Remote sensing application to estimate fish kills by Saprolegniasis in a reservoir.
作者： Matias Bonansea , Miguel Mancini , Micaela Ledesma , Susana Ferrero , Claudia Rodriguez
DOI: 10.1016/J.SCITOTENV.2019.02.442
关键词: Saprolegnia parasitica 、 Water surface temperature 、 Fish kill 、 Hydrology 、 Water temperature 、 Environmental science
摘要: Saprolegniasis is one of the most economical and ecologically harmful diseases in different species fish. Low water temperature important factors which increases stress creates favourable conditions for proliferation Saprolegniasis. Therefore, monitoring surface (WST) fundamental a better understanding The objective this study was to develop predictive algorithm estimate probability fish kills caused by Rio Tercero reservoir (Argentina). WST estimated Landsat 7 8 imagery using Single-Channel method. Logistic regression used relate from 2007 2017 with episodes registered during period time. Results showed that created first quartile (25th percentile) values sensors suitable model studied reservoir.
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