Use of Remotely Piloted Aircraft to Update Spatial Data in Areas of Social Fragility

A considerable amount of the Brazilian population lives in informal settlements, where there is a massive dynamic of territorial transformation. In this sense, the use of Remotely Piloted Aircraft (RPA) has shown an excellent cost-benefit relation for expeditiously collecting spatial data aiming at the identification of territorial objects, which can be an essential resource to assist planning and public management. This study presents a methodology for updating the spatial database collected by airborne LiDAR (Light Detection and Ranging) using an RPA and high precision GNSS (Global Navigation Satellite System) receivers. The study was carried out in an area of social fragility located in Belo Horizonte, Brazil, which presents geomorphological complexity, high density of territorial occupation, unplanned infrastructure, and complex urban morphology. Such associated characteristics are understood as social risk factors, creating difficulties for technical managers and locals. In that municipality, data are collected with airborne LiDAR every seven years for urban management purposes. However, the dynamics of territorial transformation in these places is very intense, generating demand for updating the database. For this purpose, the Digital Surface Model (DSM) generated by RPA was associated with the DSM generated by LiDAR through raster algebra. The results show the buildings’ pavement increases and new buildings’ construction, indicating to public managers the territorial changes in the analyzed period.