Publication Details |
| Category | Text Publication |
| Reference Category | Journals |
| DOI | 10.5194/isprs-archives-XLVIII-4-W1-2022-301-2022 |
Licence  |
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| 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 10.5194/isprs-archives-XLVIII-4-W1-2022-301-2022 |
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