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Pubblicazioni Scientifiche
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From model selection to maps: A completely design-based data-driven inference for mapping forest resources
Di Biase
,
Rosa Maria
,
Fattorini
,
Lorenzo
,
Franceschi
,
Sara
,
Grotti
,
Mirko
,
Puletti
,
Nicola
,
Corona
,
P.
density estimation
harmonization
model selection
predictions
pseudopopulation bootstrap
regression estimator
residuals
smoothing parameter
spatial interpolation
Mostra abstract
A completely data-driven, design-based sampling strategy is proposed for mapping a forest attribute within the spatial units tessellating a survey region. Based on sample data, a model is selected, and model parameters are estimated using least-squares criteria for predicting the attribute of interest within units as a linear function of a set of auxiliary variables. The spatial interpolation of residuals arising from model predictions is performed by inverse distance weighting. The leave-one-out cross validation procedure is adopted for selecting the smoothing parameter used for interpolation. The densities of the attributes of interest within units are estimated by summing predictions and interpolated residuals. Finally, density estimates are rescaled to match the total estimate over the survey region obtained by the traditional regression estimator with the total estimate obtained from the map as the sum of the density estimates within units. A bootstrap procedure accounts for the uncertainty. The consistency of the strategy is proven by incorporating previous results. A simulation study is performed and an application for mapping wood volume densities in the forest estate of Rincine (Central Italy) is described. © 2022 John Wiley & Sons Ltd.
Harmonized forest categories in central Italy
Chiavetta
,
U.
,
Camarretta
,
Nicolò
,
Garfì
,
Vittorio
,
Ottaviano
,
Marco
,
Chirici
,
Gherardo
,
Vizzarri
,
Matteo
,
Marchetti
,
Marco
Mostra abstract
To support sustainable forest management, planning policies and environmental actions, it is essential to have available common and standardized geospatial information on forest structure, composition and distribution. In this paper we present a harmonized forest categories (HFCs) map of four administrative Regions located in central Italy (i.e. Marche, Abruzzo, Lazio and Molise) at a scale of 1:400,000. The study area extends over 42,246 km<sup>2</sup>, 14,878 km<sup>2</sup> of which are covered by forests. Four regional forest maps were harmonized in order to produce common standardized information on composition, structure and the distribution of forests in central Italy. A forest category is a forest vegetation unit defined by the main tree species composition. In this study we adopted a nomenclature scheme composed of 16 forest and shrubland categories. This work represents the first HFCs map in Italy over a large area. The legend is also harmonized with the European Environment Agency forest types nomenclature. © 2016 Nicolò Camarretta.