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Abstract

Cyanobacterial harmful algal blooms (CyanoHABs) are widely recognized as serious and increasingly frequent water quality, public health, and environmental phenomena worldwide because they can produce toxins that adversely affect wildlife, public health, and ecosystem services. Consequently, water resources, environmental, and healthcare agencies need early information about the development of these blooms to mitigate or minimize their impact. We developed a multi-platform CyanoHABs sensing framework by integrating data from multiple earth observing (EO) satellite sensors, in-situ sampling, low-cost and easily deployable wireless sensor platforms, and citizen scientists’ observations for early detection, quantification, and continuous monitoring of CyanoHABs in inland waterbodies. The methodologies involved novel techniques to cross-calibrate Landsat 8-Operational Land Imager (OLI) and Sentinel 2-Multi-Spectral Instrument (MSI), and Landsat 8-OLI and Sentinel 3-Ocean and Land Color Instrument (OLCI) using common cyanobacteria indices derived from their near-identical band centers. A single cyanobacteria cell density (CCD) model developed for both Landsat 8-OLI and Sentinel 2-MSI was able to capture the spatio-temporal development of a historical (Summer-2016) CyanoHAB event in Utah Lake, which made more than 100 people reportedly sick during thebloom period. We also evaluated the potential of Landsat 8-OLI’s novel virtual-orange band (band center: 613nm; bandwidth: 590-635nm) that can be derived from OLI’s panchromatic band for mapping phycocyanin (PC) concentration in the Western Basin of Lake Erie (WBLE). The PC maps produced using OLI’s virtual-orange band showed similar spatial patterns, and PC concentrations, when compared to Sentinel 3-OLCI’s actual orange band (band center: 620nm; bandwidth: 615-625nm) derived maps for a near co-incident overpass in WBLE. Further, a novel cross-calibrated cyanobacteria index “Enhanced Green Line Height” was developed using a combination of orange, green, and blue bands to derive consistent PC and CCD maps using all three sesnors, Landsat 8-OLI, Sentinel 3-OLCI, and Envisat-Medium Resolution Spectrometer (MERIS) in WBLE and Lake Okeechobee, USA. Finally, we developed and implemented a multi-cloud architecture called “CyanoTRACKER” to integrate citizen scientists reported CyanoHABs locations via mobile app and social media, data from low-cost sensors at reported smaller waterbodies, and maps produced from satellite-based models for comprehensive monitoring of CyanoHABs worldwide.

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