Government Satellite Data and Its Role in Advancing Global Development

“. . .to capture the greatest usefulness from EO, our community is continually challenged to make this information much more accessible and ready for analysis, enabling data-driven development.”

Understanding our world and the interconnectedness of the natural and built environment is a great challenge to global development professionals as well as scientists and technologists. The role that Earth observation (EO) plays in this understanding is difficult to put in terms of economic value. However, to capture the greatest use from EO, our community is continually challenged to make this information much more accessible and ready for analysis, enabling data-driven development.

In March 2018, the Committee on Earth Observations Satellites and the European Space Agency (ESA) published “SATELLITE EARTH OBSERVATIONS IN SUPPORT OF THE SUSTAINABLE DEVELOPMENT GOALS.” This publication, also known as the EO Handbook, estimates that EO data plays a highly valuable role in most of the Sustainable Development Goals (SDGs) and around a quarter of all the targets. Without this high-quality and accessible data, we would struggle in many cases to quantify the majority of them.

Open Data: A Key EO Trend

As discussed in a previous article, some EO satellites are fully supported by national governments, some are the result of joint industry-government funding, while venture capital backs others. In this article — which is part of an on-going series on the value of EO data — we focus on government satellites and open data. While there is a long list of governments that operate satellites, only a few make their data open, that is, that the “data can be freely used, re-used and redistributed by anyone.” That said, the Group on Earth Observations (GEO), which is devoted to advocating governments to make their data free and open, has 100 national members and offers more than 400 million EO resources.

Click here for more information on governments providing open satellite data.

More than 10 years ago, the United States Geological Survey (USGS) offered the ability to download orthorectified Landsat 7 Enhanced Thematic Mapper (ETM) data at no cost. This significant policy change ultimately led to all archival Landsat data being released as open data. The result has been documented as a stunning return on investment. In 2014, based on a European Union (EU) decision, ESA also adopted this approach of free and open data from the outset when they launched Sentinel 1-A. ESA has made all current and future satellite missions, as part of the Copernicus program, reflect their open data policy. The EU funds and manages ESA and the Copernicus program.

In recent years, thanks in part to cloud computing, this data has become more readily accessible to a wider audience. To give an idea of the scale, over 15 Petabytes of data from Sentinel 2 has already been downloaded by users worldwide since the satellites launched in 2015 and 2017.

There are at least 20[1] government satellites that are currently operational and that provide both imagery and non-imagery EO data without restrictions. This article, however, spotlights Landsat and Copernicus, the best two examples of government satellite programs that have positively impacted global development as result of their free and open data policy. More on these programs are provided below:


The Landsat series is the longest continuous space-based open record of Earth’s land in existence. Landsat 1 was launched on 23 July 1972. As a result of that satellite and subsequent missions, we now have over 40 years of Landsat data that are accessible via the archive. Landsat 7 Enhanced Thematic Mapper + is still active even though it suffered the loss of its scan line connector in 2003. Landsat 8 is currently fully functioning. Landsat 9 is fully funded and planned for a 2020 launch, and Landsat 10 is planned in 2027–28. The longest continuous space-based record is seemingly set well into the coming decades, providing the assurance that we can rely on this important science record for decades to come.

Landsat 8 is a multispectral satellite. It records data using its Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS). The OLI records light reflected in blue, green and red (Band 2,3,4) as well as a coastal band (Band 1), near infrared (Band 5), two shortwave infrared bands (6&7), a panchromatic band (Band 8) and a cirrus band (Band 9). Bands 10 and 11 are from the TIRS and record measurements of temperature at the surface. The OLI bands are all available at 30m spatial resolution, meaning that 1 pixel captured relates to 30m x 30m on the ground. This can be enhanced using band 8 to sharpen the imagery up to 15m x 15m representative pixels. This is a common technique used to increase the spatial resolution of multispectral satellites.


The space component of the ESA-managed Copernicus mission comprises a series of satellites known as Sentinels, and a ground segment, which help enable the access to the data. There is also an in-situ component to Copernicus that utilizes ground-based sensors. Currently, the Sentinel satellites in orbit are Sentinel 1A & B, Sentinel 2A & B, Sentinel 3A & 3B and Sentinel 5P.

Table 1: Sentinels currently in orbit.

Sentinels 2A and 2B are similar multispectral satellites to Landsat, only offering more spectral bands and a greater spatial resolution. Sentinels 1A and 1B are arguably two of the most important satellites in orbit today. They are a pair of C-Band Synthetic Aperture Radar (SAR) Satellites. They offer an unprecedented revisit rate and, being SAR satellites, they are not impacted by clouds, meaning the data can be reliably used in all but the most severe rain events. Applications for Sentinel 1 include sea ice monitoring, landcover mapping, and surface deformation and motion. It is also especially helpful in mapping areas that might have suffered an extreme event, for example being used to map flooding as a result of Hurricane Harvey.

“These are exciting times; With the speed of innovation driving new satellite constellations, cloud computing that allows us to store, access and analyze this data at a fraction of the previous costs, and the emergence of machine learning and artificial intelligence applied to Earth observation analysis, we can improve the richness of the data and its resulting insights.”

Landsat, Copernicus, and their Impact

These open satellite datasets offer global coverage with a high revisit time. The datasets unlock the world providing pixels that deliver detailed information, which at its best can show 10m spatial resolution with optical data. Combining that with an unrivalled archive of information and a planned continuity of service means that this data can be relied upon. Two examples of the scale and reach that these open government datasets are described in the following paragraphs.

The first example is monitoring the extent of global forest cover. Goal 15 of the UN’s SDG’s is to “Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss.” One of the indicators set for this goal is a measure of “Forest area as a proportion of total land area.” Without the use of a global high-quality EO dataset, this would be a logistical nightmare of data gathering that would likely lack consistency across the globe. Producing high-resolution maps of global forest change is what Hansen et al. (2013) set out to do with the Landsat archive. This type of project had never been done before; the data were either too coarse or the computer processing times far too large, and before the open data policy would have been very expensive. With the help of Google Earth Engine, all the images were processed in a few days, as opposed to an estimated 15 years. The Global Forest Watch map is a useful resource that enables anyone to analyse worldwide forestry cover changes, among other measures. Without the open access to the Landsat archive, this would not have been possible.

The second example is the Copernicus global land cover product, which has been delivering high-quality EO derived products since 2014. Global products, including Landcover, Burnt Area, Leaf Area Indices and Soil Water Index, are all supplied via a portal. The Sri Lankan authorities have made use of the Soil Water Index to measure in near real-time the impact that drought and floods have on crops, especially rice. Products derived from EO data allow non-specialists immediate access to this data. As we move towards more analysis ready data (ARD), and the increased availability of EO derived products and services like the global land cover product, the case for using this data to support decision-making on the ground in a timely fashion becomes even more compelling.

The above examples undoubtedly suggest that the benefit of providing open data outweigh the investments in satellites, which helps the world to understand the interconnectedness of the natural and built environment. These are exciting times; With the speed of innovation driving new satellite constellations, cloud computing that allows us to store, access and analyze this data at a fraction of the previous costs, and the emergence of machine learning and artificial intelligence applied to Earth observation analysis, we can improve the richness of the data and its resulting insights. The benefits of this innovation must certainly accrue to our pursuit of solutions for global development issues.

In our next installment of this series, we will review the tremendous progress and growth in the commercial EO data and solutions market.





Helping the global development community navigate the Machine Learning and Earth observation marketplace and innovations taking place.

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Anne Hale Miglarese

Anne Hale Miglarese

Founder & CEO of Radiant.Earth. Follow via @OurRadiantEarth

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