Google Earth Engine Javascript Examples

This is a collection of examples how to code with Google Earth Engine Javascript API. If you are already signed up in Google Earth Engine, just copy and paste my code in the Google Earth Engine Sandbox.

Note: If you are interested in more tutorials or code snippets for Google Earth Engine JavaScript API, feel free to write me an email to rene.kopeinig@list.lu.

Sandbox Tutorials for Google Earth Engine

001 Landsat 8 Classification plus spectra chart

Classification Example for Landsat 8 plus spectra for classes in classified region.

002 Landsat 8 TOA Tasseled Cap Transformation:

Tasseled Cap Transformation for Landsat 8 based on the scientfic work "Derivation of a tasselled cap transformation based on Landsat 8 at-satellite reflectance" by M.Baigab, L.Zhang, T.Shuai & Q.Tong (2014). The bands of the output image are the brightness index, greenness index and wetness index.

003 RapidEye Spectral Angle Mapper:

Spectral Angle map calculation for RapidEye imagery. Please note, you might not be able to see the RapidEye imagery because they belong to a private repository. You can still use the Spectral Angle Mapper for Landsat as well.

004 Forest loss calculation:

Calculation of overall forest loss between 2010 and 2015 for the consecutive years.

005 Loss calculation for MODIS Landcover Classification's 'Mixed Forest' class:

Calculation of loss in class 'Mixed Forest' based on the MODIS Land cover classification 2012 between 2012 and 2015 for the consecutive years.

006 High potential forest map compared to MODIS Landcover Classification's forest classes:

High forest potential map for the Mexican state of Chiapas according to The Nature Conservancy and Alianza México REDD+ compared with MODIS Land cover classification 2012's forest classes.

007 RapidEye Tasseled Cap Transformation:

Tasseled Cap Transformation for RapidEye Imagery based on the scientfic work Derivation of Tasseled Cap Coefficients for RapidEye data by M.Schoenert, H.Weichelt, E.Zillmann & C.Jürgens (2014). The bands of the output image are the brightness index, greenness index and yellowness index. Note: You might not be able to see the RapidEye scene because of license issues but feel free to use my code on your RapidEye scene(s).

008 WEKA Learning Vector Quantization Clustering:

Example which demonstrates clustering that implements WEKA Learning Vector Quantization algorithm for Landsat 8 based on T. Kohonen, "Learning Vector Quantization", The Handbook of Brain Theory and Neural Networks, 2nd Edition, MIT Press, 2003, pp. 631-634.

009 Spectra analysis on Landsat 8 TOA & Proba-V S1 TOC

Example of spectra analysis on Landsat 8 TOA & Proba-V S1 TOC on features such as agriculture, urban and water.

010 MODIS regional or zonal statistics calculation

Regional or zonal statistics calculation based on a MODIS Net Primary Productivity (MOD17A3) for MODIS Land Cover Type (MCD12Q1) class 'Mixed forest'. Net Primary Productivity defines the rate at which all plants in an ecosystem produce net useful chemical energy.