National-scale mapping of building height using Sentinel-1 and Sentinel-2 time series.

ABSTRACT: Urban areas and their vertical characteristics have a manifold and far-reaching impact on our environment. However, openly accessible information at high spatial resolution is still missing at large for complete countries or regions. In this study, we combined Sentinel-1A/B and Sentinel-2A/B time series to map building heights for entire Germany on a 10 m grid resolving built-up structures in rural and urban contexts. We utilized information from the spectral/polarization, temporal and spatial dimensions by combining band-wise temporal aggregation statistics with morphological metrics. We trained machine learning regression models with highly accurate building height information from several 3D building models. The novelty of this method lies in the very fine resolution yet large spatial e

SUBMITTER: Frantz D 

PROVIDER: S-EPMC8190528 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature