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Author Acutis, M.; Bellocchi, G.
Title Briefing on CropM-LiveM model intercomparison protocol Type Conference Article
Year 2013 Publication Abbreviated Journal
Volume Issue Pages
Keywords CropM
Abstract
Address
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Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium
Area Expedition Conference JPI FACCE MACSUR CropM and LiveM cross-cutting activity Helsinki, Finland, 2013-05-06 to 2013-05-06
Notes Approved no
Call Number MA @ admin @ Serial (down) 2272
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Author Bellocchi, G.; Rivington, M.; Acutis, M.
Title Protocol for model evaluation Type Report
Year 2014 Publication FACCE MACSUR Reports Abbreviated Journal
Volume 3 Issue Pages D-L2.2/D
Keywords
Abstract This deliverable focuses on the development of methods for model evaluation in order to have unambiguous indications derived from the use of several evaluation metrics. The information about model quality is aggregated into a single indicator using a fuzzy expert system that can be applied to a wide range of model estimates where suitable test data are available. This is a cross-cutting activity between CropM (C1.4) and LiveM (L2.2). No Label
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number MA @ admin @ Serial (down) 2229
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Author Sanna, M.; Acutis, M.; Bellocchi, G.
Title Interrelationship between evaluation metrics to assess agro-ecological models Type Report
Year 2014 Publication FACCE MACSUR Reports Abbreviated Journal
Volume 3 Issue Pages Sp3-5
Keywords
Abstract 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. No Label
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number MA @ admin @ Serial (down) 2222
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