Spatial Decision Support Layers

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GIS Layers

A Spatial Decision Support System[1] operates on Layers as input data. Rule based system processes the layers and creates a decision support output (e.g. spatial multi-criteria evaluation and expert knowledge[2]). The output of spatial decision support system can be (among others) a spatial decision support layer again.

Mathematics: Spatial Decision Support Layer as Mapping[edit]

In terms of mathematical definition a spatial decision support layer is a mapping

where is the codomain (target set) of the mapping .

Domain of Spatial Decision Support Layer[edit]

includes the geographic coordinate system , the height and the time index . So is a subset of a threedimensional vector space . The geographic coordinate system is a coordinate system used in geography that enables every location on Earth to be specified by a set of numbers, letters or symbols. In specialized works, "geographic coordinates" are distinguished from other similar coordinate systems, such as geocentric coordinates and geodetic coordinates. See, for example, Sean E. Urban and P. Kenneth Seidelmann[3] The coordinates are often chosen such that one of the numbers represents a vertical position, and two or three of the numbers represent a horizontal position. A common choice of coordinates is latitude, longitude and elevation[4].

Output of Decision Support Layer[edit]

Think of the output set in the following categories, that are explain by examples:

  • (number) e.g. temperature is at time , at geolocation and at altitude
  • (set of objects nearby) the spatial decision support layer provides object that nearby, e.g. an geotagged ambulance and a health care facility :
with the geolocation of and .
The decision support layer answers the question,
 What are nearby health care services that I can get access to?

Ambulance might be nearer and mobile, while the health care facility might be far away but it might be far away but it could provide better health services. Decision makers will decide which resource will be used dependent on the disease or injury of a patient and the decision support layers provides the information, which resources are in reach of the patient's location. The example provides and as spatial objects, that contain the specification of the ambulance and the health care facility at .

Computer Science: Spatial Decision Support Layer as UML-Class[edit]

Learning Task[edit]

  • Learn about Spatial Fuzzy Logic and create a spatial decision support layer for temperature at specific time .
  • We use a membership function that maps a temperature into the real number between 0 and 1 (i.e. the interval ) by the following definition
With definition above the temperature is optimal for mosquitoes () at a temperature . If the temperature is higher than (e.g. ) or lower than the fuzzy value is decreasing for lower and higher temperatures example the domain can be defined as the set of real numbers , so that the membership function could take all temperatures in degrees Celsius as input variable.
  • Missing height altitude/time of argument: When the height/altitude is not provided, the altitude of the surface is use. Explain why this concept is helpful for decision makers.
  • How much time does it take to access a health care facility for get a specific health care service. This could vary in space and time due to environmental conditions.
means that it takes 3.5 hours to reach a health care facility at time . In a rainy season the value might change to (i.e. 10h travel time).
  • The function maps the the tupel with the longitude , the latitude , the elevation above sealevel and the time index to the temperature at the geolocation at altitude and time index .
  • Explain, why the altitude and time index are important input parameters for the temperature layer!
  • Composition defines a spatial decision support layers. Explain the purpose for vector control units working for a Public Health Agency.

See also[edit]


  1. Keenan, P. B. (2002). Spatial decision support systems. Decision Making Support Systems Achievements and Challenges for the New Decade, 28-39.
  2. Store, R., & Kangas, J. (2001). Integrating spatial multi-criteria evaluation and expert knowledge for GIS-based habitat suitability modelling. Landscape and urban planning, 55(2), 79-93.
  3. Explanatory Supplement to the Astronomical Almanac, 3rd. ed., (Mill Valley CA: University Science Books, 2013) p. 20–23.
  4. A guide to coordinate systems in Great Britain, Mar 2015, D00659 v2.3, access date 2015-06-22, Ordnance Survey,