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MASCOT: Multi-Criteria Analytical SCOring Tool for ArcGIS Desktop

Author

Listed:
  • Pierre Lacroix

    (Institute for Environmental Sciences, University of Geneva, EnviroSPACE Laboratory, Battelle – Building D, 7 route de Drize, CH-1227 Carouge, Switzerland;
    United Nations Environment Programme, Division of Early Warning and Assessment, Global Resource Information Database – Geneva, International Environment House, 11 chemin des Anemones, CH-1219 Chatelaine, Switzerland)

  • Helder Santiago

    (7 rue de Dizerens, CH-1205 Genève, Switzerland)

  • Nicolas Ray

    (Institute for Environmental Sciences, University of Geneva, EnviroSPACE Laboratory, Battelle – Building D, 7 route de Drize, CH-1227 Carouge, Switzerland;
    United Nations Environment Programme, Division of Early Warning and Assessment, Global Resource Information Database – Geneva, International Environment House, 11 chemin des Anemones, CH-1219 Chatelaine, Switzerland)

Abstract

Multicriteria Analytical SCOring Tool (MASCOT) is a decision-support tool based on spatial analysis that can score items (points, lines, and polygons) as a function of their Euclidian distance to other data (points, lines, polygons, rasters). MASCOT is integrated with ArcGIS 9.3.1 and makes it possible to achieve a complete workflow that may include data preparation and grouping of factors by theme, weighting, scoring, post-processing and decision-making. To achieve the weighting process, the Analytic Hierarchy Process (AHP) has been integrated. MASCOT was originally developed for the demining community, with the purpose of prioritizing clearance of mine hazards as a function of their distance to a set of predefined and measurable factors. We show here an example based on mine action data, but MASCOT is not limited to this community and many other application fields will benefit from it.

Suggested Citation

  • Pierre Lacroix & Helder Santiago & Nicolas Ray, 2014. "MASCOT: Multi-Criteria Analytical SCOring Tool for ArcGIS Desktop," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 13(06), pages 1135-1159.
    • Handle: RePEc:wsi:ijitdm:v:13:y:2014:i:06:n:s0219622014500783
    DOI: 10.1142/S0219622014500783
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    Cited by:

    1. Roberta Mele & Giuliano Poli, 2017. "The Effectiveness of Geographical Data in Multi-Criteria Evaluation of Landscape Services †," Data, MDPI, vol. 2(1), pages 1-11, February.

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