Participatory surface algal bloom monitoring in Finland in 2011-2013

Ville Kotovirta (Corresponding Author), Timo Toivanen, M. Järvinen, M. Lindholm, K. Kallio

    Research output: Contribution to journalArticleScientificpeer-review

    Abstract

    Background

    Algal mass occurrences are one of the most distinguishing effects of eutrophication in lakes and the coastal waters of the Baltic Sea. Algal bloom occurrence in water bodies varies greatly in terms of both space and time, even during short periods, which makes reliable monitoring of blooms difficult. In this paper, we explore the possibilities to extend the sensor network both spatially and temporally by applying participatory sensing to surface algal bloom monitoring in Finnish lakes and the coastal areas of the Baltic Sea.

    Results

    Two participatory sensing systems were used to collect visual algae observations by citizens: the mobile phone application Levävahti (Algae Watch) and the collaborative web service Järviwiki (Lake wiki), during the summers of 2011–2013. Citizen observations were compared with the visual observations performed by trained expert observers, and mean correlations between citizen and expert observations were calculated using the bootstrapping method: 0.72, 95% confidence interval (CI) [0.53 0.86]; 0.65, 95% CI [0.35 0.86]; and 0.56, 95% CI [0.29 0.76] for the years 2011, 2012 and 2013.

    Conclusions

    Surface algal bloom monitoring is needed to obtain data on algal bloom frequency and intensity, in particular in lakes where the use of satellite remote sensing has limitations and/or phytoplankton monitoring is infrequent or totally lacking. The correlations between expert and citizen observations suggest that citizen observers can provide additional information to support algal bloom monitoring of inland and coastal waters.
    Original languageEnglish
    JournalEnvironmental Systems Research
    Volume3
    Issue number24
    DOIs
    Publication statusPublished - 2014
    MoE publication typeA1 Journal article-refereed

    Fingerprint

    algal bloom
    monitoring
    confidence interval
    lake
    coastal water
    alga
    bootstrapping
    eutrophication
    phytoplankton
    citizen
    sensor
    remote sensing
    summer

    Cite this

    Kotovirta, Ville ; Toivanen, Timo ; Järvinen, M. ; Lindholm, M. ; Kallio, K. / Participatory surface algal bloom monitoring in Finland in 2011-2013. In: Environmental Systems Research. 2014 ; Vol. 3, No. 24.
    @article{c5ee96ca144f48d3828ebb59c0631dd0,
    title = "Participatory surface algal bloom monitoring in Finland in 2011-2013",
    abstract = "BackgroundAlgal mass occurrences are one of the most distinguishing effects of eutrophication in lakes and the coastal waters of the Baltic Sea. Algal bloom occurrence in water bodies varies greatly in terms of both space and time, even during short periods, which makes reliable monitoring of blooms difficult. In this paper, we explore the possibilities to extend the sensor network both spatially and temporally by applying participatory sensing to surface algal bloom monitoring in Finnish lakes and the coastal areas of the Baltic Sea.ResultsTwo participatory sensing systems were used to collect visual algae observations by citizens: the mobile phone application Lev{\"a}vahti (Algae Watch) and the collaborative web service J{\"a}rviwiki (Lake wiki), during the summers of 2011–2013. Citizen observations were compared with the visual observations performed by trained expert observers, and mean correlations between citizen and expert observations were calculated using the bootstrapping method: 0.72, 95{\%} confidence interval (CI) [0.53 0.86]; 0.65, 95{\%} CI [0.35 0.86]; and 0.56, 95{\%} CI [0.29 0.76] for the years 2011, 2012 and 2013.ConclusionsSurface algal bloom monitoring is needed to obtain data on algal bloom frequency and intensity, in particular in lakes where the use of satellite remote sensing has limitations and/or phytoplankton monitoring is infrequent or totally lacking. The correlations between expert and citizen observations suggest that citizen observers can provide additional information to support algal bloom monitoring of inland and coastal waters.",
    author = "Ville Kotovirta and Timo Toivanen and M. J{\"a}rvinen and M. Lindholm and K. Kallio",
    year = "2014",
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    journal = "Environmental Systems Research",
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    Participatory surface algal bloom monitoring in Finland in 2011-2013. / Kotovirta, Ville (Corresponding Author); Toivanen, Timo; Järvinen, M.; Lindholm, M.; Kallio, K.

    In: Environmental Systems Research, Vol. 3, No. 24, 2014.

    Research output: Contribution to journalArticleScientificpeer-review

    TY - JOUR

    T1 - Participatory surface algal bloom monitoring in Finland in 2011-2013

    AU - Kotovirta, Ville

    AU - Toivanen, Timo

    AU - Järvinen, M.

    AU - Lindholm, M.

    AU - Kallio, K.

    PY - 2014

    Y1 - 2014

    N2 - BackgroundAlgal mass occurrences are one of the most distinguishing effects of eutrophication in lakes and the coastal waters of the Baltic Sea. Algal bloom occurrence in water bodies varies greatly in terms of both space and time, even during short periods, which makes reliable monitoring of blooms difficult. In this paper, we explore the possibilities to extend the sensor network both spatially and temporally by applying participatory sensing to surface algal bloom monitoring in Finnish lakes and the coastal areas of the Baltic Sea.ResultsTwo participatory sensing systems were used to collect visual algae observations by citizens: the mobile phone application Levävahti (Algae Watch) and the collaborative web service Järviwiki (Lake wiki), during the summers of 2011–2013. Citizen observations were compared with the visual observations performed by trained expert observers, and mean correlations between citizen and expert observations were calculated using the bootstrapping method: 0.72, 95% confidence interval (CI) [0.53 0.86]; 0.65, 95% CI [0.35 0.86]; and 0.56, 95% CI [0.29 0.76] for the years 2011, 2012 and 2013.ConclusionsSurface algal bloom monitoring is needed to obtain data on algal bloom frequency and intensity, in particular in lakes where the use of satellite remote sensing has limitations and/or phytoplankton monitoring is infrequent or totally lacking. The correlations between expert and citizen observations suggest that citizen observers can provide additional information to support algal bloom monitoring of inland and coastal waters.

    AB - BackgroundAlgal mass occurrences are one of the most distinguishing effects of eutrophication in lakes and the coastal waters of the Baltic Sea. Algal bloom occurrence in water bodies varies greatly in terms of both space and time, even during short periods, which makes reliable monitoring of blooms difficult. In this paper, we explore the possibilities to extend the sensor network both spatially and temporally by applying participatory sensing to surface algal bloom monitoring in Finnish lakes and the coastal areas of the Baltic Sea.ResultsTwo participatory sensing systems were used to collect visual algae observations by citizens: the mobile phone application Levävahti (Algae Watch) and the collaborative web service Järviwiki (Lake wiki), during the summers of 2011–2013. Citizen observations were compared with the visual observations performed by trained expert observers, and mean correlations between citizen and expert observations were calculated using the bootstrapping method: 0.72, 95% confidence interval (CI) [0.53 0.86]; 0.65, 95% CI [0.35 0.86]; and 0.56, 95% CI [0.29 0.76] for the years 2011, 2012 and 2013.ConclusionsSurface algal bloom monitoring is needed to obtain data on algal bloom frequency and intensity, in particular in lakes where the use of satellite remote sensing has limitations and/or phytoplankton monitoring is infrequent or totally lacking. The correlations between expert and citizen observations suggest that citizen observers can provide additional information to support algal bloom monitoring of inland and coastal waters.

    U2 - 10.1186/s40068-014-0024-8

    DO - 10.1186/s40068-014-0024-8

    M3 - Article

    VL - 3

    JO - Environmental Systems Research

    JF - Environmental Systems Research

    SN - 2193-2697

    IS - 24

    ER -