Please use this identifier to cite or link to this item:
|Title:||Introduction to this special issue on geoinformatics for environmental surveillance|
|Authors:||DUBOIS Gregoire; CORNFORD Dan; HRISTOPOULOS Dionisis; PEBESMA Edzer; PILZ Jurgen|
|Citation:||COMPUTERS & GEOSCIENCES vol. 37 no. 3 p. 277-279|
|Publisher:||PERGAMON-ELSEVIER SCIENCE LTD|
|Type:||Articles in periodicals and books|
|Abstract:||The real time monitoring of our environment imposes a number of serious technical and methodological challenges to researchers. Environmental data need to be acquired and transmitted automatically to monitoring systems that need not only to be capable of automatically processing the information collected, but also to distinguish anomalies from background processes. Human intervention is usually required when anomalies are detected as very few methods are typically available to detect and characterize events that are difficult to predict. Characterising, communicating and propagating uncertainties are critical in these cases, since we are unlikely to have complete knowledge of the environment for the foreseeable future. The development of an automatic spatial interpolation system for mapping critical environmental variables is a good example illustrating the many obstacles one would encounter when designing a system able to cope with environmental processes that can fluctuate quickly in both space and time. A large oil spill in an ocean, the dispersion of volcanic ashes or an accidental release of radioactivity in the atmosphere first need to be detected by an existing monitoring network and then also monitored in real time to aid decision making. For the nuclear scenario, remote sensing techniques would be of little help and estimates at unsampled locations will have to be made available along with associated uncertainties. A number of statistical challenges encountered when dealing with similar cases was discussed in 2008 in a special issue of the journal Stochastic Environmental Research and Risk Assessment (Dubois, 2008). Some significant progress has subsequently been made, and we felt that the key role played by information systems in environmental monitoring and decision making has to date received relatively little attention. Not only are statistical methods needed to generate results in near real-time, but a much broader informatics infrastructure that includes data collection, exchange, manipulation and visualization for end-users is required. All these topics formed the theme of the StatGIS 2009 conference organized by the guest editors of this issue on the island of Milos, Greece, during June 2009. The main objective of the conference was to discuss the latest developments in spatial statistics and geoinformatics, with an emphasis on environmental monitoring and surveillance. As in the previous editions of the StatGIS conference series, this fourth edition addressed researchers in academia and research institutes, as well as practitioners and industry professionals who wanted to learn about recent developments in spatial statistics and its application. As in this special issue, we started with the collection of data from environmental sensors and monitoring networks and further discussed their use by the web services and systems involved in the processing of the information. The automated analysis of the data and the detection of anomalies and changes were also covered before finally addressing the visualization and communication of the generated information for efficient decision making. Application fields of interest for this conference therefore included spatial environmental modelling, early warning monitoring systems for the environment, geostatistics in natural hazards prediction, optimal spatial design, space-time analysis and remote sensing. From the 60 presentations made at StatGIS 2009, a selection is now presented in this special issue.|
|JRC Institute:||Sustainable Resources|
Files in This Item:
There are no files associated with this item.
Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.