Bradley, Andrew V.Rosa, Isabel Maria DuartePontius Junior, Robert G.Ahmed, Sadia E.Araújo, Miguel BastosBrown, Daniel G.Brandão Júnior, AmintasCâmara, GilbertoCarneiro, Tiago Garcia de SennaHartley, Andrew J.Smith, Matthew J.Ewers, Robert M.2018-01-302018-01-302016BRADLEY, A. V. et al. SimiVal, a multi-criteria map comparison tool for land-change model projections. Environmental Modelling & Software, v. 82, p. 229-240, 2016. Disponível em: <https://www.sciencedirect.com/science/article/pii/S1364815216301116>. Acesso em: 16 jan. 2018. 1364-8152http://www.repositorio.ufop.br/handle/123456789/9381The multiple uses of land-cover models have led to validation with choice metrics or an ad hoc choice of the validation metrics available. To address this, we have identified the major dimensions of land-cover maps that ought to be evaluated and devised a Similarity Validation (SimiVal) tool. SimiVal uses a linear regression to test a modelled projection against benchmark cases of, perfect, observed and systematicbias, calculated by rescaling the metrics from a random case relative to the observed, perfect case. The most informative regression coefficients, p-value and slope, are plot on a ternary graph of ‘similarity space’ whose extremes are the three benchmark cases. SimiVal is tested on projections of two deliberately contrasting land-cover models to show the similarity between intra- and inter-model parameterisations. We find metrics of landscape structure are important in distinguishing between different projections of the same model. Predictive and exploratory models can benefit from the tool.en-USrestritoLand-cover modellingValidationLandscape metricsLand-cover changeArtigo publicado em periodicohttps://www.sciencedirect.com/science/article/pii/S1364815216301116https://doi.org/10.1016/j.envsoft.2016.04.016