatial Analysis Laboratory have been working since 1996, researching and developing satellite-based approaches to monitor water resources. They have been joined by resource managers from several local and state agencies. Together they are committed to developing satellite technology as a cost effective way to acquire information on lakes, streams and wetlands.
The primary efforts have been directed at monitoring lake clarity, an indicator of water quality, with Landsat data. More than 10,500 lakes have been classified at seven different times from 1975 to 2008. The results are available in a MapServer application known as the Lake Browser, lakes.gis.umn.edu.
We have also been researching the potential of other sensor systems including MODIS and MERIS for monitoring large lakes at more frequent intervals and acquiring chlorophyll and suspended solids, as well as clarity. Hyperspectral data have been used to estimate several water parameters of rivers and to evaluate the potential of other spectral bands. Current attention is focused on Landsat 8 and the upcoming Sentinel 2 satellite which have more spectral bands and other improvements compared to the previous Landsat sensors. The methods and results of this research are on our Water Resources website, water.umn.edu.
The data can be downloaded from portal.gis.umn.edu.