Quantification of shallow water quality parameters by means of remote sensing

Abstract

Quantification of quality parameters of inland and near shore waters by means of remote sensing has encountered varying degrees of success in spite of the high variability of the parameters under consideration and limitations of remote sensors themselves. This paper comprehensively evaluates the quantification of four types of water quality parameters: inorganic sediment particles, phytoplankton pigments, coloured dissolved organic material and Secchi disk depth. It concentrates on quantification requirements, as well as the options in selecting the most appropriate sensor data for the purpose. Relevant factors, such as quantification implementation and validation of the quantified results are also extensively discussed. This review reveals that the relationship between in situ samples and their corresponding remotely sensed data can be linear or nonlinear, but are nearly always site-specific. The quantification has been attempted from terrestrial satellite data largely for suspended sediments and chlorophyll concentrations. The quantification has been implemented through integration of remotely sensed imagery data, in situ water samples and ancillary data in a geographic information system (GIS). The introduction of GIS makes the quantification feasible for more variables at an increasingly higher accuracy. Affected by the number and quality of in situ samples, accuracy of quantification has been reported in different ways and varies widely.

Mapping phytoplankton blooms in deep subalpine lakes from Sentinel-2A and Landsat-8

“…The last can in fact support traditional in situ samplings (Liu et al, 2003;Nausch et al, 2008) which might be insufficient for meeting the requirements also in terms of costs. Further, a key factor in deciding the value of the data to be sought is the choice of sampling sites.…”

Remote sensing supports the definition of the water quality status of Lake Omodeo (Italy)

“…Limnological methods are fundamental for the understanding of aquatic ecosystems dynamics. Nevertheless, they are characterised by onerous and time consuming fieldwork activities in predefined spatial and temporal locations, thus not allowing, an exhaustive description of the aquatic ecosystems complexity [Allee and Johnson, 1999;Liu et al, 2003;Nausch et al, 2008]. Moreover, the data quality may depend both on procedures for collecting water samples and on laboratory measuring protocols.…”

Monitoring Lake Ecosystems Using Integrated Remote Sensing / Gis Techniques: An Assessment in the Region of West Macedonia, Greece

“…Because sediment characteristics, like texture and color, influence the water reflection, developed empirical relationships are not easily transferable to other regions where erosion entrains different sediment types. Therefore, until a universal equation does not exist, most models of suspended sediment are site-specific (Liu et al, 2003). Thermal infrared (TIR) satellite images can be also used to study transport processes in lakes, such as wind-driven upwelling and surface circulation, providing a measure of spatial variability and horizontal distribution of water temperature that conventional field-based measurements cannot provide, (Steissberg et al, 2006, Zhen-Gang Ji et al, 2006.…”