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1.
IEEE Comput Graph Appl ; 44(1): 25-37, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-37812545

RESUMEN

Many subsystems of Earth are constantly monitored in space and time and undergo continuous anthropogenic interventions. However, research into this transformation remains largely inaccessible to the public due to the complexity of the Big Data generated by models and Earth observation. To overcome this barrier, we present the Leipzig Explorer of Earth Data Cubes (lexcube.org), an interactive Earth data visualization that allows users to explore terabyte-scale datasets with minimal latency through space, time, variables, and model variants. With over 2800 users and 163,000 API requests since its public release in May 2022, lexcube.org is a novel interactive data cube visualization that embraces the concept of "data cubes," enabling an equal treatment of space and time. We expect this development to be particularly relevant for the emerging exascale Digital Twins of Earth, as interactive visualizations in real-time could remove access barriers and help democratize Earth system sciences.

2.
Sci Data ; 10(1): 197, 2023 04 08.
Artículo en Inglés | MEDLINE | ID: mdl-37031236

RESUMEN

Spectral Indices derived from multispectral remote sensing products are extensively used to monitor Earth system dynamics (e.g. vegetation dynamics, water bodies, fire regimes). The rapid increase of proposed spectral indices led to a high demand for catalogues of spectral indices and tools for their computation. However, most of these resources are either closed-source, outdated, unconnected to a catalogue or lacking a common Application Programming Interface (API). Here we present "Awesome Spectral Indices" (ASI), a standardized catalogue of spectral indices for Earth system research. ASI provides a comprehensive machine readable catalogue of spectral indices, which is linked to a Python library. ASI delivers a broad set of attributes for each spectral index, including names, formulas, and source references. The catalogue can be extended by the user community, ensuring that ASI remains current and enabling a wider range of scientific applications. Furthermore, the Python library enables the application of the catalogue to real-world data and thereby facilitates the efficient use of remote sensing resources in multiple Earth system domains.

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