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1000 Titel
  • Interrelationship between evaluation metrics to assess agro-ecological models
1000 Autor/in
  1. Sanna, Mattia |
  2. Acutis, Marco |
  3. Bellocchi, Gianni |
1000 Erscheinungsjahr 2014
1000 Publikationstyp
  1. Kongressschrift |
  2. Artikel |
1000 Online veröffentlicht
  • 2014-06-27
1000 Erschienen in
1000 Quellenangabe
  • 3(Supplement):CP3-18
1000 Übergeordneter Kongress
1000 Copyrightjahr
  • 2015
1000 Verlagsversion
  • https://ojs.macsur.eu/index.php/Reports/article/view/CP3-18 |
1000 Interne Referenz
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • When evaluating the performances of simulation models, the perception of the quality of the outputs may depend on the statistics used to compare simulated and observed data. In order to have a comprehensive understanding of model performance, the use of a variety of metrics is generally advocated. However, since they may be correlated, the use of two or more metrics may convey the same information, leading to redundancy. This study intends to investigate the interrelationship between evaluation metrics, with the aim of identifying the most useful set of indicators, for assessing simulation performance. Our focus is on agro-ecological modelling. Twenty-three performance indicators were selected to compare simulated and observed data of four agronomic and meteorological variables: above-ground biomass, leaf area index, hourly air relative humidity and daily solar radiation . Indicators were calculated on large data sets, collected to effectively apply correlation analysis techniques. For each variable, the interrelationship between each pair of indicators was evaluated, by computing the Spearman’s rank correlation coefficient. A definition of “stable correlation” was proposed, based on the test of heterogeneity, allowing to assess whether two or more correlation coefficients are equal. An optimal subset of indicators was identified, striking a balance between number of indicators, amount of provided information and information redundancy. They are: Index of Agreement, Squared Bias, Root Mean Squared Relative Error, Pattern Index, Persistence Model Efficiency and Spearman’s Correlation Coefficient. The present study was carried out in the context of CropM-LiveM cross-cutting activities of MACSUR knowledge hub.
1000 Fächerklassifikation (DDC)
1000 DOI 10.4126/FRL01-006414110 |
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0001-7262-0856|https://orcid.org/0000-0002-1576-8261|https://orcid.org/0000-0003-2712-7979
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1000 Erstellt am 2019-04-17T12:05:10.335+0200
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  1. oai:frl.publisso.de:frl:6414110 |
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