Mapping Gated Neighborhoods in the Metropolitan Area of Buenos Aires Using Deep Learning and VHR Multispectral Images

Gated Neighborhoods are residential areas characterized primarily by being closed urbanized spaces, with low construction density, and low-rise buildings, as well as significant areas dedicated to green spaces and sometimes to bodies of water. They are widely spread in large urban areas across South America, and they can be found in many locations within the Metropolitan Area of Buenos Aires, Argentina.Despite their significant expansion in recent years, public geographic database of GNs in Argentina is outdated, making it difficult to monitor their expansion over natural areas such as wetlands. To automate the process of mapping GNs we developed a methodology using PlanetScope images in input and the YOLOv5 convolutional neural network as a processing tool. The results show Precision of 0.85, Recall of 0.71 and mean IoU of 0.8. These are promising results to generate an operative tool that could aid in the procedure of mapping GNs.