@book{JRC31071,
	editor = {},
	address = {Luxembourg (Luxembourg)},
	year = {2005},
	author = {Dubois G},
	isbn = {92-894-9400-X},
	edition = {},
	abstract = {Computer-based decision-support systems for nuclear emergencies are, in many respects, similar to systems used to monitor natural hazards. For instance, monitoring
		networks regularly collect and report local observations of a variable that need to be
		converted into information with spatial continuity, in other words, maps that might be
		essential for decision-making. Ideally, these maps should be established automatically
		in order to allow real-time assessments and to minimize human intervention in case
		of emergency. Automating the spatial interpolation step is not as straightforward is it
		may sound: many methods exist, and each has its advantages and disadvantages. The choice of a method depends mainly on:
		1. the nature of the data,
		2. the density and spatial distribution of the sampling points,
		3. the spatial variability of the variable,
		4. the initial assumptions made on the phenomena being studied,
		5. the goals of the study (description, quantification, identification of hot spots, etc),
		6. the desired level of accuracy,
		7. the computing load,
		8. the experience of the user.
		},
	title = {Automatic Mapping Algorithms for Routine and Emergency Monitoring Data},
	url = {},
	volume = {},
	number = {},
	issn = {},
	publisher = {Office for Official Publications of the European Communities},
	doi = {}
}