Chapter Citizen science and machine learning forecasting Ostreopsis cf ovata blooms

The toxic benthic dinoflagellate Ostreopsis cf. ovata causes harmful algal blooms in Apulia region of Southern Italy. In this study the volunteers of a citizens’ observatory engaged with public research centres to apply a machine learning approach and develop a predictive modelling tool able to fore...

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প্রধান লেখক: Cataldo, Pasquale, Cifarelli, Salvatore, Garofoli, Giuseppe, Lamberti, Grazia, Degryse, Bernard, DE VIRGILIO, MADDALENA, Borrello, Patrizia, Spada, Emanuela, Ottaviani, Ennio
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ভাষা:ইংরেজি
প্রকাশিত: Firenze University Press 2025
বিষয়গুলি:
অনলাইন ব্যবহার করুন:ONIX_20250801T173835_9791221505566_238
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author Cataldo, Pasquale
Cifarelli, Salvatore
Garofoli, Giuseppe
Lamberti, Grazia
Degryse, Bernard
DE VIRGILIO, MADDALENA
Borrello, Patrizia
Spada, Emanuela
Ottaviani, Ennio
author_browse Borrello, Patrizia
Cataldo, Pasquale
Cifarelli, Salvatore
DE VIRGILIO, MADDALENA
Degryse, Bernard
Garofoli, Giuseppe
Lamberti, Grazia
Ottaviani, Ennio
Spada, Emanuela
author_facet Cataldo, Pasquale
Cifarelli, Salvatore
Garofoli, Giuseppe
Lamberti, Grazia
Degryse, Bernard
DE VIRGILIO, MADDALENA
Borrello, Patrizia
Spada, Emanuela
Ottaviani, Ennio
author_sort Cataldo, Pasquale
collection Directory of Open Access Books
description The toxic benthic dinoflagellate Ostreopsis cf. ovata causes harmful algal blooms in Apulia region of Southern Italy. In this study the volunteers of a citizens’ observatory engaged with public research centres to apply a machine learning approach and develop a predictive modelling tool able to forecast O. ovata blooms. We applied the Quantile Regression Forest to draw up two models named Model4Cities and Citizens’Model. Model4Cities was trained with data of cell abundance detected by the Regional Agency of Environmental Protection of Apulia from 2010 to 2022 in the cities of Bisceglie, Molfetta, Giovinazzo and Bari where the microalgae proliferate at high rates. Citizen’sModel was trained with data of cell abundance detected by citizens in two sites within the coastline of Molfetta from 2016 to 2022. Both models show a good capacity to forecast O. ovata concentrations as function of meteorological open data with 81% and 89% of prediction accuracy.
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publisherStr Firenze University Press
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spelling doab-20.500.12854ir-1633932025-08-02T05:06:02Z Chapter Citizen science and machine learning forecasting Ostreopsis cf ovata blooms Cataldo, Pasquale Cifarelli, Salvatore Garofoli, Giuseppe Lamberti, Grazia Degryse, Bernard DE VIRGILIO, MADDALENA Borrello, Patrizia Spada, Emanuela Ottaviani, Ennio Ostreopsis ovata Forecast Citizen science Machine learning Apulia Region The toxic benthic dinoflagellate Ostreopsis cf. ovata causes harmful algal blooms in Apulia region of Southern Italy. In this study the volunteers of a citizens’ observatory engaged with public research centres to apply a machine learning approach and develop a predictive modelling tool able to forecast O. ovata blooms. We applied the Quantile Regression Forest to draw up two models named Model4Cities and Citizens’Model. Model4Cities was trained with data of cell abundance detected by the Regional Agency of Environmental Protection of Apulia from 2010 to 2022 in the cities of Bisceglie, Molfetta, Giovinazzo and Bari where the microalgae proliferate at high rates. Citizen’sModel was trained with data of cell abundance detected by citizens in two sites within the coastline of Molfetta from 2016 to 2022. Both models show a good capacity to forecast O. ovata concentrations as function of meteorological open data with 81% and 89% of prediction accuracy. 2025-08-02T05:06:01Z 2025-08-02T05:06:01Z 2025-08-01T15:55:05Z 2024 chapter ONIX_20250801T173835_9791221505566_238 2975-0288 https://library.oapen.org/handle/20.500.12657/104788 9791221505566 https://directory.doabooks.org/handle/20.500.12854/163393 eng Monitoring of Mediterranean Coastal Areas: Problems and Measurement Techniques open access image/jpeg Attribution-NonCommercial-ShareAlike 4.0 International https://library.oapen.org/bitstream/20.500.12657/104788/1/43721.pdf Firenze University Press 10.36253/979-12-215-0556-6.76 10.36253/979-12-215-0556-6.76 2ec4474d-93b1-4cfa-b313-9c6019b51b1a 9791221505566 11 Florence open access
spellingShingle Ostreopsis ovata
Forecast
Citizen science
Machine learning
Apulia Region
Cataldo, Pasquale
Cifarelli, Salvatore
Garofoli, Giuseppe
Lamberti, Grazia
Degryse, Bernard
DE VIRGILIO, MADDALENA
Borrello, Patrizia
Spada, Emanuela
Ottaviani, Ennio
Chapter Citizen science and machine learning forecasting Ostreopsis cf ovata blooms
title Chapter Citizen science and machine learning forecasting Ostreopsis cf ovata blooms
title_full Chapter Citizen science and machine learning forecasting Ostreopsis cf ovata blooms
title_fullStr Chapter Citizen science and machine learning forecasting Ostreopsis cf ovata blooms
title_full_unstemmed Chapter Citizen science and machine learning forecasting Ostreopsis cf ovata blooms
title_short Chapter Citizen science and machine learning forecasting Ostreopsis cf ovata blooms
title_sort chapter citizen science and machine learning forecasting ostreopsis cf ovata blooms
topic Ostreopsis ovata
Forecast
Citizen science
Machine learning
Apulia Region
topic_facet Ostreopsis ovata
Forecast
Citizen science
Machine learning
Apulia Region
url ONIX_20250801T173835_9791221505566_238
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