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    <title>Unitus DSpace</title>
    <link>http://http://dspace.unitus.it:80</link>
    <description>The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material.</description>
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        <rdf:li rdf:resource="http://hdl.handle.net/2067/2150" />
        <rdf:li rdf:resource="http://hdl.handle.net/2067/2081" />
        <rdf:li rdf:resource="http://hdl.handle.net/2067/2094" />
        <rdf:li rdf:resource="http://hdl.handle.net/2067/2125" />
        <rdf:li rdf:resource="http://hdl.handle.net/2067/2313" />
        <rdf:li rdf:resource="http://hdl.handle.net/2067/2316" />
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    </items>
    <dc:date>2013-05-23T07:18:18Z</dc:date>
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  <item rdf:about="http://hdl.handle.net/2067/2150">
    <title>Assessing the attributes of scattered trees outside the forest by a multi-phase sampling strategy</title>
    <link>http://hdl.handle.net/2067/2150</link>
    <description>Title: Assessing the attributes of scattered trees outside the forest by a multi-phase sampling strategy
Authors: Baffetta, Federica; Corona, Piermaria; Fattorini, Lorenzo
Abstract: A sampling strategy to be used with multi - phase forest inventories is proposed for assessing scattered trees outside the&#xD;
forest on large territories. The fi rst phase is carried out by means of a systematic search over the area to be inventoried.&#xD;
The area is partitioned into regular polygons of the same size and points are randomly located, one per polygon.&#xD;
Subsequently, in the second phase, the land cover class of the fi rst-phase points is determined by very high - resolution&#xD;
remotely sensed imagery and a sample of points are selected from each land cover stratum. Then, the number of trees&#xD;
outside the forest lying within plots at the sampled points is recorded on the imagery. Finally, in the third phase, a&#xD;
subsample is selected from the second-phase samples of each stratum and the biophysical attributes of trees within plots&#xD;
are measured in the fi eld. Approximately unbiased estimators of abundance and of totals and averages of biophysical&#xD;
attributes are achieved in the second and third phase , respectively, together with the estimators of the corresponding&#xD;
variances. A simulation study is performed in order to assess the accuracy of the strategy under random and aggregated&#xD;
distributions of trees. The sampling errors achieved in the second phase using sampling fractions of ~ 0.3 per cent of&#xD;
trees vary from 6 to 13 per cent , whereas the errors achieved in the third phase using sampling fractions of ~ 0.15 per&#xD;
cent vary from 15 to 31 per cent . The results obtained from three case studies carried out in Italy confi rm the accuracy&#xD;
levels achieved in the simulation.
Description: L'articolo è disponibile sul sito dell'editore http://forestry.oxfordjournals.org/</description>
    <dc:date>2010-12-31T23:00:00Z</dc:date>
  </item>
  <item rdf:about="http://hdl.handle.net/2067/2081">
    <title>Design-based approach to k-nearest neighbours technique for coupling field and remotely sensed data in forest surveys</title>
    <link>http://hdl.handle.net/2067/2081</link>
    <description>Title: Design-based approach to k-nearest neighbours technique for coupling field and remotely sensed data in forest surveys
Authors: Baffetta, Federica; Fattorini, Lorenzo; Franceschi, Sara; Corona, Piermaria
Abstract: The statistical properties of the k-NN estimators are investigated in a design-based framework, avoiding any assumption about the population under study. The issue of coupling remotely sensed digital imagery with data arising from forest inventories conducted using probabilistic sampling schemes is considered. General results are obtained for the k-NN estimator at the pixel level. When averages (or totals) of forest attributes for the whole study area or sub-areas are of interest, the use of the empirical difference estimator is proposed. The estimator is shown to be approximately unbiased with a variance admitting unbiased or conservative estimators. The performance of the empirical difference estimator is evaluated by an extensive simulation study performed on several populations whose dimensions and covariate values are taken from a real case study. Samples are selected from the populations by means of simple random sampling without replacement. Comparisons with the generalized regression estimator and Horvitz–Thompson estimators are also performed. An application to a local forest inventory on a test area of central Italy is considered.
Description: L'articolo è disponibile sul sito dell'editore www.sciencedirect.com</description>
    <dc:date>2008-12-31T23:00:00Z</dc:date>
  </item>
  <item rdf:about="http://hdl.handle.net/2067/2094">
    <title>Design-based diagnostics for k-NN estimators of forest resources</title>
    <link>http://hdl.handle.net/2067/2094</link>
    <description>Title: Design-based diagnostics for k-NN estimators of forest resources
Authors: Baffetta, Federica; Corona, Piermaria; Fattorini, Lorenzo
Abstract: The k-nearest neighbours (k-NN) method constitutes a possible approach to improve the precision of the Horvitz–&#xD;
Thompson estimator of a single interest variable using auxiliary information at the estimation stage. Improvements&#xD;
are likely to occur when the neighbouring structure in the space of auxiliary variables is similar to the neighbouring structure&#xD;
in the space of the survey variables. Populations suitable for k-NN can be identified via the scores of the first principal&#xD;
component computed on the variance–covariance matrix of auxiliary variables. If the first principal component&#xD;
explains a large portion of the whole variability, distances among scores provide good approximations of distances in the&#xD;
space of auxiliary variables in such a way that the effectiveness of k-NN can be assessed by plotting the first principal&#xD;
component scores versus the sampled values of each of the interest variables. Monotone relationships with high values of&#xD;
Spearman’s correlation coefficients should denote effectiveness. Otherwise, when the first principal component explains&#xD;
small fractions of the total variation, an index that directly quantifies the similarity between the neighbouring structure in&#xD;
the space of interest and auxiliary variables is proposed. The validity of the proposed diagnostics is theoretically argued&#xD;
and empirically proven by a simulation study performed on a wide range of artificial and real populations.
Description: L'articolo è disponibile sul sito dell'editore www.nrcresearchpress.com</description>
    <dc:date>2010-12-31T23:00:00Z</dc:date>
  </item>
  <item rdf:about="http://hdl.handle.net/2067/2125">
    <title>Estimation of small woodlot and tree row attributes in large-scale forest inventories</title>
    <link>http://hdl.handle.net/2067/2125</link>
    <description>Title: Estimation of small woodlot and tree row attributes in large-scale forest inventories
Authors: Baffetta, Federica; Fattorini, Lorenzo; Corona, Piermaria
Abstract: Forest surveys performed over a large scale (e.g. national inventories)&#xD;
involve several phases of sampling. The first phase is usually performed by means of&#xD;
a systematic search of the study region, in which the region is partitioned into regular&#xD;
polygons of the same size and points are randomly or systematically selected, one per&#xD;
polygon. In most cases, first-phase points are selected and recognized in orthophotos or&#xD;
very high resolution satellite images available for the whole study area. Disregarding&#xD;
the subsequent phases, the first phase of sampling can be effectively adopted to select&#xD;
small woodlots and tree rows, in the sense that a unit is selected when at least one firstphase&#xD;
point falls within it. On the basis of such a scheme of sampling, approximately&#xD;
unbiased estimators of abundance, coverage and other physical attributes readily measurable&#xD;
from orthophotos (e.g. tree-row length) are proposed, together with estimators&#xD;
of the corresponding variances. A simulation study is performed in order to check the&#xD;
performance of the estimators under several distributions of units over the study area&#xD;
(random, clustered, spatially trended).
Description: L'articolo è disponibile sul sito dell'editore www.springerlink.com</description>
    <dc:date>2010-12-31T23:00:00Z</dc:date>
  </item>
  <item rdf:about="http://hdl.handle.net/2067/2313">
    <title>A matching procedure to improve k-NN estimation of forest attribute maps</title>
    <link>http://hdl.handle.net/2067/2313</link>
    <description>Title: A matching procedure to improve k-NN estimation of forest attribute maps
Authors: Baffetta, Federica; Corona, Piermaria; Fattorini, Lorenzo
Abstract: The integration of forest inventory and mapping has emerged as a major issue for assessing forest attributes&#xD;
and multiple environmental functions. Associations between remotely sensed data and the biophysical&#xD;
attributes of forest vegetation (standing wood volume, biomass increment, etc.) can be&#xD;
exploited to estimate the attribute values for sampled and non-sampled pixels, thus producing maps&#xD;
for the entire region of interest. Among the available procedures, the k-nearest neighbours (k-NN) technique&#xD;
is becoming popular, even for practical applications. However, the k-NN estimates at the pixel level&#xD;
tend to average towards the population mean and to have suppressed variance, since large values are usually&#xD;
underestimated and small values overestimated. This tendency may be detrimental for k-NN applications&#xD;
in forest resource management planning and scenario analysis where the representation of the&#xD;
spatial variability of each attribute of interest across the surveyed territory is fundamental. The present&#xD;
paper proposes a procedure to tackle such an issue by modifying k-NN estimates via a post-processing&#xD;
procedure of distribution matching. The empirical distribution function of the population values is estimated&#xD;
from the sample of ground data by using the 0-inflated beta distribution as the assisting model&#xD;
and the k-NN estimates are subsequently modified in such a way as to match the estimated distribution.&#xD;
The statistical properties of the distribution matching estimators for totals and averages are theoretically&#xD;
derived, while the performance of the distribution matching estimator at the pixel level are empirically&#xD;
evaluated by a simulation study.
Description: L'articolo è disponibile sul sito dell'editore www.Journals.elsevier.com</description>
    <dc:date>2011-12-31T23:00:00Z</dc:date>
  </item>
  <item rdf:about="http://hdl.handle.net/2067/2316">
    <title>Extending large-scale forest inventories to assess urban forests</title>
    <link>http://hdl.handle.net/2067/2316</link>
    <description>Title: Extending large-scale forest inventories to assess urban forests
Authors: Corona, Piermaria; Agrimi, Mariagrazia; Baffetta, Federica; Barbati, Anna; Chiriacò, Maria Vincenza; Fattorini, Lorenzo; Pompei, Enrico; Valentini, Riccardo; Mattioli, Walter
Abstract: Urban areas are continuously expanding&#xD;
today, extending their influence on an increasingly&#xD;
large proportion of woods and trees located&#xD;
in or nearby urban and urbanizing areas, the socalled&#xD;
urban forests. Although these forests have&#xD;
the potential for significantly improving the quality&#xD;
the urban environment and the well-being of&#xD;
the urban population, data to quantify the extent&#xD;
and characteristics of urban forests are still lacking&#xD;
or fragmentary on a large scale. In this regard,&#xD;
an expansion of the domain of multipurpose forest&#xD;
inventories like National Forest Inventories&#xD;
(NFIs) towards urban forests would be required.&#xD;
To this end, it would be convenient to exploit the&#xD;
same sampling scheme applied in NFIs to assess&#xD;
the basic features of urban forests. This paper considers&#xD;
approximately unbiased estimators of abundance&#xD;
and coverage of urban forests, together with&#xD;
estimators of the corresponding variances, which&#xD;
can be achieved from the first phase of most largescale&#xD;
forest inventories. A simulation study is carried&#xD;
out in order to check the performance of the&#xD;
considered estimators under various situations involving&#xD;
the spatial distribution of the urban forests&#xD;
over the study area. An application is worked out&#xD;
on the data from the Italian NFI.
Description: L'articolo è disponibile sul sito dell'editore www.springer.com</description>
    <dc:date>2011-12-31T23:00:00Z</dc:date>
  </item>
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