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A distributed system for traceability and sustainability assessment of leather shoe supply chains
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La valutazione dei risultati aziendali attraverso il Bilancio del Bene Comune. AGRIREGIONIEUROPA, p. 45-50,
No full textLa realizzazione della carta delle formazioni naturali e semi-naturali e della carta forestale su basi tipologiche della regione Lazio
Get PDFL'articolo è disponibile sul sito dell'editore http://www.sisef.it/
forest@/contents/?id=efor1204-011Map of the natural and semi-natural environments and forest types map for the Latium region (Italy). The paper presents the main methodological aspects and the most important results achieved in the implementation of the “Map of natural and semi-natural environments” and of the “Forest types map” in Lazio region at a scale of 1:10.000. The project was carried out for the Agenzia dei Parchi and for the Area Foreste of Regione Lazio through a collaboration between e-GEOS , the University of Rome "La Sapienza", the University of Tuscia and Forestlab Centre , a spin- off of the University of Molise . The project is based on the integrated use of high-resolution satellite imagery and ADS40 false-color infrared digital orthophotos and led to the creation of two maps geometrically and thematically consistent with each other. The “Map of natural and semi-natural environments” is integrated with the pre-existing land use map of the Lazio region deepening the thematic
detail up to the 6th Corine level. The “Forest types map” is based on a typological system organized in 17 categories
and 36 forest types
A comparative evaluation of fluidized bed assisted drag finishing and centrifugal disk dry finishing
No full textMapping by spatial predictors exploiting remotely sensed and ground data: a comparative design-based perspective
No full textThis study was designed to compare the performance – in terms of bias and accuracy – of four different parametric,semiparametric and nonparametric methods in spatially predicting a forest response variable using auxiliary information from remote sensing. The comparison was carried out in simulated and real populations where the value of
response variable was known for each pixel of the study region. Sampling was simulated through a tessellation stratified design. Universal kriging and cokriging were considered among parametric methods based on the spatial autocorrelation of the forest response variable. Locallyweighted regression and k-nearest neighbor predictors were
considered among semiparametric and nonparametricmethods based on the information from neighboring sites in the auxiliary variable space. The study was performed from a design-based perspective, taking the populations as fixed and replicating the sampling procedurewith 1000Monte Carlo simulation runs. On the basis of the empirical values of relative bias and relative root mean squared error it was concluded that universal kriging and cokriging were more suitable in the presence of strong spatial autocorrelation of the forest variable, while locally weighted
regression and k-nearest neighbors were more suitable when the auxiliary variables were well correlated with the response variable. Results of the study advise that attention should be paid when mapping forest variables
characterized by highly heterogeneous structures. The guidelines of this study can be adopted even for mapping environmental attributes beside forestry
