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Space technology is enabling advancement on Earth

Some of the most important, consequential, and, frankly, coolest new innovations on Earth are being driven by new technology up in space.

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Satellites and the images and data they produce have long been used for crucial scientific study and vital military operations. The launch of NASA’s Nimbus program in the 1960s heralded a new age of meteorology and weather forecasting, enabling scientists to achieve a revolutionary new understanding of this planet and how humans impact it. Around the same time, satellites also became part of an expanded American defense strategy, with the CIA’s Corona satellite program providing essential intelligence during the Cold War.

With breakthroughs that have made satellites both more powerful and cheaper to launch, they are now also powering remarkable advances in cutting-edge technologies here on Earth and out in space. Among their many invaluable contributions, satellite imaging is central to rapid advances in a wide range of industries and innovations, from autonomous vehicles and 5G networks to NASA’s ambitious Mars missions.

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It’s almost hard to believe, but it wasn’t all that long ago that people were unfolding big paper maps to plan road trips and figure out how to get from one place to another. Dashboard GPS technology changed driving forever, and over time, products like Google Maps and other digital navigation services have continued to improve the experience of navigating from behind the wheel.

For the most part, mapping out the Earth for these products has been an arduous task performed by special cars that are equipped with LiDAR sensors and drive around acquiring data block by block. They were a neat development when first introduced, but a fleet of cars has serious limitations — steering around paved streets means that they can only cover so much land and offer a limited amount of information, which is in turn only sporadically updated. As both the automotive industry and other tech sectors continue to advance and expand, though, far more precise and extensive maps are needed, which is where satellite imaging comes in.

Satellites that produce high definition and multispectral imagery as well as advanced geospatial analytics are driving new developments that make navigating easier, roads safer, and rides more available. GPS is enhanced by vastly more detailed and accurate maps, which are created by satellites’ ability to capture a location’s topography and its spatial context in exacting detail. The satellites are also able to cover far more territory and return to spots many times a day for much more accurate information.

Any app that requires a user’s location relies on mapping, and the more details available, the better an experience the app can offer. Rideshare services like Uber and Lyft utilize these more precise maps to help their drivers navigate and facilitate faster and easier passenger pick-ups and drop-offs; the maps expand the areas in which companies can operate, as well. Maxar Technologies, the industry leader in high definition satellite imaging, provides rideshare services with images and data to facilitate improved service and much larger innovations. (Read More: Source: Tech Chrunch)


Microsoft and NASA offer some ideas about how you could apply Python for space exploration

Microsoft has teamed up with NASA to create three project-based learning modules that teach entry-level coders how to use the Python programming language and machine-learning algorithms to explore space, classify space rocks and predict weather and rocket-launch delays.


Students need a Windows, Mac or Linux computer to complete the modules, which teach the basics of what a programming language is, how to use Microsoft’s Visual Studio Code (VS Code) code editor, install extensions for Python, and how to run a basic Jupyter Notebook within VS Code – some of the key ingredients to get started on a machine-learning project.


Microsoft’s learning modules don’t actually teach anything about how to code in Python but rather offer some ideas, focussing on NASA’s space exploration activities, to illustrate how Python could be used in space exploration.

It might suit students learning to code who need some ideas for how that knowledge could be applied to solving challenges NASA faces, or those considering programming to see how Python could be used.

The Introduction to Python for Space Exploration module contains eight units and offers background on NASA’s Artemis lunar exploration program, which aims to land the first woman and the next man on the moon by 2024.

It also details key technology behind the program, such as exploration ground systems, the space launch system, human landing systems, communication systems and more.

There’s not much information about how to learn Python in the first module, but it does explain how machines and robots used in lunar exploration give computer scientists and developers an important role, alongside astronauts and geologists. 

“Deciding how to program a robot to collect rock samples, collect metadata, and not disturb the sample area, is non-trivial, especially when you consider that developers can’t test the robots in a truly accurate environment before sending them on the mission,” it explains.

The second module, Classify space rocks by using Python and artificial intelligence, also has eight units and requires some “Python experience”. It details key data analysis and data visualization libraries for Python, such as PyTorch. Of course, Microsoft plugs its Azure AI services, too.

Again, there’s no real information about how to start programming in Python, but it explains how AI can be used to improve space rock research. For example, astronauts with a computer could take photos of rocks in space to quickly identify the type of rock it is.

The module for predicting rocket launch delays with machine learning explores what kinds of algorithms are more suitable for different types of analysis, such as classifying images, predicting values and generating recommendations. It also offers a high-level overview of training a machine-learning model.

While Microsoft’s NASA lesson doesn’t offer any actual lessons in Python programming, the company has previously released free video tutorials that do aim to learn Python. (Source:””)