Data Descriptor evaluates LiDAR device performance in spatial data acquisition within favelas, highlighting implications for urban planning.
Favelas (slums) are densely populated informal settlements that house over 1.1 billion people globally and represent challenging environments for spatial data acquisition and urban mapping. Their dense morphology, irregular street networks, and overlapping building structures make conventional mapping approaches difficult. These areas are often characterized by limited access to essential services such as water supply, sanitation, and waste collection, as well as insecure land tenure. Despite their scale, favelas are frequently absent from official maps, limiting their inclusion in urban planning processes. This Data Descriptor presents a terrestrial LiDAR dataset collected with five distinct devices along a standardized 360-meter survey route in Jardim Colombo, a favela in São Paulo, Brazil, covering approximately 5,685 m². The area was also surveyed using aerial photogrammetry and a total station to establish a spatial reference supporting comparison among the terrestrial LiDAR devices. A multicriteria framework evaluates device performance considering point density, completeness, spatial uniformity, and logistical constraints. These data support research in urban environments where accurate spatial representation remains a critical challenge.
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Dimitrov et al. (2026) studied this question.
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