Earth observation for monitoring and mapping of cyanobacteria blooms. Case studies on five Italian lakes

Abstract

<p>Cyanobacterial blooms occur in many parts of the world as a result of entirely natural causes or human activity. Due to their negative effects on water resources, efforts are made to monitor cyanobacteria dynamics. This study discusses the contribution of remote sensing methods for mapping cyanobacterial blooms in lakes in northern Italy. Semi-empirical approaches were used to flag scum and cyanobacteria and spectral inversion of bio-optical models was adopted to retrieve chlorophyll-a (Chl-a) concentrations. Landsat-8 OLI data provided us both the spatial distribution of Chl-a concentrations in a small eutrophic lake and the patchy distribution of scum in Lake Como. ENVISAT MERIS time series collected from 2003 to 2011 enabled the identification of dates when cyanobacterial blooms affected water quality in three small meso-eutrophic lakes in the same region. On average, algal blooms occurred in the three lakes for about 5 days a year, typically in late summer and early autumn. A suite of hyperspectral sensors on air- and space-borne platforms was used to map Chl-a concentrations in the productive waters of the Mantua lakes, finding values in the range of 20 to 100 mgm<sup>-3</sup>. The present findings were obtained by applying state of the art of methods applied to remote sensing data. Further research will focus on improving the accuracy of cyanobacteria mapping and adapting the algorithms to the new-generation of satellite sensors.</p>

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

“…Giardino et al (2012) provided a full description of the model. Relevant for this study is the parametrization of the model, which relies on SIOPs gathered in situ, as described in Giardino et al (2014) and in Bresciani et al (2016). In particular, the model performed the inversion by choosing the specific absorption spectra due to phytoplankton and chl-a concentration which provided the minimum error.…”

“…In particular, the model performed the inversion by choosing the specific absorption spectra due to phytoplankton and chl-a concentration which provided the minimum error. During the optimization, the chl-a concentration was free to vary between 0.01 and 50 mg m -3 , while two specific absorption spectra due to phytoplankton were used, one suitable for clear waters and the other for more productive waters (Bresciani et al, 2016).…”

“…To plan possible measures for managing and protecting natural ecosystems affected by extensive cyanobacteria blooms, it is important to obtain timely and synoptic information (Bresciani et al, 2016). 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.…”

Aquatic biomonitoring: Lessons from the past, challenges for the future

“…Bresciani et al (2017) test their usefulness in the analysis of cyanobacterial blooms in the frame of the BLASCO project (CARIPLO Rif. 2014-1249.…”

Red Algae Bloom Detection in Occhito Lake Combining MERIS and MODIS Data

“…In lacustrine environments much attention has been paid to the monitoring of cyanobacteria blooms [14,15] because of their potential harmfulness.…”