Application of fuzzy measures in multi-criteria evaluation in GIS

By Hongren Jiang, J. Eastman. International Journal of Geographical Information Science, 2000

769 citations recorded by the source corpus.

Subfields: Management, Monitoring, Policy and Law, Management Science and Operations Research, Signal Processing

View Paper: https://www.semanticscholar.org/paper/841006e205d0a2da3847866772baa55598e1a034

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In Management, Monitoring, Policy and Law

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Citations in the corpus

GIS-Based Multiple-Criteria Decision Analysis (2011, methodology): “7 Uncertainty: Whether the criteria and weighting should be modelled with certainty (i.e. deterministically) or uncertainty (i.e. probabilistically or fuzzily) (Jiang and Eastman 2000; Malczewski 1999a; Shepard 2005).”
A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping (2014, methodology): “Fuzzy sets have been applied in the context of MCDA in order to standardize criterion maps by assigning to each object a degree of membership or non- membership of each of the criteria (Jiang and Eastman, 2000; Gorsevski and Jankowski, 2010).”
GIS-multicriteria decision analysis for landslide susceptibility mapping: comparing three methods for the Urmia lake basin, Iran (2012, methodology): “…the degree to which a low standardized value on one layer can be compensated for by a high standardized value on other considered criteria risk refers to how much each criterion affects the final solution (Jiang and Eastman 2000; Malczewski 2006a; Robinson et al. 2010; Feizizadeh et al. 2012a).”
Quantifying cumulative impacts of human pressures on the marine environment: a geospatial modelling framework (2010, methodology): “The integration of MCA in Geographical Information System (GIS), i.e. a spatially explicit MCA, is a major contribution to the development of tools for integrated management (Jiang & Eastman 2000, Malczewski 2006).”
Implementing an extension of the analytical hierarchy process using ordered weighted averaging operators with fuzzy quantifiers in ArcGIS (2008, methodology): “These approaches can be generalized within the framework of ordered weighted averaging (OWA) (Jiang and Eastman, 2000; Makropoulos et al., 2003; Malczewski et al., 2003; Malczewski and Rinner, 2005; Malczewski, 2006b).”
Multi-attribute Decision Analysis in GIS: Weighted Linear Combination and Ordered Weighted Averaging (2009, background): “Jiang and Eastmann [17] suggested that those kinds of problems could be solved by considering decision-making as a set problem and through the application of fuzzy measures in multi-criteria evaluation.”