Stream ecosystems have great importance for the maintenance of water quality in watersheds, but are subject to disturbances that influence their self-depuration capacity, increasing primary production (PP) and resulting in environmental problems such as eutrophication. The biomass of benthic microalgae in lotic ecosystems is a major indicator of PP, being normally evaluated using chlorophyll a concentrations, through a lengthy process with high financial cost, generating large amounts of chemical residues. On the other hand, remote sensing techniques allow the acquisition of data with great precision and in a non-destructive way, such as the use of multispectral images obtained with infrared cameras (IRC). Thus, the objective of this project is to evaluate whether multispectral images obtained by IRC can be used to quantify benthic chlorophyll in streams. For this, an experiment will be carried out to artificially increase nutrient concentration in a creek, with monitoring of substrates that will be recovered weekly over a month. Images of the substrates will be obtained with a IRC and the concentrations of chlorophyll a will be determined in the laboratory. The images will be used to obtain vegetation indices commonly used to determine the primary production. These indexes will be used in chlorophyll a prediction models, with part of the data used for calibration and another part used to test the model. The results may contribute to improve the monitoring of waterbodies, using cheaper and faster methods.
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