In order to analyze decision problems,the need to integrate spatial data with algorithmic techniques hasbeen recognized and gave rise to a research stream in the contextof decision support systems (DSS) related to the so-called SpatialDecision Support Systems (SDSS).
As mentioned by Maniezzo et al., these systems are concerned with how to integrate spatiallyreferenced information in a decision making environment in order topositively affect the performance of decision makers, showing howspatially integrated DSS can be used to bridge the gap between policymakers and complex computerized models.
In the context of urban and regional planning, where the “thecomplexity of the decision problem is obvious” [22], DSS are used toassist governments and communities, aiding urban planners in organizing,analyzing, modifying, and re-evaluating existing or needed spatialinformation within land-use planning activities
In order to analyze decision problems,the need to integrate spatial data with algorithmic techniques hasbeen recognized and gave rise to a research stream in the contextof decision support systems (DSS) related to the so-called SpatialDecision Support Systems (SDSS).
As mentioned by Maniezzo et al., these systems are concerned with how to integrate spatiallyreferenced information in a decision making environment in order topositively affect the performance of decision makers, showing howspatially integrated DSS can be used to bridge the gap between policymakers and complex computerized models.
In the context of urban and regional planning, where the “thecomplexity of the decision problem is obvious” [22], DSS are used toassist governments and communities, aiding urban planners in organizing,analyzing, modifying, and re-evaluating existing or needed spatialinformation within land-use planning activities
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