2020
ESTIMATING DISPLACED POPULATIONS FROM OVERHEAD
Abstract
We introduce a deep learning approach to perform fine grained population estimation for displacement camps using high-resolution overhead imagery. We train and evaluate our approach on drone imagery cross-referenced with population data for refugee camps in Cox’s Bazar, Bangladesh in 2018 and 2019. Our proposed approach achieves 7.41% mean absolute percent error on sequestered camp imagery. We believe our experiments with real-world displacement camp data constitute an important step towards the development of tools that enable the humanitarian community to effectively and rapidly respond to the global displacement crisis.
Citation
@onlineHadzic_2020 author: Hadzic Armin and Christie Gordon and Freeman Jeffrey and Dismer Amber and Bullard Stevan and Greiner Ashley and Jacobs Nathan and Mukherjee Ryan title: Estimating Displaced Populations from Overhead year: 2020 month: Jun eprinttype: arXiv eprint: 2006.14547v2 howpublished: arXiv:2006.14547v2 url: http://arxiv.org/abs/2006.14547v2
Citation
@onlineHadzic_2020 author: Hadzic Armin and Christie Gordon and Freeman Jeffrey and Dismer Amber and Bullard Stevan and Greiner Ashley and Jacobs Nathan and Mukherjee Ryan title: Estimating Displaced Populations from Overhead year: 2020 month: Jun eprinttype: arXiv eprint: 2006.14547v2 howpublished: arXiv:2006.14547v2 url: http://arxiv.org/abs/2006.14547v2