Gian Paolo Marra

Globus Monitoring and Discovery Service and SensorML for Grid Sensor Networks

This paper describes an approach based on Globus toolkit for developing grid sensor networks. In fact, the globus monitoring and discovery service is used to integrate sensor networks in grid environments by means of the design of an information structure based on sensor modeling language (SensorML). A case study is also presented in order to provide some relevant details about our approach and to verify the concrete applicability of the proposed methodology

A grid-enabled Web map server

Today Geographic Information Systems (GIS) provide several tools for studying and analyzing varied human and natural phenomena, therefore GIS and geospatial data has grown so much in both public and private organizations. A challenge is the integration of these data to get innovative and exhaustive knowledge about topics of interest. In this paper we describe the design of a Web map service (WMS) OGC-compliant, through the use of grid computing technology and demonstrate how this approach can improve, w.r.t. security, performance, efficiency and scalability, the integration of geospatial multi-source data. End users, with a single sign-on, securely and transparently, gets maps whose data are distributed on heterogeneous data sources belonging to one or more Virtual Organizations via distributed queries in a grid computing environment.

NDVI fluctuations from 1995 to 2006 in South Italy and North Africa: a search for a climate change indicator

Seasonal and interannual vegetation trends in the last eleven years were analyzed for two macro-regions, South Italy and North Africa, in search for evidence of climate changes and associated desertification processes. The South Italy macro-region comprises Apulia, Campania, Basilicata, Calabria and Sicily regions, while the North Africa one covers the northern part of Lybia. Vegetation index data for the whole Europe and North Africa can be retrieved from the DLR archive of thematic maps in the form of monthly composite Normalized Difference Vegetation Index (NDVI) maps. The DLR archive dates back to 1995, thus the analysis could only be carried out for the last eleven years. The analysis of temporal vegetation variations was performed by implementing specific routines which provide objective measurements of vegetation trends and anomaly. Rainfall data for the same periods and geographic areas, were also analyzed in order to investigate the correlation between the two phenomena. Results for the two selected macro-regions, from 1995 to 2006, are presented and discussed. In a successive phase, this study will focus on distinguishing vegetation variations at regional level, in order to compare different local trends.

G-AQFS: grid computing exploitation for the management of air quality in presence of complex meteorological circulations

Leveraging grid computing technology, i.e. the visualization of distributed computing and data resources such as processing, network bandwidth and storage capacity to create a single system image, we present a Grid Air Quality Forecast System (G-AQFS). The modeling system consists of meteorological and dispersion models coupled in cascade. The computational workflow of the modeling system is defined by means of DAGs (direct acyclic graph). A simple system is presented to manage and schedule the computational grid resources. As case study the system has been applied over Salento area, in the Apulia region (South-eastern Italy), to simulate ground level ozone concentration. Model predictions have been compared with field measurements, with reasonable results.