This paper presents a family of spatial polarisation indices that integrates distributional and spatial dimensions to measure economic polarisation. Traditional polarisation metrics either focus solely on distributional aspects or rely on exogenously defined regional partitions, limiting their applicability to dynamic spatial economies. Building on economic polarisation theory and spatial inequality decomposition, the proposed indices incorporate spatial adjacency relations and dynamically evolving regional configurations. By constructing intersection graphs that capture both attribute similarity (e.g., income levels) and geographic associations, this framework identifies spatially coherent clusters, and multiscalar measures of spatial polarisation across global, meso and local scales. The indices extend beyond bipolarisation to multipolarisation, allowing for richer insights into complex spatial-economic patterns. As an illustrative case study, the paper analyses the evolution of spatial income polarisation across Mexican states from 1940 to 2000. Findings highlight persistent north–south disparities, spatially cohesive low-income clusters, and fragmented high-income regions, underscoring the importance of dynamic spatial frameworks for understanding and addressing regional inequality. This approach provides policymakers and researchers with a flexible tool to examine the spatial dynamics of economic polarisation and identify endogenous regional formations over time.