Using Imagery Collected by an Unmanned Aerial System to Monitor Cyanobacteria in New Hampshire, USA, Lakes

نویسندگان

چکیده

With the increasing occurrence of cyanobacteria blooms, it is crucial to improve our ability monitor impacted lakes accurately, efficiently, and safely. Cyanobacteria are naturally occurring in many waters globally. Some species can release neurotoxins which cause skin irritations, gastrointestinal illness, pet/livestock fatalities, possibly additional complications after long-term exposure. Using a DJI M300 RTK Unmanned Aerial Vehicle equipped with MicaSense 10-band dual camera system, six New Hampshire were monitored from May September 2022. image spectral data coupled situ water quality data, random forest classification algorithm was used predict categories. The analysis yielded very high overall accuracies for cell (93%), chlorophyll-a (87%), phycocyanin concentrations (92%). 475 nm wavelength, normalized green-blue difference index—version 4 (NGBDI_4), green-red (NGRDI_4) indices most important features these classifications. Logarithmic regressions illuminated relationships between single bands/indices but did not perform as well approach. Ultimately, UAS multispectral collected this study successfully classified cell, chlorophyll-a, studied NH lakes.

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ژورنال

عنوان ژورنال: Remote Sensing

سال: 2023

ISSN: ['2315-4632', '2315-4675']

DOI: https://doi.org/10.3390/rs15112839