Mapping people distribution at very high resolution from remote sensing imagery and a priori coarse people counts

Abstract

The paper presents a fast and fully automatic method for estimating people distribution maps at very high resolution (≥ 25 m) from VHR optical imagery. This method is implemented in the High-res Urban Globe (HUG) suite of tools developed at DigitalGlobe, Inc. The methods relies on the a priori knowledge of coarse people counts to train a model acting on building features extracted from VHR imagery. Experiments and results show the high fidelity of HUG population density estimate to detailed census data.