https://github.com/awesome-spectral-indices/spectral

Awesome Spectral Indices for the Google Earth Engine JavaScript API (Code Editor).

https://github.com/awesome-spectral-indices/spectral

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Awesome Spectral Indices for the Google Earth Engine JavaScript API (Code Editor).

README.rst

.. raw:: html

   
     

       
       

       Awesome Spectral Indices for the Google Earth Engine JavaScript API (Code Editor)
     
   

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        :alt: Documentation Status

.. image:: https://img.shields.io/badge/Paper-10.5194%2Fisprs--archives--XLVIII--4--W1--2022--301--2022-brightgreen
        :target: https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-301-2022

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        :target: https://github.com/awesome-spectral-indices/awesome-spectral-indices/blob/main/output/spectral-indices-dict.json
        
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- GitHub: `https://github.com/awesome-spectral-indices/spectral `_
- Documentation: `https://ee-spectral.readthedocs.io/ `_
- Awesome Spectral Indices: `https://github.com/awesome-spectral-indices/awesome-spectral-indices `_
- Examples/Tutorials: `https://github.com/awesome-spectral-indices/spectral/tree/main/examples `_

Overview
-------------------

`Google Earth Engine `_ (GEE) is a cloud-based service for geospatial processing of vector and raster data. The Earth Engine platform has a `JavaScript and a Python API `_ with different methods to process geospatial objects. Google Earth Engine also provides a `HUGE PETABYTE-SCALE CATALOG `_ of raster and vector data that users can process online. The `Awesome Spectral Indices `_ is a standardized ready-to-use curated list of spectral indices that can be used as expressions for computing spectral indices in GEE. The spectral module extends the GEE JavaScript API with new functions to access and compute spectral indices from the `Awesome List of Spectral Indices `_.

Check the simple usage of spectral here:

.. code-block:: javascript

   var spectral = require("users/dmlmont/spectral:spectral");
   
   var dataset = "COPERNICUS/S2_SR";

   var S2 = ee.ImageCollection(dataset).first();
   var S2 = spectral.scale(S2,dataset);
   
   var parameters = {
       "N": S2.select("B8"),
       "R": S2.select("B4"),
       "G": S2.select("B3"),
       "L": 0.5
   };
   
   var S2 = spectral.computeIndex(S2,["NDVI","GNDVI","SAVI"],parameters);
   
List
-------

Check the full list of spectral indices `here `_.

How does it work?
-----------------------

The spectral module can be accepted `HERE `_. Once accepted, it can be required by running the following line in the `GEE JavaScript Code Editor `_:

.. code-block:: javascript

   var spectral = require("users/dmlmont/spectral:spectral");

The complete list of spectral indices can be accessed by using the :code:`indices` attribute:

.. code-block:: javascript

   print(spectral.indices);

The list of available attributes for a specific index can be accessed using dot notation:

.. code-block:: javascript

   print(spectral.indices.NDVI);
   
Or by using a key:

.. code-block:: javascript

   print(spectral.indices["NDVI"]);
   
An attribute can be accessed using also dot notation:

.. code-block:: javascript

   print(spectral.indices.NDVI.formula);
   
Or by using a key:

.. code-block:: javascript

   print(spectral.indices.NDVI["formula"]);
   
The available attributes of an index are:

- :code:`short_name`: Short name of the index (e.g. :code:`"NDWI"`).
- :code:`long_name`: Long name of the index (e.g. :code:`"Normalized Difference Water Index"`).
- :code:`formula`: Expression/formula of the index (e.g. :code:`"(G - N)/(G + N)"`).
- :code:`bands`: List of required bands/parameters for the index computation (e.g. :code:`["N","G"]`).
- :code:`reference`: Link to the index reference/paper/doi (e.g. :code:`"https://doi.org/10.1080/01431169608948714"`).
- :code:`type`: Type/application of the index (e.g. :code:`"water"`).
- :code:`date_of_addition`: Date of addition to the list (e.g. :code:`"2021-04-07"`).
- :code:`contributor`: GitHub user link of the contributor (e.g. :code:`"https://github.com/davemlz"`).

Finally, an index (e.g. NDVI) can be computed using the :code:`computeIndex(img, index, params)` function:

.. code-block:: javascript

   var dataset = "COPERNICUS/S2_SR";
   
   var S2 = ee.ImageCollection(dataset).first()
   var S2 = spectral.scale(S2,dataset);
   
   var parameters = {
       "N": S2.select("B8"),
       "R": S2.select("B4"),
   };
   
   var S2 = spectral.computeIndex(S2,"NDVI",parameters);

And multiple indices can be computed using an array of indices:

.. code-block:: javascript

   var dataset = "COPERNICUS/S2_SR";
   
   var S2 = ee.ImageCollection(dataset).first()
   var S2 = spectral.scale(S2,dataset);
   
   var parameters = {
       "N": S2.select("B8"),
       "R": S2.select("B4"),
       "G": S2.select("B3"),
       "L": 0.5
   };
   
   var S2 = spectral.computeIndex(S2,["NDVI","GNDVI","SAVI"],parameters);

All specified indices are added as new bands.

License
-------

The project is licensed under the MIT license.

How to cite
-----------

Do you like using :code:`spectral` and think it is useful? Share the love by citing it!

.. code-block::

   Montero, D., Aybar, C., Mahecha, M. D., Wieneke, S. (2022). spectral: Awesome Spectral Indices deployed
   via the Google Earth Engine JavaScript API. The International Archives of the Photogrammetry, Remote Sensing 
   and Spatial Information Sciences, Volume XLVIII-4/W1-2022. Free and Open Source Software for Geospatial 
   (FOSS4G) 2022 Academic Track, 22-28 August 2022, Florence, Italy. doi: 10.5194/isprs-archives-XLVIII-4-W1-2022-301-2022

If required, here is the BibTex!

.. code-block::

   @article{Montero2022,
      doi = {10.5194/isprs-archives-XLVIII-4-W1-2022-301-2022},
      url = {https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-301-2022},
      year = {2022},
      volume = {XLVIII-4/W1-2022},
      pages = {301-306},
      author = {David Montero, Cesar Aybar, Miguel D. Mahecha, Sebastian Wieneke},
      title = {spectral: Awesome Spectral Indices deployed via the Google Earth Engine JavaScript API},
      journal = {The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences}
   }

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