A standardized catalogue of spectral indices to advance the use of remote sensing in Earth system research

作者：David Montero, César Aybar, Miguel D. Mahecha, Francesco Martinuzzi, Maximilian Söchting, Sebastian Wieneke · 发表于：Scientific Data · 年份：2023 · DOI：10.1038/s41597-023-02096-0 · 被引用次数：198 · 研究领域：Remote Sensing in Agriculture、Remote-Sensing Image Classification、Remote Sensing and Land Use

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 However, most of these resources are either closed-source, outdated, unconnected to a catalogue or lacking a common Application Programming Interface (API).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.