Water remote sensing
Water Remote Sensing is the observation of water bodies such as lakes, oceans, and rivers from a distance in order to describe their color, state of ecosystem health, and productivity. Water remote sensing studies the color of water through the observation of the spectrum of water leaving radiance. From the spectrum of color coming from the water, the concentration of optically active components of the upper layer of the water body can be estimated via specific algorithms.
Water quality monitoring by remote sensing and close-range instruments has obtained considerable attention since the founding of EU Water Framework Directive.
Overview
Water remote sensing instruments allow scientists to record the color of a water body, which provides information on the presence and abundance of optically active natural water components. The water color spectrum as seen by a satellite sensor is defined as an apparent optical property of the water. This means that the color of the water is influenced by the angular distribution of the light field and by the nature and quantity of the substances in the medium, in this case, water. Thus, the values of remote sensing reflectance, an AOP, will change with changes in the optical properties and concentrations of the optically active substances in the water. Properties and concentrations of substances in the water are known as the inherent optical properties or IOPs. IOPs are independent from the angular distribution of light but they are dependent on the type and amount of substances that are present in the water. For instance, the diffuse attenuation coefficient of downwelling irradiance, Kd is defined as an AOP, while the absorption coefficient and the scattering coefficient of the water are defined as IOPs.There are two different approaches to determine the concentration of optically active water components by the study of spectra, distributions of light energy over a range of wavelengths or colors. The first approach consist of empirical algorithms based on statistical relationships. The second approach consists of analytical algorithms based on the inversion of calibrated bio-optical models. Accurate calibration of the relationships and/or models used is an important condition for successful inversion on water remote sensing techniques and the determination of concentration of water quality parameters from observed spectral remote sensing data.
Thus, these techniques depend on their ability to record these changes in the spectral signature of light backscattered from water surface and relate these recorded changes to water quality parameters via empirical or analytical approaches. Depending on the water constituents of interest and the sensor used, different parts of the spectrum will be analyzed.