Measuring Water Clarity and Quality in Minnesota Lakes and Rivers: A Census-Based Approach Using Remote-Sensing Techniques

Over the past few decades, satellite-derived information has become an integral part of our daily life. It is difficult to imagine how crude and inaccurate weather forecasts would be without the daily satellite feeds that drive the complex models on which weather forecasts are based, and of course the satellite images themselves have revolutionized how we view the movement (and scale) of weather patterns. Similarly, satellite technology has become such an essential and commonplace component of global telecommunications, television, and Internet systems that few give a second thought to the technology behind these marvels. Google Earth now provides detailed images on our television and computer screens of far-off places using high-resolution satellite images. In addition, GPS systems based on satellites now enable even “directionally challenged” drivers to head their cars to the desired destination and make it possible to locate and track people in the most remote and inaccessible locations. Satellite technology also has had profound impacts on the Earth sciences and on science-based management of natural resources. For example, Landsat imagery has been used for several decades to analyze land-use and land-cover patterns, estimate crop production, and monitor forest health. More recently, the MODIS satellites have been used to estimate terrestrial primary production on a continental scale and to monitor oceanic levels of chlorophyll on a global scale. Satellites also provide essential hydrologic information (e.g., snow pack, rainfall, and evapotranspiration estimates) for water resources management. Despite many efforts reported in the scientific literature during the past three decades, however, procedures using satellite imagery to measure surface water quality have not been adopted on a routine basis. For the past nine years, we have been working with colleagues Measuring Water Clarity and Quality in Minnesota Lakes and Rivers: A Census-Based Approach Using Remote-Sensing Techniques