Bio-Optical Modeling in a Tropical Hypersaline Lagoon Environment

Abstract

In this chapter, we attempted to present an overview of the use of remote sensing to monitor water quality parameters, mainly chlorophyll-a chl-a and turbidity. We summarized the main concepts of bio-optical modeling and presented a case study of the application of the Hyperspectral Imager for the Coastal Ocean HICO for the monitoring of water quality in a tropical hypersaline aquatic environment. Using HICO, we evaluated a set of different semi-empirical bio-optical algorithms for chl-a and turbidity estimation developed for inland and oceanic waters in the "raruama Lagoon, RJ, "razil, which is an extreme environment due to its high salinity values. We also developed an empirical algorithm for both water quality parameters and compared the performances. Results showed that for chl-a estimation all models have a low performance with a normalized root mean square error NRMSE varying from . to . . For turbidity, the bio-optical algorithms showed a better performance with the NRMSE between . and . . Overall, these results highlight the importance of including extreme environments, such as the "raruama Lagoon, on the validation of bio-optical algorithms as well as the need for new orbital hyperspectral sensors which will improve the development of the field.