Share:


Cartographic visualization of outputs for spatial decision-making in regional development

    Aleš Ruda Affiliation

Abstract

Regional development is full of planning and decision making. Having precise results for spatial decision making (SDM) is more than necessary. On one site, there are many approaches how to process input data, on the other hand thematic cartography also operates with many visualizing methods and techniques. Loss of accuracy of the results is more than expected because there are two phases (data processing during SDM and cartographic visualization) where the accuracy might be distorted. In both phases processing recommendations must be obeyed. Selection of spatial decision making method must follow considered aims as well as visualization techniques and setting their parameters (especially during reclassification, interpolation or generalization). Paper deals with the proposal of elementary scheme of SDM and related visualization during two case studies (CS). First CS represents composite indicators proposal followed by weighted sum method using heuristics approaches with the aim to identify the tourism influence on the landscape. Combined visualization techniques for quantitative and qualitative data are presented. Second CS uses ordered weighted average method for finding the best place for building of a new public logistics centre. Constraints and factors represent key indicators and following factor and order weights enable to propose the best accepted risk model. In this case grid maps describe derived values and chosen reclassification documents conversion into linguistic variables.

Keyword : choropleth map, grid map, generalization, reclassification, conversion, GIS

How to Cite
Ruda, A. (2015). Cartographic visualization of outputs for spatial decision-making in regional development. Geodesy and Cartography, 41(4), 174-184. https://doi.org/10.3846/20296991.2015.1120431
Published in Issue
Dec 17, 2015
Abstract Views
546
PDF Downloads
460
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.