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New data sources for cloudburst risk assessment and management

Urbana översvämningar orsakar stora samhällsskador och skyfallens snabba och lokala karaktär gör dem svåra att observera, förutsäga och varna för. Det finns också brist på data om översvämningsskador, främst på grund av knapp och icke-systematisk datainsamling och -hantering. I denna artikel presenterar vi ett nytt forskningsprojekt: SPARC. Det övergripande syftet med projektet är att förbättra säUrban flooding causes large societal damages and increased climate adaptation measures is needed. Therapid and local character of extreme rain events make them difficult to observe and predict, and to issuewarnings for. There is also a lack of data on urban flood damages, mainly because of scarce and nonsystematic data collection and management. In this paper, we present the approaches behind the

Urban land use and land cover classification with interpretable machine learning – A case study using Sentinel-2 and auxiliary data

The European commission launch of the twin Sentinel-2 satellites provides new opportunities for land use and land cover (LULC) classification because of the readily availability of their data and their enhanced spatial, temporal and spectral resolutions. The rapid development of machine learning over the past decade led to data-driven models being at the forefront of high accuracy predictions of t

Understanding of the Electrochemical Behavior of Lithium at Bilayer-Patched Epitaxial Graphene/4H-SiC

Novel two-dimensional materials (2DMs) with balanced electrical conductivity and lithium (Li) storage capacity are desirable for next-generation rechargeable batteries as they may serve as high-performance anodes, improving output battery characteristics. Gaining an advanced understanding of the electrochemical behavior of lithium at the electrode surface and the changes in interior structure of 2