This study examined the spatial distribution of childhood community-acquired pneumonia detected through prospective surveillance in Goiânia, Brazil. Three spatial analysis techniques were applied to detect intra-urban geographic aggregation of pneumonia cases: Kernel method, nearest neighbor hierarchical technique, and spatial scan statistic. A total of 724 pneumonia cases confirmed by chest radiography were identified from May 2000 to August 2001. All cases were geocoded on a digital map. The annual pneumonia risk rate was estimated at 566 cases/100,000 children. Analysis using traditional descriptive epidemiology showed a mosaic distribution of pneumonia rates, while GIS methodologies showed a non-random pattern with hot spots of pneumonia. Cluster analysis by spatial scan statistic identified two high-risk areas for pneumonia occurrence, including one most likely cluster (RR = 2.1; p < 0.01) and one secondary cluster (RR = 1.3; p = 0.01). The data used for the study are in line with recent WHO-led efforts to improve and standardize pediatric pneumonia surveillance in developing countries and show how GIS and spatial analysis can be applied to discriminate target areas of pneumonia for public heath intervention.