The NEXUS area covers approximately 30% of the Brazilian territory. In order to assist preservation and sustainable development policies in that region, this study proposes to replicate the work done by Yeh et al in Africa , in which a convolutional neural network estimates indicators through satellite images, each covering a region of approximately 45 km². This work compares the size and distribution of Brazil’s census tracts with those in Africa to define if the scale of images can be maintained and to define the clusters that will be used. To avoid biasing the model, special care must be taken in selecting clusters, such as keeping a balance between urban and rural sectors and, most importantly, making sure that there is little to no overlap of clusters. To do so, two approaches were proposed. The first one samples tracts in each municipality as centroids for clusters, the second merges neighboring urban tracts into a single group and fits clusters to these groups.