Health diseases caused by environmental pollution are a growing concern worldwide, which in recent years addressed more studies on causal links between environmental pollution and health at regional and global levels. A greater understanding is thus needed of the links between exposure to pollution and its effect on health, as well as the long term impact on health of chemical substances, biological organisms and physical changes in the environment. Monitoring and modelling are, therefore, a crucial activity for identifying the key pressures on the environment, the condition or state of the environment, and the level of environmental quality being achieved by society. Monitoring and modelling are inevitably challenging, not only from a technical point of view but also due to the complexity of the problems being addressed, originating in the interaction of multiple parameters at various levels of organization (anthropogenic or biological, individual or population) and scale (from global to local). Using the information collected through monitoring provides big challenges in integrating and connecting the various information sources used and the technologies implemented. Data and model simulations are, therefore, crucial to support policy makers and public participation within any environmental decision making process as well as for a broad understanding of the environment. However, these data are not always available to the public and are not usually in a format that is understood by all the different stakeholders. Also, monitoring systems show relevant discrepancies in terms of spatial and temporal trends, as they do not cover appropriate regions, are discontinue along years and are often application-oriented. To fulfil he gap Spatial Data Infrastructures (SDIs) have been developed.
A Spatial Data Infrastructure for Geo Data management / D'Amore, Francesco. - (31/01/2013).
A Spatial Data Infrastructure for Geo Data management
Francesco D'Amore
31/01/2013
Abstract
Health diseases caused by environmental pollution are a growing concern worldwide, which in recent years addressed more studies on causal links between environmental pollution and health at regional and global levels. A greater understanding is thus needed of the links between exposure to pollution and its effect on health, as well as the long term impact on health of chemical substances, biological organisms and physical changes in the environment. Monitoring and modelling are, therefore, a crucial activity for identifying the key pressures on the environment, the condition or state of the environment, and the level of environmental quality being achieved by society. Monitoring and modelling are inevitably challenging, not only from a technical point of view but also due to the complexity of the problems being addressed, originating in the interaction of multiple parameters at various levels of organization (anthropogenic or biological, individual or population) and scale (from global to local). Using the information collected through monitoring provides big challenges in integrating and connecting the various information sources used and the technologies implemented. Data and model simulations are, therefore, crucial to support policy makers and public participation within any environmental decision making process as well as for a broad understanding of the environment. However, these data are not always available to the public and are not usually in a format that is understood by all the different stakeholders. Also, monitoring systems show relevant discrepancies in terms of spatial and temporal trends, as they do not cover appropriate regions, are discontinue along years and are often application-oriented. To fulfil he gap Spatial Data Infrastructures (SDIs) have been developed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.