Introduction to Google Earth Engine

Earth Engine Explorer (EE Explorer) is a lightweight geospatial image data viewer with access to a large set of global and regional datasets available in the Earth Engine Data Catalog. It allows for quick viewing of data with the ability to zoom and pan anywhere on Earth, adjust visualization settings, and layer data to inspect change over time.

This tutorial will cover the use of the EE Explorer application, including:

  • how to find data in the Data Catalog
  • adding data to the Workspace
  • explanation of interface features
  • how to tailor data visualization

The goals of this tutorial are to enable you to use EE Explorer, inspire you to discover and view new data, and provide a starting point to imagine how you might expand your exploration using the other more powerful Earth Engine platform tools to answer questions about the current state and ongoing changes affecting the Earth.

Tutorial Contents

Earth Engine Explorer

Follow this link ( to take you to the EE Explorer application. EE Explorer is composed of an integrated Data Catalog and Workspace. The Workspace is where you’ll view data, and the Data Catalog is where you‘ll discover and import data to the Workspace. Common to both of these components are a set of buttons to toggle between the Data Catalog and the Workspace and a search bar where you can find datasets and places by keyword and location name. Following the above link takes you to the Workspace, as shown in the image below. This is where we’ll spend most of our time in this lesson, but before we get started, we’ll need some data. Let’s check out the Data Catalog.

Earth Engine Explorer

Data Catalog

The Data Catalog lists the datasets available for viewing and analysis in Earth Engine proper. A subset of the data are available for display in EE Explorer.

  • Click on the Data Catalog button in the upper right of the EE Explorer app.

On the Data Catalog page you will see a list of Popular Tags, linking to datasets that have those tags applied. Below that is a list of various data types and multi-day mosaics, including brief descriptions of, and direct links to, a handful of the available datasets. To access other datasets, use the search bar at the top of the page.

  • Click on a few of the popular tags to see what kinds of datasets they contain.
    • For example, toa brings up a list of datasets depicting “top-of-atmosphere reflectance”.
    • Clicking on usgs brings up a list of datasets from the USGS, including datasets from Landsat, MODIS, and products derived from them.
  • On the Data Catalog page, click on the 32-day tag to bring up all the 32-day mosaics.
  • Select the Landsat 8 Collection 1 Tier 1 32-Day NDWI Composite to open its detail page, shown below.

Landsat 8 Collection 1 Tier 1

This page shows details about the selected dataset, including its name, a brief description, a sample image, and information such as which dates are available, the provider’s name, and any tags for that dataset. There is also a blue Open in workspace button which can be used to add the dataset to your current workspace (more on that below).

You can return to the Data Catalog page by clicking your browser Back button twice, or by clicking the Data Catalog button in the upper right.


The Workspace is where you manage and visualize datasets in EE Explorer.

  • Click on the Workspace button in the upper right of any EE Explorer page.


On the Workspace page, you will see a map on the right, and space for a list of data layers on the left. Unless you have already added a dataset to your workspace, your Data list will be empty, and the map will show the Google Maps terrain layer, as shown above. As a reminder for navigating the Google Maps interface, the following points provide some basics.

  • Panning:
    • Right or left click + hold + drag.
  • Zooming:
    • Buttons: zoom in and out with the [+] and [-] buttons.
    • Pointer: zoom in with double-left-click, out with double-right-click.
    • Mouse wheel: zoom in and out by scrolling your mouse wheel. The mouse settings for your computer will determine the action of forward and backward scrolling.
    • Touch screen/trackpad: two-finger expand to zoom in, contract to zoom out.

    To change the map background, use the buttons in the upper right of the map to select either Map view or Satellite view. When selecting Map view, a checkbox will appear below the Map button to turn on/off Terrain instead of the road-map view. When selecting Satellite, a checkbox will appear below the Satellite button allowing you to turn on/off the Labels (borders, countries, cities, water bodies, etc.).

    Now let’s view some data in the Workspace.

Managing Data Layers

Adding data layers

  • Click the Data Catalog button to return to the Data Catalog page.
  • Search for MCD43A4.006 MODIS Nadir BRDF-Adjusted Reflectance in the search bar.
  • Click the result to display its details. It is a MODIS reflectance mosaic of the best pixel over a 16-day period.
  • On the dataset details page, click the blue Open in Workspace button. This will bring you to the Workspace, with the dataset visible as a layer.
  • Alternatively, you can skip the details page and open the layer in your Workspace directly from the Data Catalog by clicking the “open in workspace” link next to the dataset name.


After adding the data, you will see that the dataset is overlain on the Google Maps base layer, the dataset name is added to the Data list, and the layer’s visualization settings dialog is open and attached to the right of the dataset name.

  • Close the Layer Settings dialog for now - we’ll revisit it later.
  • Pan and zoom the map to get a sense for the controls.
  • Zoom as far as possible on a location of your choice to see the maximum resolution of the dataset. The MODIS data we’re using in this example has only moderate resolution (each pixel is 500 meters on a side; note that this MODIS data uses a sinusoidal projection, which results in parallelogram-shaped pixels when displayed on a geographic canvas).
  • Set the view frame to a regional scale centered on a location of interest, preferably one that has some diversity in land cover type. Note that this tutorial will display examples from the United States.


Layer visibility

  • Toggle off the visibility of the data layer by clicking the visibility button (eye icon) to the right of the data layer name. You will see the Google Maps terrain view revealed.
  • Click the visibility button (eye icon) again to make the data layer visible on the map again.

Toggle Visibility

Note that some datasets can only be shown at certain zoom levels. For example, if you are zoomed all the way out to a global view with Landsat 8 dataset, it will not be visible on the map. Don’t worry, it’s not broken! A yellow bar appears at the top of the map saying that you need to zoom in to view the data. Also, note that some datasets contain missing data as a result of quality masking and absent observations. Pixels representing these data are set to 100% transparent, allowing the Google Maps base layer to show through.

Adjusting data layer date

An added layer will generally default to the most recent temporal representation. You can adjust the date(s) displayed through the layer’s visualization settings dialog.

  • Click on the MCD43A4 layer name in the Data list to bring up the Layer Settings, as shown below.
  • Change the date of data display by dragging the time slider or clicking the date cells. Notice that the map will automatically update upon these actions.
  • To go farther back in time, or to select a specific date range, click on the Jump to date link below the time slider and use the calendar interface to select a date. Try selecting a different season to see more dramatic changes to the map.


  • When you have selected the date range you wish to work with, click the Save button to save the Layer Settings. If you wish to return to your previous settings, click the Cancel button instead. If you close the Layer Settings without saving, the layer display properties will revert to their previous state.


Adding multiple layers

You can view multiple data layers on your map at once by adding additional datasets. To add additional datasets, return to the Data Catalog and simply select another dataset. You can access the Data Catalog any of three ways:

  1. Click the Data Catalog button in the top right button bar.
  2. Click on the “+” button at the top right of your data layer list.
  3. Click the Add data link at the bottom of your data layer list.

Though tempting, avoid using the search bar, as it will return many results that are not compatible with EE Explorer (only accessible through Earth Engine proper). For datasets having either “open in workspace” following the data name or Open in Workspace button in their description page, click the link to add it as an additional layer to your Workspace data list. The new data layer will appear above your current data layer(s) both in the data list and the map. See below for changing the order of the layers.


Duplicate datasets

You can also add the same dataset twice, as two separate layers in your Workspace. One reason to do this would be to view two different time slices of the same dataset, to view change over time. For more on this, see the Visualizing change over time section below.

Reordering layers

When you have more than one dataset visible on your map, the one listed at the top of the Data list will be drawn on top of those below it. To change the order, left-click + hold + drag the layer handle found to the left of the dataset name in the Data list. Note that in the example image below, the SRTM Digital Elevation Data Version 4 dataset has been added. Try adding a new layer and change layer visibility by reordering the layers, and alternating visibility with the visibility icon.


Removing layers

  • Click on the data layer name in the Data list to bring up the Layer Settings dialog.
  • Click the Trash button and the layer will be removed from your Data list and from the map.


Now that you know the basics, let’s explore a few of the more powerful things you can do in the EE Explorer workspace. In the sections below, we’ll go over adjusting a layer’s visualization parameters and visualizing change over time.

Setting visualization parameters

In the Layer Settings dialog, you will see a Visualization Parameters dropdown. Each dataset has different default values, but you can modify them to change how you visualize the dataset.

  • Ensure the MCD43A4 Layer Settings dialog is open.
  • If the Visualization Parameters are not expanded, do so by clicking on the section title.


Data band display

Data can be viewed as either single-band grayscale, single-band pseudo-color, and three-band RGB.

  • Single-band display is useful for viewing a single continuous variable such as elevation, vegetation indices like NDVI, or precipitation.
  • Three-band display is useful for viewing image data where each of three selected bands are assigned to gradients of red (R), green (G), and blue (B) color, respectively. Mixing of the bands in RGB space results in a final display color. Natural color and false color visualization is achieved this way.

Single-band grayscale

Some data have only a single band and will default to single-band display. Multi-band data will default to three-band display, but you can choose to view just a single band as grayscale. Note that you can also display single-band data as three-band RGB display, but the map appearance will not change. To demonstrate visualizing a single band, let’s try it with an elevation layer and then try looking at a single band of the multi-band MCD43A4 Nadir reflectance data.

  • Use one of the previously mentioned methods for accessing the Data Catalog and search for the SRTM Digital Elevation Data Version 4 dataset and add it to your Workspace. The data will appear at the top of your Data list and map. What you are seeing is elevation above sea level represented as a color gradient from black (low elevation) to white (high elevation).
  • Open the Layer Settings if they are not already. Notice that the 1 band (Grayscale) radio button is activated by default, indicating that there is only 1 band for this dataset - click the band selector dropdown to verify.


  • Close the Layer Settings dialog and then move the MCD43A4 Nadir reflectance data to the top of the data list or alter the visibility of the layers so that it is shown on the map.
  • Click on its name to reveal the Layer Settings. Notice that this dataset is displayed as three-band RGB by default, indicating it is a multi-band raster. You can, however, choose to view a single band as grayscale by activating the 1 Band (Grayscale) radio toggle.
  • Activate the 1 band (Grayscale) radio toggle.
  • Click the Band Selection dropdown and choose a different band to display as grayscale.
  • Click the Save button after selecting a new band and you’ll see the map display change from color to grayscale. The band you selected is now being represented as a color gradient from black (low reflectance) to white (high reflectance).

Note that you can preview changes by clicking the Apply button, which will change the map to reflect your changes, while keeping the Layer Settings dialog open and ready for adjustments.

Three-band true color

Let’s work with the MCD43A4 data again to understand three-band display, as well as changing the color assignment to various bands.

  • Ensure that the MCD43A4 layer is the first dataset in the list and is visible.
  • Click on its name to reveal the Layer Settings and make sure that the 3 Bands (RGB) radio toggle is activated.
  • Click the Band Selector drop downs for Red, Green, and Blue and notice the band name assigned to each color.


  • Ensure that Nadir reflectance bands 1, 4, and 3 are assigned to red, green, and blue, respectively, and then click the Save button. The map display should show land cover as it appears naturally to our color interpretation of the world.

If you visit the data description page for this layer, you’ll see that these three bands are associated with reflectance in particular wavelength ranges. In this case, band 1 represents reflectance intensity in the blue part of the electromagnetic spectrum, 4 in the green range, and 3 in the red range. Pairing red, green, and blue reflectance bands to red, green, and blue display color will produce a natural color image very similar to what our eyes see as we view the landscape from a plane, for instance.


Three-band false color

Natural color is nice because it is familiar, but assignment of reflectance bands outside of what we can see with our eyes to RGB color allows us to “see” landscapes in a whole new way. These types of data representations are called false color composites. They often include representation from the visible, near-infrared (NIR), and shortwave (SWIR) ranges of the electromagnetic spectrum. False color display can accentuate inter- and intra-landscape feature type contrast, improving some aspects of image interpretation. To demonstrate, let’s visualize the “standard” false color composite, where NIR, red, and green reflectance bands are assigned to display colors red, green, and blue, respectively.

  • Open the MCD43A4 data Layer Settings dialog.
  • Ensure the 3 Bands (RGB) radio toggle is active.
  • Set the Red, Green, and Blue Band Selector dropdowns to Nadir reflectance bands 2, 1, and 4, respectively.
  • Click the Save button to apply the changes to the map layer display and close the Layer Settings. You should see a dramatic shift in vegetation color from green to red.


Contrast, brightness, and opacity

Data range

The contrast and brightness of an image can be adjusted using the Range (min and max) and Gamma parameters. Visualization of data requires that a given value range be scaled between 0 and 255 for each band being displayed. The range parameter allows you to adjust the range of values to display. The defined min value will be drawn to 0 and the max to 255, all data values in between the defined min and max range are scaled linearly. Data outside the min and max range are set to either 0 or 255, depending on whether they are less than or greater than the provided range. Let’s try to add some more contrast to a vegetated region to better distinguish subtle differences in vegetation cover.

  • Using the “standard” false color display applied in the previous section, go the eastern United States.
  • Open the Layer Settings and set the Range parameter to min: 2000 and max: 5500.
  • Apply the new setting by clicking the Save button.

You should now see greater contrast - areas of red look less saturated. We have narrowed the visible data range and exaggerated the disparity between high reflectance in red and low reflectance in near-infrared.



Gamma represents the relationship between a value and the luminance used to represent it. Roughly speaking, increasing gamma increases the intensity of values in the middle of the visualization range. It adjusts image brightness and contrast.

  • Using the above adjusted data range, open the Layer Settings again and try setting the Gamma to a lower value like 0.75.
  • Apply the change and you’ll notice that the contrast has increased further.



Opacity is the condition of lacking transparency. It is on a scale from 0 to 1, where 0 is transparent and 1 is opaque. It can be helpful for maintaining some visibility of the top data layer while also displaying information from underlying layers. In the example below, opacity has been set to 0.6, which faintly reveals the underlying Google Maps terrain layer. With this data view it is possible to determine which states have the greatest vegetation response for the given time period of the image (May 23rd, in this case).


Note that setting the data Range, Gamma, and Opacity applies to both three-band and single-band displays.


A palette allows you to assign colors to the range of values in a dataset to single-band (grayscale) display. A palette is a series of hexadecimal color values. Providing two values sets the colors of the defined min and max value of the dataset explicitly, and all values in between are mapped to a linear interpolation of the color gradient. For example, the SRTM digital elevation model is displayed in shades of gray by default, but we can display it in shades of green instead, where the lowest elevation pixels are black and the highest elevation pixels are green (“lowest” and “highest” are defined by the Range parameter).

  • Make sure you have the SRTM dataset in your Data list and it’s at the top.
  • Open the Layer Settings and activate the Palette radio toggle.
  • Use either the [+] button or the editor icon (pencil) to select or enter colors black and green to represent the min and max data values for the selected band (000000, 32cd32).
  • Click the apply button and then adjust the min and max Range values until you are satisfied with the stretch for your region of interest.


Additional colors can be added to the palette. Try visualizing SRTM elevation with this palette:

000004, 2c105c, 711f81, b63679, ee605e, fdae78, fcfdbf, fdffe5

  • Copy and paste the above palette color list into the Palette Editor (pencil icon).
  • Apply the changes and then adjust the min and max Range values until you are satisfied with the stretch for your region of interest.


Visualizing change over time

One of the interesting things you can do in EE Explorer is visualize change over time. To do this, you will need to add the same dataset to your Workspace as two separate layers and then set them to show different time slices. The example below will show you how to visualize the rapid urban expansion of Las Vegas, Nevada.

  • Go to your Workspace, search for “Las Vegas, NV” in the search bar, and zoom to it.
  • Remove (or turn off) all the layers from your Data list.
  • Add the Landsat 5 TM Collection 1 Tier 1 32-Day TOA Reflectance Composite dataset to your Workspace.
  • Add it again as a second identical layer.
  • Using Layer Settings, set the top one to: Aug 13, 2011 - Sept 14, 2011, and the bottom one to: Aug 13, 1986 - Sep 14, 1986.
  • Toggle the visibility of the top layer on and off, and you will see the growth of the city over the 26-year period.



As you can see, when looking between the two images above, the 2011 image has far greater urban area than the 1986 image. Note that in this example I’ve set the display to a false color representation of Landsat 5 bands 5, 4, 2 / red, green, blue, respectively. This representation enhances the contrast between vegetation and barren desert.

The following graphic is a practical example of an application of date-to-date comparison. Here, two screen clips from EE Explorer were merged together and annotated to convey information about land cover change recorded by Landsat. This example shows expansion of an open pit coal mine and forest clear cutting near Elkford, British Columbia, Canada from 1984 to 2011.


Things to look out for

The following are a list of possibly unintuitive behaviors and characteristics of EE Explorer and datasets that you should be aware of.

  • Landsat imagery cannot be viewed globally; you must zoom in a few levels. If the image isn’t appearing on the map, look for the yellow bar at the top of the page indicating that you need to zoom in.
  • Each dataset comes from a satellite that functions (or functioned) over a specific time frame. Landsat 5, for example, stopped sending data in November, 2011; Landsat 8 began sending data in June, 2013.
  • Different satellites visit the same spot on the Earth with different frequency. MODIS imagery covers almost the entire globe every day. Landsat only visits the same spot every 16 days. In addition, there are places on Earth that are missing data for some satellites. For instance, Landsat 5 data are missing in many places due to acquisition tasking and onboard storage limitations.
  • Missing data are rendered as transparent - you can see through to the Google Maps base layer.
  • Some places are cloudy all the time, and accordingly, have no clear imagery. Certain datasets will show these areas as having missing data.
  • Landsat 7 had a partial failure of its imaging system on May 31, 2003, which results in long stripes of missing data in every Landsat 7 image taken since then, as visible in the image below. These can be avoided by using a 32-day composite dataset, which combines multiple images over time and therefore can fill in the missing gaps.


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