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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
Research.fi
Dataset . 2022
License: CC BY
Data sources: Research.fi
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Claim

Data from: Modeling the drivers of eutrophication in Finland with a machine learning approach

Research datakeyboard_double_arrow_right Dataset 01 Jan 2022 Finland Publisher:ZenodoFunded by:AKA | Towards more resilient fo...
Authors: Heikonen, Sara; Yli-Heikkilä, Maria; Heino, Matias;

doi: 10.5281/zenodo.6630432 , 10.5281/zenodo.6630433

Data from: Modeling the drivers of eutrophication in Finland with a machine learning approach

Abstract

The dataset contains data on characteristics of 1547 Finnish EU Water Framework Directive monitored lakes and their catchments from years 2016-2019. Usage notes The zip-file contains catchment and lake characteristics data to support the main analysis code in Github (link) (‘Analyses and visualization’) which produces results, figures and tables presented in the study ‘Modeling the drivers of eutrophication in Finland with a machine learning approach’. Detailed information about the data can be found in the ‘README.docx’ file.

Country
Finland
Related Organizations
Keywords

catchment characteristics, lake characteristics, satellite observed chlorophyll-a, trophic state modelling

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visibility
download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
Average
Average
Average
21
7
Related to Research communities
University Network for Innovation, Technology and Engineering
Italian National Biodiversity Future Center