Local climate zone-based urban land cover classification from multi-seasonal Sentinel-2 images with a recurrent residual network.

ABSTRACT: The local climate zone (LCZ) scheme was originally proposed to provide an interdisciplinary taxonomy for urban heat island (UHI) studies. In recent years, the scheme has also become a starting point for the development of higher-level products, as the LCZ classes can help provide a generalized understanding of urban structures and land uses. LCZ mapping can therefore theoretically aid in fostering a better understanding of spatio-temporal dynamics of cities on a global scale. However, reliable LCZ maps are not yet available globally. As a first step toward automatic LCZ mapping, this work focuses on LCZ-derived land cover classification, using multi-seasonal Sentinel-2 images. We propose a recurrent residual network (Re-ResNet) architecture that is capable of learning a joint spectral-spat

SUBMITTER: Qiu C 

PROVIDER: S-EPMC6686635 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature