TerraWatch Essentials · · 6 min read

Last Week in Earth Observation: October 16, 2023

State of SPACs, impact of edge computing on the Earth observation value chain, monitoring crop nutrients with satellite data and more.

Welcome to a new edition of ‘Last Week in Earth Observation, containing a summary of major developments in EO from last week and some exclusive analysis and insights from TerraWatch.

In this edition: State of SPACs, the impact of edge computing on the Earth observation value chain, monitoring crop nutrients with satellite data and more.


Four Curated Things

Major developments in EO from the past week


1. Contractual Stuff: Funding, Contracts and Deals 💰

Funding

Financials

Credit: Michael Sheetz / CNBC

2. Strategic Stuff: Partnerships and Announcements 📈

Partnerships

Announcements

Credit: Copernicus

3. Interesting Stuff: More News 🗞️


4. Click-Worthy Stuff: Check These Out 🔗


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One Discussion Point

Analysis, thoughts, and insights on developments in EO


5. Impact of Edge Computing on the EO Value Chain

What impact can edge computing (or on-board processing) have on the EO industry, and more specifically, how does it affect the EO value chain?

If you have read anything from TerraWatch before, you know that I segment the EO Operating Stack into 5 segments: Data, Platform, Analytics, Insights and Applications. Edge computing might have some interesting dynamics on the Platform layer, but its impact on the Analytics layer is perhaps more fascinating.

As a reminder, the Analytics layer is the part of the EO value chain, where data is converted into useful information, sometimes by integrating other sources of data. However, note that the Analytics layer does not inform, it only translates. You might not be able to make direct decisions with Analytics, as you might need to contextualise the information. Some examples of Analytics are cloud detection, vessel identification, building detection, crop classification etc. As you see, Analytics is all about converting imagery on pixels into some information, but it is not an actionable insight.

And that is what edge computing brings to the table - the ability to process data onboard the satellite, as it is being taken, in order to convert this data into some form of useful information. Note that edge computing might not necessarily provide actionable Insights, nor can it become a usable Application. My thesis is that edge computing helps move the Analytics layer closer to the orbit, but not completely away from the ground, as the figure represents below.

As an example, edge computing may enable the detection of clouds in orbit, but might not succeed in detecting all clouds in the image from the start. It may enable the detection of vessels in the sea, but may not provide a 100 per cent accuracy to begin with. And, the power of edge computing may not be enough to detect objects that are inherently harder to detect scalably (like the different types of trees), especially objects that require a lot of training data. The differences between traditional AI (on the ground) vs. edge AI (in orbit) might have limitations on how much information it can derive. At least as long as we successfully build data centers in space, where training data can be stored.

So, what edge computing really does to the EO Operating Stack is it literally shakes things up a bit - moving the Analytics layer closer to orbit. At least for starters, some simple forms of Analytics like cloud detection and vessel detection can be “outsourced” to be performed on-orbit, while the more complex forms of Analytics such as building detection and crop identification might be harder to execute with limited training data available onboard the satellite.

For more on edge computing, check out the exclusive deep dive on the topic, which is accessible to paid subscribers. Not a subscriber? You can do it now!


Scene from Space

One visual leveraging EO


6. Monitoring Crop Nutrients with Satellite Data

The following image shows the results from research into the potential of using satellites to monitor crop nutrients over large areas. Data from the Sentinel-2 mission and the Italian Prisma mission were used to measure the nutritional content of staple crops, particularly potassium (K), phosphorous (P), magnesium (Mg) and iron (Fe), in soybean and wheat.

So what? Integrating insights from EO can enable farmers to intervene with fertilisers or other agricultural practices before they actually harvest.

Credit: ESA

PS. If you were not lucky enough to see the Solar eclipse or if you are not living in one of the places where it was visible (like me), then you might want to check out this cool animation, showing the sunrise, the eclipse shadow and the sunset - courtesy of NOAA’s GOES-East satellite.

Credit: National Weather Service

Until next time,

Aravind.

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