How Does It Work?
Remote sensing is the science of obtaining information about an object or area through the analysis of measurements made at a distance from the object, i.e., not coming in contact with it.
The oldest form of remote sensing, in use since the 1920s, is aerial photography, where the sensor system is a camera and film. Over the past ~45 years, the field of remote sensing has grown to include various electronic-optical sensors that acquire multispectral digital images, which can be processed and analyzed by computers. Many of these sensors are on satellites that regularly orbit the Earth. There are numerous applications of satellite remote sensing for mapping and monitoring environmental and natural resources at local to global scales.
The quantity most frequently measured by these satellite sensors is the electromagnetic energy reflected by the object. Such data are recorded in imagery for various wavelengths (spectral bands) within the visible, near infrared and thermal infrared regions of the spectrum. The source of the electromagnetic energy for most of these sensors is the sun, and the spectral reflectance properties of many Earth surface features, such as soil, vegetation and water, can be used to uniquely identify and characterize them.
Much research and monitoring of natural resources has been accomplished using multispectral sensors on the Landsat series of satellites (landsat.usgs.gov). Several features of these satellites make them particularly useful for assessment of inland lakes. Their geographic coverage (12,000 square miles per image) allows simultaneous assessment of thousands of lakes in lake-rich areas. Their spatial resolution (30 meters) is suitable for all lakes larger than ~10 acres and can be used to map in-lake variability. In addition, the imagery is available at no cost to users.
Strong relationships exist between the Landsat spectral responses in several visible bands and in-situ observations of water clarity (Secchi depth, SD, which is a general measure of water quality). We have used such relationships to assess the clarity of water in more than 10,000 Minnesota lakes. Seven classifications at ~5-year intervals from 1975 to 2008 have provided an unprecedented assessment of these lakes.
Similar relationships can be developed between reflectance data in various sensor bands and other important measures of water quality, including chlorophyll, a measure of the abundance of algae in waterbodies; colored dissolved organic matter (CDOM), a measure of total dissolved organic carbon that affects many aquatic ecosystem processes; phycocyanin, a measure of cyanobacteria (blue-green algae); and various measures of suspended particulate matter in natural waters. Compared with earlier Landsat satellites, the sensors on newer satellites, such as Landsat 8 and the European Sentinel-2 satellites, have greater numbers of spectral bands that are more narrowly focused and facilitate measurement of these constituents.