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Features

Benefits

Single point of access

The Earth on Demand imagery portal allows access to a variety of EO data sources, so you only have one place to go to build your query

Up-to-date imagery

Because our data refresh is limited only by the underlying satellite, we can offer near-real-time (< 5 day old) data across the globe

Widely usable

With multiple output formats, we can help everyone from business analysts to data scientists to unlock insights from EO data

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Get to Know the Product

What can I do with satellite image data?

How do I use Earth OnDemand?

How do I search for imagery?

How do I know which platform/satellite operator to choose?

How do I download a single natural color image?

How can I export my full query results into a CSV file or Jupyter notebook?

How can I analyze this data using Python?

What can I do with satellite image data?

Earth Observing satellite image data is useful for a variety of purposes, from viewing the most recent satellite picture of your hometown, to observing how a glacier changes over time, to making economic measurements by estimating oil inventories and counting cars, to combating climate change through scientific analysis.

Experienced remote sensing scientists understand that the spectral richness and massive scale of this data make it a treasure trove for uncovering insights. However, this imagery is accessible and applicable to anyone, and each individual can explore the Earth's surface and how it changes over time according to their own inspiration.

With Earth OnDemand, we set out to serve everyone who wants to better understand our planet. We offer support for experienced scientists via our Jupyter Notebook export, and we provide natural color images for any user inspired to observe our changing planet.

How do I use Earth OnDemand?

Screenshot of Earth OnDemand platform showing preview tiles and details of data selections after search query

How do I know which platform/satellite operator to choose?

Earth OnDemand provides access to the latest imagery and historical archives of multiple satellite platforms and operators. For our current beta, we offer access to the below public (free) providers:

Satellite Operated By Launch Year Resolution Revisit Rate Bands
MODIS NASA 2002 As fine as 500m 1-2 days 7
Landsat NASA, USGS 2013 As fine as 15m 10-20 days 11
Sentinel ESA 2015 As fine as 10m 2-10 days 12

Each platform offers unique advantages. For some analyses, well-calibrated spectral data (e.g. measurements including visible and non-visible light) can be the most useful; in this case MODIS would likely be the best candidate. In other analyses, Sentinel’s granular 10m resolution could be best. Thus, the choice of provider will ultimately depend on the type of analysis or exploration being performed. In these cases, cost is not a factor, as this data (both current imagery and historical archives) are publicly available.

How do I download a single natural color image?

Screenshot of Earth OnDemand platform showing preview tiles and details of data selections after search query

After performing a search, click on the footprint (and satellite platform) of the scene in which you are interested. From the list of scenes that appear:

  1. Get more details of an image by clicking the More Info button.
  2. Click the Download button to save a JPEG image.
  3. View a larger version in a new browser window by clicking on the thumbnail image.

How can I export my full query results into a CSV file or Jupyter notebook?

Screenshot of Earth OnDemand platform showing preview tiles and details of data selections after search query
  1. Click on the CSV download button. This will return an indexed directory of links to the band-specific images for the dates, times, and Area of Interest for your search.
  2. Click on the Jupyter Notebook download button. This will download a notebook pre-populated with code to request your queried imagery from the selected providers.

How can I analyze this data using Python?

  1. Click on the Jupyter Notebook download button (see image above). This will download a notebook pre-populated with code that will:
    1. Submit your original query to the Earth OnDemand REST API.
    2. Download the results to a CSV file.
    3. Create a Pandas DataFrame of your query results.
  2. Step through example tasks in our "Getting Started Notebook".
  3. Learn how to build your own EO workflows in Python with our "RasterFrames Documentation".
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