The 4.2 ka event in the vegetation record of the central Mediterranean

In this paper, the variation in forest cover in the central Mediterranean region, reflected by percentage changes in the arboreal pollen record, has been examined in relation to the 4.2 ka event. A total of 36 well-dated and detailed pollen records from latitudes between 45 and 36 degrees N were selected and their vegetation dynamics between 5 and 3 ka examined in relation to the physiographic and climatic features of the study area and to the influence of human activity on past vegetation, as suggested by anthropogenic pollen indicators. We have found that the sites located between 43 and 45 degrees N do not show any significant vegetation change in correspondence with the 4.2 ka event. Several sites located on the Italian Peninsula between 39 and 43 degrees N show a marked opening of the forest, suggesting a vegetation response to the climate instability of the 4.2 ka event. Between 36 and 39 degrees N, a forest decline is always visible around 4.2 ka, and in some cases it is dramatic. This indicates that this region was severely affected by a climate change towards arid conditions that lasted a few hundred years and was followed by a recovery of forest vegetation in the Middle Bronze Age. Human activity, especially intense in southern Italy, may have been favored by this natural opening of vegetation. In Sardinia and Corsica, no clear change in vegetation is observed at the same time. We suggest that during the 4.2 ka event southern Italy and Tunisia were under the prevalent influence of a north African climate system characterized by a persistent high-pressure cell

Open source tool for DSMs generation from high resolution optical satellite imagery. Development and testing of an OSSIM plug-in

The fully automatic generation of digital surface models (DSMs) is still an open research issue. From recent years, computer vision algorithms have been introduced in photogrammetry in order to exploit their capabilities and efficiency in three-dimensional modelling. In this article, a new tool for fully automatic DSMs generation from high resolution satellite optical imagery is presented. In particular, a new iterative approach in order to obtain the quasi-epipolar images from the original stereopairs has been defined and deployed. This approach is implemented in a new Free and Open Source Software (FOSS) named Digital Automatic Terrain Extractor (DATE) developed at the Geodesy and Geomatics Division, University of Rome ‘La Sapienza’, and conceived as an Open Source Software Image Map (OSSIM) plug-in. DATE key features include: the epipolarity achievement in the object space, thanks to the images ground projection (Ground quasi-Epipolar Imagery (GrEI)) and the coarse-to-fine pyramidal scheme adopted; the use of computer vision algorithms in order to improve the processing efficiency and make the DSMs generation process fully automatic; the free and open source aspect of the developed code. The implemented plug-in was validated through two optical datasets, GeoEye-1 and the newest Pléiades-high resolution (HR) imagery, on Trento (Northern Italy) test site. The DSMs, generated on the basis of the metadata rational polynomial coefficients only, without any ground control point, are compared to a reference lidar in areas with different land use/land cover and morphology. The results obtained thanks to the developed workflow are good in terms of statistical parameters (root mean square error around 5 m for GeoEye-1 and around 4 m for Pléiades-HR imagery) and comparable with the results obtained through different software by other authors on the same test site, whereas in terms of efficiency DATE outperforms most of the available commercial software. These first achievements indicate good potential for the developed plug-in, which in a very near future will be also upgraded for synthetic aperture radar and tri-stereo optical imagery processing

FOSS4G date assessment on the isprs optical stereo satellite data. A benchmark for DSM generation

The ISPRS Working Group 4 Commission I on "Geometric and Radiometric Modelling of Optical Spaceborne Sensors", provides a benchmark dataset with several stereo data sets from space borne stereo sensors. In this work, the Worldview-1 and Cartosat-1 datasets are used, in order to test the Free and Open Source Software for Geospatial (FOSS4G) Digital Automatic Terrain Extractor (DATE), developed at Geodesy and Geomatics Division, University of Rome "La Sapienza", able to generate Digital Surface Models starting from optical and SAR satellite images. The accuracy in terms of NMAD ranges from 1 to 3 m for Wordview-1, and from 4 to 6 m for Cartosat-1. The results obtained show a general better 3D reconstruction for Worldview-1 DSMs with respect to Cartosat-1, and a different completeness level for the three analysed tiles, characterized by different slopes and land cover

Read Operators and their Expressiveness in Process Algebras

We study two different ways to enhance PAFAS, a process algebra for modelling asynchronous timed concurrent systems, with non-blocking reading actions. We first add reading in the form of a read-action prefix operator. This operator is very flexible, but its somewhat complex semantics requires two types of transition relations. We also present a read-set prefix operator with a simpler semantics, but with syntactic restrictions. We discuss the expressiveness of read prefixes; in particular, we compare them to read-arcs in Petri nets and justify the simple semantics of the second variant by showing that its processes can be translated into processes of the first with timed-bisimilar behaviour. It is still an open problem whether the first algebra is more expressive than the second; we give a number of laws that are interesting in their own right, and can help to find a backward translation.Comment: In Proceedings EXPRESS 2011, arXiv:1108.407

Direct Marketing Autonomico

La tesi tratta due importanti branche del marketing, il direct e il database marketing (DM e DBM), e concetti ad essi correlati, ma non coincidenti: marketing interattivo e marketing relazionale. Si descrive quindi il progetto di una piattaforma software basata sull’apprendimento automatico volta ad affrontare importanti problemi di DM con un approccio originale. La prima parte del lavoro è di taglio economico-aziendale: si descrivono rilevanza, problematiche e metodi del DM e del DBM. Si descrivono i metodi matematico-statistici di uso più tradizionale e si accenna alle tecnologie dei data warehouse e del data mining. La seconda parte focalizza l’attenzione sul progetto, preliminarmente si descrivono i fondamenti teorici del reinforcement learning, una metodologia di apprendimento automatico derivante dall’intelligenza artificiale e, in questo lavoro, complementare al data mining. L’idea del progetto è di realizzare un sistema autonomico di gestione delle campagne di DM. Il sistema parte dai risultati di un’analisi di data mining e in base a questi seleziona i clienti da contattare e gli accoppiamenti cliente-offerta ottimali. Durante la campagna il sistema analizza in continuo i feedback provenienti dai clienti e in base a questi formula nuove ipotesi, adattando le conclusioni dell’analisi di data mining e ripianificando il proseguo della campagna

Upgrade of foss date plug-in: Implementation of a new radargrammetric DSM generation capability

Synthetic Aperture Radar (SAR) satellite systems may give important contribution in terms of Digital Surface Models (DSMs) generation considering their complete independence from logistic constraints on the ground and weather conditions. In recent years, the new availability of very high resolution SAR data (up to 20 cm Ground Sample Distance) gave a new impulse to radargrammetry and allowed new applications and developments. Besides, to date, among the software aimed to radargrammetric applications only few show as free and open source. It is in this context that it has been decided to widen DATE (Digital Automatic Terrain Extractor) plug-in capabilities and additionally include the possibility to use SAR imagery for DSM stereo reconstruction (i.e. radargrammetry), besides to the optical workflow already developed. DATE is a Free and Open Source Software (FOSS) developed at the Geodesy and Geomatics Division, University of Rome "La Sapienza", and conceived as an OSSIM (Open Source Software Image Map) plug-in. It has been developed starting from May 2014 in the framework of 2014 Google Summer of Code, having as early purpose a fully automatic DSMs generation from high resolution optical satellite imagery acquired by the most common sensors. Here, the results achieved through this new capability applied to two stacks (one ascending and one descending) of three TerraSAR-X images each, acquired over Trento (Northern Italy) testfield, are presented. Global accuracies achieved are around 6 metres. These first results are promising and further analysis are expected for a more complete assessment of DATE application to SAR imagery

NET-GE: a novel NETwork-based Gene Enrichment for detecting biological processes associated to Mendelian diseases

Enrichment analysis is a widely applied procedure for shedding light on the molecular mechanisms and functions at the basis of phenotypes, for enlarging the dataset of possibly related genes/proteins and for helping interpretation and prioritization of newly determined variations. Several standard and Network-based enrichment methods are available. Both approaches rely on the annotations that characterize the genes/proteins included in the input set; network based ones also include in different ways physical and functional relationships among different genes or proteins that can be extracted from the available biological networks of interactions

Free global DSM assessment on large scale areas exploiting the potentialities of the innovative google earth engine platform

The high-performance cloud-computing platform Google Earth Engine has been developed for global-scale analysis based on the Earth observation data. In particular, in this work, the geometric accuracy of the two most used nearly-global free DSMs (SRTM and ASTER) has been evaluated on the territories of four American States (Colorado, Michigan, Nevada, Utah) and one Italian Region (Trentino Alto-Adige, Northern Italy) exploiting the potentiality of this platform. These are large areas characterized by different terrain morphology, land covers and slopes. The assessment has been performed using two different reference DSMs: the USGS National Elevation Dataset (NED) and a LiDAR acquisition. The DSMs accuracy has been evaluated through computation of standard statistic parameters, both at global scale (considering the whole State/Region) and in function of the terrain morphology using several slope classes. The geometric accuracy in terms of Standard deviation and NMAD, for SRTM range from 2-3 meters in the first slope class to about 45 meters in the last one, whereas for ASTER, the values range from 5-6 to 30 meters. In general, the performed analysis shows a better accuracy for the SRTM in the flat areas whereas the ASTER GDEM is more reliable in the steep areas, where the slopes increase. These preliminary results highlight the GEE potentialities to perform DSM assessment on a global scale