Automated National Urban Map Extraction

arXiv:2404.06202v1 Announce Type: new
Abstract: Developing countries usually lack the proper governance means to generate and regularly update a national rooftop map. Using traditional photogrammetry and surveying methods to produce a building map at the federal level is costly and time consuming. Using earth observation and deep learning methods, we can bridge this gap and propose an automated pipeline to fetch such national urban maps. This paper aims to exploit the power of fully convolutional neural networks for multi-class buildings' …

abstract arxiv automated bridge building cs.cv deep learning developing countries earth earth observation extraction gap generate governance map observation photogrammetry type update urban