Weight Impact on Comparative Evaluation of Topographic Data

• Autorzy: Borkowska Sylwia , Bielecka Elżbieta , Pokonieczny Krzysztof

Identyfikatory

DOI

10.7494/geom.2024.18.4.97

• Języki publikacji: EN

Abstrakty

EN

The paper addresses the problem of weighting in an analysis that supports the selection of a categorical data set according to user needs. Using the Relative Change (RC) of the Compound Correspondence Index (CCI), it is shown that weights have a significant impact on user choice – reaching extreme values in both urbanized and forested areas. Decreasing the weights from 0.25 to 0.17 in forested and built-up areas resulted in the maximum variations that were seen in the hot spot maps, with cold areas generally corresponding to builtup regions and hot areas to forested areas. The analysis covers seven counties that are located in different regions of Poland: Pomerania, Podlasie, Mazovia, Greater Poland and the Beskidy Mountains.

Słowa kluczowe

EN

quantitative data; OSM; sensitivity analysis; MCDA; TOPSIS

• Wydawca: AGH University of Science and Technology Press
• Czasopismo: Geomatics and Environmental Engineering
• Rocznik: 2024
• Tom: Vol. 18, no. 4
• Strony: 97--116
• Opis fizyczny: Bibliogr. 33 poz., il., tab.

Twórcy

autor

Borkowska Sylwia

• Military University of Technology, Faculty of Civil Engineering and Geodesy, Institute of Geospatial Engineering and Geodesy

• https://orcid.org/0000-0003-3183-1512

autor

Bielecka Elżbieta

• Military University of Technology, Faculty of Civil Engineering and Geodesy, Institute of Geospatial Engineering and Geodesy

• https://orcid.org/0000-0003-3255-1264

autor

Pokonieczny Krzysztof

• Military University of Technology, Faculty of Civil Engineering and Geodesy, Institute of Geospatial Engineering and Geodesy

• https://orcid.org/0000-0001-9114-5317

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024)