Evolving Spatial Weights for Cartographic Synthesis
The integration of multiple thematic data layers into a single composite map, known as the cartographic synthesis problem, is typically addressed through expert-driven weighting schemes. This study presents a multi-objective formulation of cartographic synthesis grounded in spatial autocorrelation structure. We develop a bi-objective evolutionary framework, GIS-moGA, that estimates layer weights by simultaneously maximizing global spatial structure, measured by Global Moran's I, and minimizing local spatial heterogeneity, measured by the variance of Local Indicators of Spatial Association (LISA). Because naive evaluation of spatial relationships requires O(N^2) operations, direct computat...
| Authors | Gesiel R. Lopes, Roberto F. da Silva, Mellina Yamamura et al. |
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| Primary category | cs.LG |
| Published | 20 June 2026 |
| Last updated at source | 20 June 2026 |
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