Publication Details

Category Text Publication
Reference Category Journals
DOI 10.5194/isprs-archives-XLVIII-4-W1-2022-301-2022
Licence creative commons licence
Title (Primary) Spectral: Awesome Spectral Indices deployed via the Google Earth Engine JavaScript API
Author Montero, D.; Aybar, C.; Mahecha, M.D.; Wieneke, S.
Source Titel The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Year 2022
Department RS
Volume XLVIII-4/W1-2022
Page From 301
Page To 306
Language englisch
Topic T5 Future Landscapes
Keywords Remote Sensing; Spectral Indices; Google Earth Engine; JavaScript; Earth Systems
Abstract Spectral Indices derived from Remote Sensing (RS) data are widely used for characterizing Earth System dynamics. The increasing amount of spectral indices led to the creation of spectral indices catalogues, such as the Awesome Spectral Indices (ASI) ecosystem. Google Earth Engine (GEE) is a cloud-based geospatial processing service with an Application Programming Interface (API) that is accessible through JavaScript (Code Editor) and Python. Tools for computing indices, including raster operations, normalized differences, and expression evaluation methods have been developed in the API. However, users still have to hard-code spectral indices for the JavaScript library since there are no implementations that link catalogues of spectral indices to the Code Editor. Here we present spectral, a module that links the Awesome Spectral Indices (ASI) catalogue to GEE for querying and computing spectral indices inside the Code Editor. The module allows accessing and computing spectral indices from the catalogue for multiple remote sensing products in GEE. All indices can be queried by using a key-value model and computed by using a single method. The module demonstrates that spectral indices can be easily computed inside the Code Editor. Image and Image Collection objects can be used for the calculation of all spectral indices in the catalogue if the specific dataset counts with the required bands. We anticipate that spectral will be used by most GEE users for Earth System research. Analyses conducted by the community will be sped up by avoiding hard-coding and RS investigations will be boosted.
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=25204
Montero, D., Aybar, C., Mahecha, M.D., Wieneke, S. (2022):
Spectral: Awesome Spectral Indices deployed via the Google Earth Engine JavaScript API
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. XLVIII-4/W1-2022 , 301 - 306