It is that time of the year when a few try to predict what will happen in the next 12 months, which ends up being wrong most of the time. I am going to try and wear that ‘pretend foreteller’ hat to imagine what might happen in EO in 2023. Let’s roll!

Note: I would have loved to touch on more topics, which did not make this final list, such as the evolving role of the public sector in EO, the continued dominance of the defense sector in EO, the lack of growth of commercial weather data from space and more. But, that’s why we have social media. You will certainly hear from me on these subjects, if you follow me on LinkedIn or Twitter.

Three Overarching Trends

1. More Climate and Biodiversity Narratives 🌍

This one is quite predictable and frankly, inevitable. As climate and biodiversity crisis move up the social, political and economic agendas of nations, so will the application of Earth observation (EO) across all of the narratives and sub-narratives of these two umbrella terms.

Whether you are looking at an intergovernmental level like the Global Stocktake of the Paris Agreement for tracking global emission goals, or at an enterprise level for climate risk disclosures and biodiversity risk disclosures or even at a consumer level for finding property risk before making an investment, EO has a fundamental role to play (but it will most likely stay in the background).

While much remains to be done, especially in translating EO into insights for policy implementation and moving the needle with data fusion, I believe that the demand for monitoring, measuring and reporting much of the climate and biodiversity data needed will help drive adoption and chart the way forward for EO in 2023. And, I expect those narratives to be equally spread across the five segments of EO (see below), but, my focus will be on how the ‘Intelligence’ layer evolves, the closest of the three that leads to action and impact.

2. Horizontal and Vertical Consolidation ↕️ 💸 ↔️

You would have probably heard this a dozen times: consolidation is inevitable. So, instead of repeating the same thing, I am going to try and go one step deeper. I think we will probably see two types of consolidation: horizontal and vertical:

Horizontal consolidation, when two similar type of businesses get together - for example, an EO sensor company acquiring another one due to possible synergies and growth potential (see news about Maxar acquiring Aurora Insights).
Vertical consolidation, when a user acquires one of its suppliers to become self-sufficient with that capability - for example, a market leader in a vertical acquiring a downstream, analytics company (like when Land O'Lakes acquired Geosys back in 2013, before selling them back) or when a EO data company acquires an analytics company to double down on a specific vertical (like when Planet acquired Vandersat in 2021).

Although, consolidation might be a strong word, and could be less likely given the macroeconomic situation, in some cases, we might see baby steps towards an potential consolidation - a strategic investment or a strategic partnership. See #8 for more thoughts on this.

3. Continuing Sovereign Earth Observation Dynamics 🚩

After the year we have had, in which, Australia, UAE, Albania, Ukraine, Spain, Norway and Netherlands and several others took steps towards owning Earth observation capabilities, you would think we are done with this trend. But, I wouldn’t be so sure. Just this month, we saw Kuwait and the region of Catalonia launch their first EO satellite, with several other firsts coming up this year. Follow-on national EO missions from national space agencies are also expected to continue (see upcoming launch of Thailand’s THEOS).

As the last major EO news from 2022 (Poland acquiring two EO satellites from Airbus) showed, there is scope for a lot more to come. I seem so certain not just because of the evolving geopolitics and the changing climate that increases willingness to spend on EO, but also due to the increasing availability of off-the-shelf solutions, whether it is a high-resolution SAR instrument or an electro-optical sensor or more innovatively, lease satellites already on orbit or just provide the payload and outsource the space segment.

For the next five predictions, I am going to use my ‘3A’s of EO’ framework from my last post to add some structure. It is quite straightforward, but you can read more about the 3A’s here!

Two Predictions on EO ‘Availability’

Let me just show you one more figure, before we continue. It is not because I want to repurpose my old content and make you want to read those pieces, but I am going to be using some generic terms like, ‘data’, ‘platforms’, ‘analytics’, ‘insights’ etc. which might mean different things for different people. So, just so we are all on the same page here!

4. More Launches of New Sensors and Capabilities 🛰️

As always, we have an exciting year ahead, when it comes to showcasing the capabilities of the ‘Data’ layer. However, expect funding for that layer to be on hold as investors look for market validation for the already well-funded EO companies. I predict funding to be more concentrated on companies that scale in the ‘Analytics’ and ‘Insights’ layers. And, last but not least, there will be numerous companies in the ‘Application’ layer that will be funded, but we will never hear about them - after all, those are companies with products that just happen to use satellite data among other technologies for solving a specific problem, so they might not even be considered part of the EO market.

If you are curious what EO missions are coming up in 2023, here’s a non-exhaustive list of some that I am looking forward to, in no particular order:

TEMPO (NASA) to measure air pollution over North America;
TROPICS (NASA) to measure precipitation and storms over the tropics;
EarthCARE* (ESA/JAXA) to observe clouds & aerosols, with 4 instruments - an atmospheric lidar, a cloud radar, an imager and a radiometer;
Sentinel-1C* (ESA/EU) adding to the Sentinel-1 constellation of SAR satellites;
ALOS-3 (JAXA) with an optical imager and ALOS-4 (JAXA) with an L-band SAR instrument;
THEOS-2 (GISTDA), Thailand’s second Earth observation satellite;

Some first satellite launches including:

Legion (Maxar) and Pelican (Planet) with very high-resolution electro-optical sensors (30 cm);
Satellite Vu 1 (SatelliteVu) with thermal infrared instruments;
GHOSt (Orbital Sidekick), HySpec (HySpecIQ), Wyvern, and Tanager (Planet) with hyperspectral sensors;
Tomorrow-R1, R2 (Tomorrow.io) with precipitation radars;
Xplore with multiple sensors and GHGSat-C10 (GHGSat) for CO2 monitoring.

And, several follow-on missions for the current constellations of EO companies and startups.**

*The launch in 2023 might depend on how soon Vega-C comes back into action

** Includes many companies within the ‘Data’ layer of this market landscape, which does not include this one from China.

5. Cracking the Analytics Layer (on orbit & on ground) 📊

The end of last year saw several announcements related to on-orbit processing of EO data - from AWS showcasing their experiment to platforms like SkyWatch extending their offerings. On the other end, we had companies like Ursa Space Systems double down on data fusion to derive use-case specific analytics.

I see these developments as essentially just two different ways of trying to solve one problem - identify use cases that can scale and derive analytics on-demand.

The former strategy, cracking the analytics layer on orbit, is the lighter version of analytics enabling object detection and monitoring changes to those objects by processing data at the edge (typically, single source data)
The latter strategy, cracking the analytics layer on ground, is the heavier version of analytics enabling more effective object detection and change monitoring by processing data on ground (typically, multi-source data).

We are likely to see more experiments, announcements and partnerships in an attempt to crack the analytics layer, whether it is through the former or the latter strategy or a mix of both. The ‘Analytics’ layer is actually the only one of the five layers of EO, where we haven’t seen any large scale success yet. Is it coming?

6. Platforms Inching Towards Analysis Ready Data 🗺️

I am going to bring in my biased opinion here, and use that to make a pretty strong prediction. I see two types of platforms in the future of EO:

The first category, which I call Data Platforms, consists of the ones we already know: the data aggregators, who bring multi-sensor, multi-modal data together for users to access (marketplaces) and process (platforms) with a computing environment, typically aimed at users with pretty strong foundations of EO.
The second category, which I call Data Product Platforms, are the ones which will aim to provide ‘analysis-ready data’ (the commercial definition of which is yet to be defined) abstracting the remote sensing layer away from users, yet still provide data products derived from EO, typically aimed at users with limited knowledge of EO.

In 2023, we might start seeing more developments in the second category. To make more sense of Data Product Platforms, let’s use Planet’s Planetary Variables as an example - say soil moisture, forest carbon or land temperature. Now, imagine a platform that provides access to such commercially useful data products useful for many use cases, derived from multi-sensor, multi-modal EO data. I would imagine them to be not a bunch of random data products that are possible with EO, but carefully assembled to fit market requirements.

One Prediction on EO ‘Adoption’

7. Towards Strategic Adoption of EO 📈

I should have probably allocated more than one bullet point for adoption, but, here’s one prediction about adoption of EO for 2023: EO will start to become more strategic than operational for some companies.

While there will be a part of adoption that will happen inevitably simply because of the value offered by EO (like the $ it saves or the data gap it fills) , I expect some adoption for reasons that are beyond the fundamental benefits offered by EO. Companies would be less likely to adopt a technology that every competitor of theirs will have access to - the same data, the same algorithms or the same products. Instead, they would want to develop competitive strengths, derived from EO. This might mean looking into developing proprietary sensors, or acquiring proprietary datasets that can used to derive exclusive insights or simply integrating EO into their long-term data strategy.

Executing on these approaches does not necessarily mean that the end-user companies will start launching their own satellites (they might), but they will more likely might make strategic investments in EO companies or form exclusive partnerships. They do not have to make this decision alone - the growth of the ‘advisory service layer’ in EO this year will be their guide. And, I expect, quite a bit of this to happen over 2023.

One Wishful Prediction about EO ‘Awareness’

8. More Purposeful Communication 🗣️

This is just anecdotal evidence, but we have started seeing an increasing use of satellite data in mainstream media. Whether it is a consequence of the changing geopolitical and environmental situations, or just a correlation with increasing availability and easier accessibility of satellite data, we are more likely to see widespread usage of satellite imagery or more importantly, insights gathered from satellite data (which is good news).

But, my wishful prediction for 2023, is communication about EO gets more purposeful, especially as the need for commercial adoption grows. I have written about this topic before (#7), but what I hope happens this year is we start becoming earnest in our efforts to evangelise the use of satellite data, keeping the end-users ‘job to be done’ in mind. I am convinced that the future of EO lies in our ability to learn the impact of EO for the end-user and build accordingly.

As we continue our efforts towards educating the customer about what EO can do, let’s try and be upfront about what it also cannot do. As several companies invest in their marketing efforts to communicate the capabilities of their technology or product, let’s remember that is not about a sensor, an algorithm or even the product, it is about how much money it can save for the user and what action it can lead to. Let’s make that happen, together!

Until next time,

Aravind.

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