Abstract
This study analyzed the spatial autocorrelation among Brazilian municipalities using the Sustainable Cities Development Index – Brazil (IDSC-Br) and GDP per capita through Exploratory Spatial Data Analysis with GeoDa software. Univariate and Bivariate Moran’s I were applied, revealing relevant regional patterns, with the predominance of the LL cluster (low IDSC-Br and GDP per capita) in the North and Northeast regions and the HH cluster (high values) in the Southeast and Midwest, while the HL and LH clusters occurred in transition areas. The findings highlight the importance of spatial analysis for monitoring sustainable development and identifying regional inequalities, providing support for public policy planning aligned with the Sustainable Development Goals (SDGs). Furthermore, the study emphasizes the need to consider local specificities and territorial dynamics when formulating strategies to promote a fairer, more balanced, and environmentally sustainable society.
Keywords: spatial interaction; local Moran's index; local development.