Abstract: Varied distribution of resources, populations and Indigenous people result in significant socio-economic differences among statistical local areas (SLAs) in remote Australia. These differences indicate that the experience of change at the height of the resources boom will differ among SLAs in the region. Using hierarchical cluster analysis with Ward's minimum variance method, four socio-economic clusters were identified among the 197 SLAs in the region. The first was the most disadvantaged, with limited resources and human capital and the highest percentage of Indigenous people. The other three clusters improved in sequence, with the fourth having the most resources with the highest employment rate and income but least number of Indigenous people. Multivariate analysis of variance with main and interaction effects showed changes in demographics, industry structure, human capital and income over the period of investigation for the region as a whole and differences in the extent of these changes among the clusters. Policy interventions in the region are suggested for each group to match its specific needs.