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Tonolli S.,Provincia Autonoma di Trento (Italy) | Dalponte M.,Research and Innovation Center | Vescovo L.,Research and Innovation Center | Rodeghiero M.,Research and Innovation Center | And 2 more authors.
European Journal of Forest Research

In this paper, we present a study on the efficiency of multi-return LIDAR (Light Detection Ranging) data in the estimation of forest stem volume over a multi-layered forest area in the Italian Alps. The goals of this paper are (1) to verify the usefulness of multi-return LIDAR data compared to single-return data in forest volume estimation and (2) to define the optimal resolution of a stem volume distribution raster map over the investigated area. To achieve these goals, raw data were segmented into a net, and different cell dimensions were investigated to maximize the relationship between the LIDAR data and the ground-truth information. Twenty predicting variables (e. g., mean height, coefficient of variation) have been extracted from multi-return LIDAR data, and a multiple linear regression analysis has been used for predicting tree stem volume. Experimental results found that the optimal resolutions of the net square cells were 40 m. The analysis indicated that in a mixed multi-layered forest, characterized by a complex vertical structure, the correct selection of the map spatial resolution and the inclusion of the secondary-return data were important factors for improving the effectiveness of the laser scanning approach in forest inventories. The experimental tests showed that the chosen model is effective for the estimation of stem volume over the analyzed area, providing good results on all the three considered validation methods. © 2010 Springer-Verlag. Source

Agency: Cordis | Branch: FP7 | Program: CP | Phase: ICT-2013.4.3 | Award Amount: 1.86M | Year: 2014

To make publishing and processing of linked data easy, the proposed project develops a set of integrated software components based on open-source Linked Data Platform best practices. The tightly integrated components support the multilingual data value chain from data exploration (e.g. identifying structured and unstructured data sources), extraction (e.g. using named entity recognition, RDF conversion), enrichment (e.g. interlinking, crowdsourcing), and delivery (e.g. analytics, apps for desktop and mobile devices). These components run on an open-source data platform with various enterprise-grade storage solutions.The vision is to make publishing and reuse of linked data as easy as possible for the end user thanks to a thriving market economy with data publishers, developers, and consumers along the value chain. Making data reusable and interoperable within and outside the organization requires a fundamentally different ap-proach to storing knowledge. The best name is probably a Logical Data Warehouse...because it focuses on the logic of information ...[for] giving integrated access to all forms of information assets. Only with integrated access to the data is it possible to have apps on top of that data that scale across single use cases and provide real added value.Fusepool LDAP (Linked Data Analytics Processing) derives its name from the idea of fusing and pooling linked data with analytical processing on top of it. Because linked data is multidimensional data, it lends itself to analytical processing such as consolidation (e.g. aggregation within a dimension), drill-down (e.g. navigating through the details), and slicing and dicing (e.g. viewing an aspect from different dimensions). However, an integrated publishing and processing workflow with integrated user interfaces is still missing. The lack of an integrated publishing and processing environment makes it difficult and time-consuming for data publishers and consumers to engage with linked data.

De Barba M.,University of Idaho | De Barba M.,Institute for Environmental Protection and Research | Waits L.P.,University of Idaho | Garton E.O.,University of Idaho | And 4 more authors.
Molecular Ecology

Genetic monitoring has rarely been used for wildlife translocations despite the potential benefits this approach offers, compared to traditional field-based methods. We applied genetic monitoring to the reintroduced brown bear population in northern Italy. From 2002 to 2008, 2781 hair and faecal samples collected noninvasively plus 12 samples obtained from captured or dead bears were used to follow the demographic and geographical expansion and changes in genetic composition. Individual genotypes were used to reconstruct the wild pedigree and revealed that the population increased rapidly, from nine founders to >27 individuals in 2008 (L = 1.17-1.19). Spatial mapping of bear samples indicated that most bears were distributed in the region surrounding the translocation site; however, individual bears were found up to 163 km away. Genetic diversity in the population was high, with expected heterozygosity of 0.74-0.79 and allelic richness of 4.55-5.41. However, multi-year genetic monitoring data showed that mortality rates were elevated, immigration did not occur, one dominant male sired all cubs born from 2002 to 2005, genetic diversity declined, relatedness increased, inbreeding occurred, and the effective population size was extremely small (Ne = 3.03, ecological method). The comprehensive information collected through genetic monitoring is critical for implementing future conservation plans for the brown bear population in the Italian Alps. This study provides a model for other reintroduction programmes by demonstrating how genetic monitoring can be implemented to uncover aspects of the demography, ecology and genetics of small and reintroduced populations that will advance our understanding of the processes influencing their viability, evolution, and successful restoration. © 2010 Blackwell Publishing Ltd. Source

Tonolli S.,Provincia Autonoma di Trento (Italy) | Dalponte M.,Research and Innovation Center | Neteler M.,Research and Innovation Center | Rodeghiero M.,Research and Innovation Center | And 2 more authors.
Remote Sensing of Environment

Remote sensing can be considered a key instrument for studies related to forests and their dynamics. At present, the increasing availability of multisensor acquisitions over the same areas, offers the possibility to combine data from different sensors (e.g., optical, RADAR, LiDAR). This paper presents an analysis on the fusion of airborne LiDAR and satellite multispectral data (IRS 1C LISS III), for the prediction of forest stem volume at plot level in a complex mountain area (Province of Trento, Southern Italian Alps), characterized by different tree species, complex morphology (i.e. altitude ranges from 65m to 3700m above sea level), and a range of different climates (from the sub-Mediterranean to Alpine type). 799 sample plots were randomly distributed over the 3000km2 of the forested areas of the Trento Province. From each plot, a set of variables were extracted from both LiDAR and multispectral data. A regression analysis was carried out considering two data sources (LiDAR and multispectral) and their combination, and dividing the plot areas into groups according to their species composition, altitude and slope. Experimental results show that the combination of LiDAR and IRS 1C LISS III data, for the estimation of stem volume, is effective in all the experiments considered. The best developed models comprise variables extracted from both of these data sources. The RMSE% on an independent validation set for the stem volume estimation models ranges between 17.2% and 26.5%, considering macro sets of tree species (deciduous, evergreen and mixed), between 17.5% and 29.0%, considering dominant species plots, and between 15.5% and 21.3% considering altitude and slope sets. © 2011 Elsevier Inc. Source

Magny M.,French National Center for Scientific Research | Joannin S.,French National Center for Scientific Research | Galop D.,French National Center for Scientific Research | Vanniere B.,French National Center for Scientific Research | And 5 more authors.
Quaternary Research

A lake-level record of Lake Ledro (northern Italy) spans the entire Holocene with a chronology derived from 51 radiocarbon dates. It is based on a specific sedimentological approach that combines data from five sediment profiles sampled in distinct locations in the littoral zone. On a millennial scale, the lake-level record shows two successive periods from 11,700 to 4500calyr BP and from 4500calyr BP to the present, characterized by lower and higher average lake levels, respectively. In addition to key seasonal and inter-hemispherical changes in insolation, the major hydrological change around 4500calyr BP may be related to a non-linear response of the climate system to orbitally-driven gradual decrease in insolation. The Ledro record questions the notion of an accentuated summer rain regime in the northern Mediterranean borderlands during the boreal insolation maximum. Moreover, the Ledro record highlights that the Holocene was punctuated by successive centennial-scale highstands. Correlations with the Preboreal oscillation and the 8.2ka event, and comparison with the atmospheric 14C residual record, suggest that short-lived lake-level fluctuations developed at Ledro in response to (1) final steps of the deglaciation in the North Atlantic area and (2) variations in solar activity. © 2012 University of Washington. Source

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