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

被引:0
|
作者
M. Bresciani
I. Cazzaniga
M. Austoni
T. Sforzi
F. Buzzi
G. Morabito
C. Giardino
机构
[1] National Research Council of Italy,Remote Sensing of Environmental Dynamics Laboratory, DISAT
[2] Institute for Electromagnetic Sensing of the Environment (CNR-IREA),undefined
[3] Università degli Studi Milano-Bicocca,undefined
[4] Institute for the Study of Ecosystems,undefined
[5] National Research Council of Italy (CNR-ISE),undefined
[6] ARPA Lombardia,undefined
[7] Dipartimento di Lecco,undefined
来源
Hydrobiologia | 2018年 / 824卷
关键词
Satellite images; Water reflectance; Chlorophyll-a; Cyanobacteria; Remote sensing;
D O I
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中图分类号
学科分类号
摘要
For effective lakes’ management, high-frequent water quality data on a synoptic scale are essential. The aim of this study is to test the suitability of the latest generation of satellite sensors to provide information on lake water quality parameters for the five largest Italian subalpine lakes. In situ data of phytoplankton composition, chlorophyll-a (chl-a) concentration and water reflectance were used in synergy with satellite observations to map some algal blooms in 2016. Chl-a concentration maps were derived from satellite data by applying a bio-optical model to satellite data, previously corrected for atmospheric effects. Results were compared with in situ data, showing good agreement. The shape and magnitude of water reflectance from different satellite data were consistent. Output chl-a concentration maps, show the distribution within each lake during blooming events, suggesting a synoptic view is required for these events monitoring. Maps show the dynamic of bloom events with concentration increasing from 2 up to 7 mg m−3 and dropping again to initial value in less than 20 days. Latest generation sensors were shown to be valuable tools for lakes monitoring, thanks to frequent, free of charge data availability over long time periods.
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页码:197 / 214
页数:17
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