Mapping Local Climate Zones in Lausanne (Switzerland) with Sentinel-2 and PRISMA imagery: comparison of classification performance using different band combinations and building height data

ABSTRACT

The Local Climate Zone (LCZ) concept has emerged as a valuable classification system for climate-related studies. The World Urban Database and Access Portal Tools (WUDAPT) protocol provides a framework for generating a LCZ segmentation which relies on the supervised classification of multispectral imagery. However, since LCZ is based on the physical and thermal properties of the urban surfaces, more insightful information on the surface reflectivity characteristics – which is provided by hyperspectral sensors – may be beneficial for improving the LCZ classification. This assumption is investigated in this study by comparing the classification performance of a supervised algorithm applied to multispectral (Sentinel-2) and hyperspectral (PRISMA) satellite imagery. The study area is the city of Lausanne (Switzerland). Experiments are performed considering these sensors and different band combinations, including the building height layer as an additional band. Preliminary outcomes show that PRISMA imagery yields satisfying results in terms of classification accuracy while not outperforming Sentinel-2. An improvement is achieved by leveraging the first 10 PRISMA Principal Components which allows to retain the uncorrelated information out of the original bands. These first results will be validated in future investigations by improving image pre-processing and exploiting a larger number of seasonal PRISMA acquisitions.

KEYWORDS:

• Local Climate Zones
• Sentinel-2
• PRISMA
• supervised classification
• building height

Acknowledgements

This work was carried out in the frame of a PhD Program in Environmental and Infrastructure Engineering, funded by the Italian PON (Programma Operativo Nazionale) project scholarship entitled ‘Geospatial Enablement for Climate Change Impact Mitigation on Cities and Urban Resilience Acceleration’. This paper is based on the dataset made available by the Italian Space Agency (ASI): Data/Information generated by the authors under a license from ASI Original PRISMA Product – © ASI – 2021/2022. The authors would like to thank Mr. Olivier Travaglini, Cadaster and GeoInformation Department of the Vaud State, for providing the ancillary data (e.g. building height) of the city of Lausanne.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.