Browsing by Autor "A German"

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    Spatial Algal Bloom Characterization by Landsat 8-Oli and Field Data Analysis
    (2018) Andrea Guachalla Alarcon; A German; Alejandro Aleksinkó; María Fernanda García Ferreyra; Carlos Marcelo Scavuzzo; Anabella Ferral
    Water pollution is an important problem around the world as it is closely related to human and environmental health. Field campaigns are expensive, time consuming and may provide little information. Remote sensing provides synoptic spatio-temporal views and can lead to a better understanding of lake ecology. In this work an extreme algal bloom event which occurred in a reservoir is characterized by LANDSAT8-OLI sensor and in situ sampling. Chlorophyll-a concentration and algae abundance data are measured on samples collected simultaneously with satellite pass and used to build semiempirical models. Two linear functions to calculate chlorophyll-a from satellite data are presented and compared. A linear model from band 2 (blue) and band 5 (NIR) presents the best performance with a determination coefficient equal to 0,89. In situ and satellite chlorophyll-a lead comparable trophic class assessment, hypertrophic. Both Models fail to predict chlorophyll-a concentration near river intrusion (North), where low values of reflectance are recorded.
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    Spectral Monitoring of Algal Blooms in an Eutrophic Lake Using Sentinel-2
    (2019) A German; Anabella Ferral; Scavuzzo Carlos Marcelo; Guachalla Alarcon Andrea; Tropper Ivana; Ibanez Guillermo; Torrusio Sandra; Michal Shimoni
    Eutrophication is a process in which elevated organic matter and nutrients raises the primary production of a water body. As a result, the productivity of phytoplankton and biomass are very high at all trophic levels. During bloom event, the spatial and temporal distribution of this phenomena is difficult to be observed using conventional water sampling methods. This work advance the state of the art by using Sentinel-2 (S2) images to estimate chlorophyll-a (chl-a) concentration with an empirical model. Specifically, the model uses band 8 (NIR) and band 4 (red) to predict chl-a concentration during an algal bloom event in San Roque lake, Córdoba, Argentina. Nevertheless, novel spectral ratio for algae composition patterns has also been created using bands 8a and 9. The results show that S2 has the potential to monitor bloom events in eutrophic lakes.