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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>
    <pubDate>Tue, 21 May 2013 18:48:09 GMT</pubDate>
    <dc:date>2013-05-21T18:48:09Z</dc:date>
    <item>
      <title>Use of remotely sensed and ancillary data for estimating forest gross primary productivity in Italy</title>
      <link>http://hdl.handle.net/2067/2080</link>
      <description>Title: Use of remotely sensed and ancillary data for estimating forest gross primary productivity in Italy
Authors: Maselli, Fabio; Barbati, Anna; Chiesi, Marta; Chirici, Gherardo; Corona, Piermaria
Abstract: The current paper describes the development and testing of a procedure which can use widely available remotely sensed and ancillary data to assess large-scale patterns of forest productivity in Italy. To reach this objective a straightforward model (C-Fix) was applied which is based on the relationship between photosynthetically active radiation absorbed by plant canopies and relevant gross primary productivity (GPP). The original C-Fix methodology was improved by using more abundant ancillary information and more efficient techniques for NDVI data processing. In particular, two extraction methods were applied to NDVI data, derived from two sensors (NOAA-AVHRR and SPOT-VGT) to feed C-Fix. The accuracy of the model outputs was assessed through comparison with annual and monthly values of forest GPP derived from eight eddy covariance flux towers. The results obtained indicated the superiority of SPOT-VGT over NOAA-AVHRR data and a higher efficiency of the more advanced NDVI extraction method. Globally, the procedure was proved to be of easy and objective implementation and allowed the evaluation of mean productivity levels of existing forests on the national scale.
Description: L'articolo è disponibile sul sito dell'editore www.sciencedirect.com</description>
      <pubDate>Sat, 31 Dec 2005 23:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://hdl.handle.net/2067/2080</guid>
      <dc:date>2005-12-31T23:00:00Z</dc:date>
    </item>
    <item>
      <title>Evaluating the effects of environmental changes on the gross primary production of italian forests</title>
      <link>http://hdl.handle.net/2067/2133</link>
      <description>Title: Evaluating the effects of environmental changes on the gross primary production of italian forests
Authors: Maselli, Fabio; Moriondo, Marco; Chiesi, Marta; Chirici, Gherardo; Puletti, Nicola; Barbati, Anna; Corona, Piermaria
Abstract: A ten-year data-set descriptive of Italian forest gross primary production (GPP)&#xD;
has been recently constructed by the application of Modified C-Fix, a parametric model&#xD;
driven by remote sensing and ancillary data. That data-set is currently being used to develop&#xD;
multivariate regression models which link the inter-year GPP variations of five forest types&#xD;
(white fir, beech, chestnut, deciduous and evergreen oaks) to seasonal values of temperature&#xD;
and precipitation. The five models obtained, which explain from 52% to 88% of the interyear&#xD;
GPP variability, are then applied to predict the effects of expected environmental&#xD;
changes (+2 °C and increased CO2 concentration). The results show a variable response of&#xD;
forest GPP to the simulated climate change, depending on the main ecosystem features. In&#xD;
contrast, the effects of increasing CO2 concentration are always positive and similar to those&#xD;
given by a combination of the two environmental factors. These findings are analyzed with&#xD;
reference to previous studies on the subject, particularly concerning Mediterranean&#xD;
environments. The analysis confirms the plausibility of the scenarios obtained, which can&#xD;
cast light on the important issue of forest carbon pool variations under expected&#xD;
global changes.</description>
      <pubDate>Wed, 31 Dec 2008 23:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://hdl.handle.net/2067/2133</guid>
      <dc:date>2008-12-31T23:00:00Z</dc:date>
    </item>
    <item>
      <title>Assessment of forest net primary production through the elaboration of multisource ground and remote sensing data</title>
      <link>http://hdl.handle.net/2067/2132</link>
      <description>Title: Assessment of forest net primary production through the elaboration of multisource ground and remote sensing data
Authors: Maselli, Fabio; Chiesi, Marta; Barbati, Anna; Corona, Piermaria
Abstract: This paper builds on previous work by our research group which demonstrated the applicability of a parametric model, Modified C-Fix, for the monitoring of Mediterranean forests. Specifically, the model is capable of combining ground and remote sensing data to estimate forest gross primary production (GPP) on various spatial and temporal scales. Modified C-Fix is currently applied to all Italian forest areas using a previously produced data set of meteorological data and NDVI imagery descriptive of a ten-year period (1999–2008). The obtained GPP estimates are further elaborated to derive forest net primary production (NPP) averages for 20 Italian Regions. Such estimates, converted into current annual increment of standing volume (CAI) through the use of specific coefficients, are compared to the data of a recent national forest inventory (INFC). The results obtained indicate that the modelling approach tends to overestimate the ground CAI values for all forest types. The correction of a drawback in the current model implementation leads to reduce this overestimation to about 9% of the INFC increments. The possible origins of this overestimation are investigated by examining the results of previous studies and of older forest inventories. The implications of using different NPP estimation methods are finally discussed in view of assessing the forest carbon budget on a national basis.</description>
      <pubDate>Thu, 31 Dec 2009 23:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://hdl.handle.net/2067/2132</guid>
      <dc:date>2009-12-31T23:00:00Z</dc:date>
    </item>
    <item>
      <title>Stima dei flussi di carbonio degli ecosistemi forestali italiani attraverso dati telerilevati ed ancillari</title>
      <link>http://hdl.handle.net/2067/2294</link>
      <description>Title: Stima dei flussi di carbonio degli ecosistemi forestali italiani attraverso dati telerilevati ed ancillari
Authors: Chirici, Gherardo; Chiesi, Marta; Pasqui, Massimiliano; Corona, Piermaria; Salvati, Riccardo; Barbati, Anna; Lombardi, Fabio; Maselli, Fabio
Abstract: Le foreste rivestono un ruolo fondamentale nell’ambito dei cicli bio-geo-chimici di molti elementi&#xD;
quali, tra gli altri, azoto e carbonio. In particolare possono svolgere l’importante funzione di assorbitori di carbonio, sottraendo CO2 dall’atmosfera. Per questo, ed in vista dei cambiamenti climatici in atto sul nostro pianeta, un obiettivo importante è quello di quantificare l’effettivo accumulo di carbonio stoccato nelle foreste italiane. A questo ambisce il progetto FIRB&#xD;
C_FORSAT finanziato dal MIUR fino al 2013.&#xD;
Tra le metodologie proposte per raggiungere tale scopo (tecniche di eddy covariance, immagini da satellite e modelli bio-geochimici), quelle basate sull’impiego di modelli di simulazione&#xD;
dell’ecosistema unite all’utilizzo di dati telerilevati risultano le più promettenti. Esse infatti uniscono la possibilità offerta dai modelli di stimare tutti i processi dell’ecosistema (GPP, NPP ed&#xD;
NEE) basandosi sulla conoscenza delle specie analizzate e dell’ambiente in cui si trovano con quella di ottenere informazioni su vasta scala spaziale e con alto grado di ripetizione grazie all’uso&#xD;
di dati tele rilevati.&#xD;
A questo scopo il modello bio-geochimico BIOME-BGC opportunamente calibrato e validato per le&#xD;
principali classi forestali italiane appare particolarmente utile. L’utilizzo del modello in forma&#xD;
spazializzata su base nazionale richiede però la disponibilità di una vasta disponibilità di strati&#xD;
informativi. Tra questi i dati meteorologici giornalieri sono particolarmente critici, in quanto non&#xD;
risultano ancora disponibili sul territorio nazionale. Il contributo richiama brevemente la&#xD;
metodologia utilizzata nel progetto e si sofferma in particolare sull’approccio individuato per la&#xD;
generazione della banca dati meteo spazializzata ed il suo utilizzo per simulare il comportamento&#xD;
della macchia mediterranea.; Forests play an important role within numerous bio-geo-chemical cycles among which those of&#xD;
nitrogen and carbon. In particular, forests can behave as carbon sink by removing CO2 from the&#xD;
atmosphere. For this reason, and in view of global climate changes, it is important to quantify the&#xD;
amount of carbon stocked within Italian forest ecosystems. This is the objective of the FIRB project&#xD;
C_FORSAT financed by MIUR up to 2013.&#xD;
Among the available methodologies (eddy-covariance, remote sensing and bio-geo-chemical&#xD;
models), those based on the combined use of ecosystem simulation model and remotely sensed data&#xD;
are the most promising. They in fact enable to estimate all ecosystem processes (GPP, NPP and&#xD;
NEE) based on the knowledge of the species and the environment in which these live. Moreover,&#xD;
they offer the possibility to obtain spatial information with a high temporal frequency.&#xD;
The model BIOME-BGC is particularly useful to this aim after proper calibration and validation for&#xD;
the main Italian forest types. It requires numerous data layers, among which daily meteorological data are the most difficult to obtain for the whole national territory. This contribution summirezes&#xD;
the main methodological steps and focuses on the creation of a daily meteorological database,&#xD;
which is utilized to drive the simulation of Mediterranean macchia.
Description: La pubblicazione è disponibile all'indirizzo http://www.attiasita.it/ASITA2011/indice_atti.html</description>
      <pubDate>Fri, 31 Dec 2010 23:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://hdl.handle.net/2067/2294</guid>
      <dc:date>2010-12-31T23:00:00Z</dc:date>
    </item>
    <item>
      <title>Use of BIOME-BGC to simulate water and carbon fluxes within Mediterranean macchia</title>
      <link>http://hdl.handle.net/2067/2308</link>
      <description>Title: Use of BIOME-BGC to simulate water and carbon fluxes within Mediterranean macchia
Authors: Chiesi, Marta; Chirici, Gherardo; Corona, Piermaria; Duce, Pierpaolo; Salvati, Riccardo; Spano, Donatella; Vaccari, Francesco; Maselli, Fabio
Abstract: The biogeochemical model BIOME-BGC is capable to estimate the main ecophysiological&#xD;
processes characterising all terrestrial ecosystems. To this aim it&#xD;
needs to be properly adapted to reproduce the behaviour of each biome type&#xD;
through a calibration phase. The aim of this paper is to adapt BIOME-BGC to reproduce&#xD;
the evapotranspiration (ET) and photosynthesis (GPP) of Mediterranean&#xD;
macchia spread all over Italy. Ten different sites were selected in the&#xD;
Centre-South of Italy and their gross primary production (GPP) was estimated&#xD;
by applying a parametric model, C-Fix, based on remotely sensed data for ten&#xD;
years (1999-2008). These monthly data were then used to calibrate BIOME-BGC&#xD;
through an iterative process which led to reproduce the spatial and temporal&#xD;
GPP variations found by C-Fix. The calibrated model was then applied to simulate&#xD;
the ET and GPP of two Italian sites characterised by the presence of an&#xD;
eddy flux tower; its performances were evaluated against ground data by common&#xD;
statistics. The results obtained indicate that, after a proper calibration&#xD;
phase, BIOME-BGC can be applied to estimate the evapotranspiration and photosynthesis&#xD;
of Mediterranean macchia with a good accuracy, strictly dependent&#xD;
on the input data utilised.
Description: L'articolo è disponibile sul sito dell'editore www.sisef.it</description>
      <pubDate>Sat, 31 Dec 2011 23:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://hdl.handle.net/2067/2308</guid>
      <dc:date>2011-12-31T23:00:00Z</dc:date>
    </item>
    <item>
      <title>Modeling primary production using a 1 km daily meteorological data set</title>
      <link>http://hdl.handle.net/2067/2349</link>
      <description>Title: Modeling primary production using a 1 km daily meteorological data set
Authors: Maselli, Fabio; Pasqui, Massimiliano; Chirici, Gherardo; Chiesi, Marta; Fibbi, Luca; Salvati, Riccardo; Corona, Piermaria
Abstract: The availability of daily meteorological data extended over wide areas is a common&#xD;
requirement for modeling vegetation processes on regional scales. The present paper investigates&#xD;
the applicability of a pan-European data set of daily minimum and maximum temperatures and&#xD;
precipitation, E-OBS, to drive models of ecosystem processes over Italy. Daily meteorological data&#xD;
from a 10 yr period (2000 to 2009) were first downscaled to 1 km spatial resolution by applying&#xD;
locally calibrated regressions to a digital elevation model. The original and downscaled E-OBS&#xD;
maps were compared with meteorological data collected at 10 ground stations representative of&#xD;
different eco-climatic conditions. Additional tests were performed for the same sites to evaluate&#xD;
the effects of driving a model of vegetation processes, BIOME-BGC, with measured and estimated&#xD;
weather data. The tests were carried out using 10 BIOME-BGC versions characteristic for local&#xD;
vegetation types (Holm oak, other oaks, chestnut, beech, plain/hilly conifers, mountain conifers,&#xD;
Mediterranean macchia, olive trees, and C3 and C4 grasses). The experimental results indicate&#xD;
that the applied downscaling performs best for maximum temperatures, which is the most decisive&#xD;
factor for driving BIOME-BGC simulation of vegetation production. The downscaled data set is&#xD;
particularly suitable for the modeling of forest ecosystem processes, which could be further&#xD;
improved by the use of information obtained from remote sensing imagery.
Description: L'articolo è disponibile sul sito dell'editore www.int-res.com. Periodo di embargo: 5 anni.</description>
      <pubDate>Sat, 31 Dec 2011 23:00:00 GMT</pubDate>
      <guid isPermaLink="false">http://hdl.handle.net/2067/2349</guid>
      <dc:date>2011-12-31T23:00:00Z</dc:date>
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