Introduction to Google Earth Engine

Step 1
To use Google Earth Engine you first have to sign up using a gmail account. Go to signup.earthengine.google.com and follow the steps to sign up for Earth Engine. Applications are reviewed and can take up to a week to be processed.

Step 2
Once you have signed up and been accepted to use Earth Engine you can begin to explore the tools capabilities.Once you've been accepted, you'll be able to access the Earth Engine Code Editor, the browser-based interactive development environment for Earth Engine analyses: code.earthengine.google.com.

Step 1
To access the Earth Engines datasets click on that Datasets tab on the Earth Engine homepage or navigate to developers.google.com/earth-engine/datasets/

Step 2
The Data Catalog gives you a number of options. You can view all datasets, browse by tags, or access datasets based on the satellite program they were created by. Landsat: the longest-running enterprise for acquisition of satellite imagery of Earth.  Modis: Moderate Resolution Imaging Spectroradiometer that was launched into Earth’s orbit in 1999. Sentinel: is part of Copernicus is the European Union's Earth observation programme.

Step 3
Select ‘Browse by tags’

Step 4
With in the browse by tags category there is access to all the datasets tagged by where they were produced, what they contain and what they can be used for. Select the NDVI dataset, which stands for normalized difference vegetation index.

Step 5
Once you click on NDVI you are taken to a library of all of the datasets which contain NDVI subsets. Each dataset has an image as well as a description of what it contains. Below the descriptions is the list of tags that have been added to that dataset.

Step 6
Find and click on MYD13Q1.006 Aqua Vegetation Indices 16-Day Global 250m

Step 7
You are now in the dataset. The information box at the bottom contains information on: Bands: the different types of imagery within the set; Terms of use: the licensing; Citations: How to cite the data correctly

Step 8
At the bottom of the page is a code snippet. This is a javascript snippet that if you click the “OPEN IN CODE EDITOR” button will open a new window with Earth Engine running.

Step 1
If you have been following our guide you should now have the NDVI data set code sample opened in the code editor. Click on the "Run" button at the top of the editor to execute the code sample, which will  render the dataset as a new layer on the world map.

Step 2
The code editor has now rendered the dataset on to the map. You can zoom in and pan on the map. In addition, by altering the code in the editor you can change the imagery displayed. If you change the dates where it says: .filter(ee.Filter.date('2018-01-01', '2018-05-01'));You can alter the imagery that is displayed on the screen.

Step 3
On the left side of the code editor is the Scripts manager. The scripts manager has code snippets that you can run in the editor to enable different features of Earth Engine. You can also save your work here by clicking NEW and then create a repository. Within the repository you can then save, share and track changes of folders and files that you are working on. The full documents on the code editor or available here.

Step 4
The search box at the top of the code editor allows you to search the Data Catalog. Get Link: Creates a unique link to the script that you are working on so that you can share it with others. ‘Save’ and ‘Run’ do as described while ‘Reset’ clears your code.

Step 5
On the right of the code editor are the Inspector, Console and Tasks tabs. The Inspector tab allows you to use your cursor to examine the layers visible on the map. The Console tab is where objects appear if you use the print() in the code editor. The ‘Tasks’ tabs handles long computations such as videos, exporting static map tiles, or exporting analysis results as tables, GeoTIFFs, and other formats.

Step 1
This image on the left tracks the growth and retreat of vegetation in eastern Africa over the course of one year using data from the NDVI imagery we added to the code editor earlier.

Step 2
First we need to identify the area. Add this code above the dataset:var rect = ee.Geometry.Rectangle({  coords: [[-12, 15], [3, 2]],  geodesic: false});Map.addLayer(rect);Map.centerObject(rect, 3);coords = the points of longitude and latitude to highlight. Click run.

Step 3
Now that we have the area highlighted we need to prepare the images for the GIF animation, using the visualize() method, which converts the native pixel data into 8-bit RGB, suitable for use in exported videos or GIFs:var visualizedCollection = ndvi.map(function(image){  return image.visualize(ndviVis)})var firstImage = ee.Image(visualizedCollection.first());map.addLayer(firstImage, {}, "first image");

Step 4
The second to last step is to specify the parameters for the animation:var animationParams = {    dimensions: '300',    crs: 'EPSG:3857',    region: geometry,    framesPerSecond: 12,}

Step 5
The final step is to create the thumbnail image and add it to the map:var thumb = ui.Thumbnail({   image: visualizedCollection,  params: animationParams,  style: {    position: 'bottom-right',    width: '320px'  }});Map.add(thumb);Click Run

Step 1
To export to video add the following code:Export.video.toDrive({  collection: visualizedCollection,  description: 'NDVIVideoExample',  dimensions: 720,  framesPerSecond: 12,  region: rect});Click Run

Step 2
As you are rendering out to a video this operation is created as a Task. If you go to the Tasks tab you will have created a Task that needs to be run to create the video. Once you click ‘Run’ a video will be rendered to your drive.This link here will take you to saved version of this scriptNote: Batch exports can take some time to complete. You can check the status of the export by looking at the Tasks tab. When the task completes, it will change color to blue.