topherhaddad

TDI (time delay integration)

A little more detail that we didn't get into in the post. The 3-CMG control mode we first uploaded was v1. We had plans to improve the agility with later versions. In v1, we didn't have quite enough rate to match earth's, even with max TDI. We called it Banana Scanning. Kind of like slipping over the earth.

Net - the CMG imagery we captured had a few pixels of along-track smear in it. Which would have been removed in post-processing if we had made it through focus cal.

Our business model is focused on providing VLEO systems (satellites, buses, and full mission services). But future customers may be provide image services :)

Thank you!

1. The proximity improves performance: - Range^2: imaging, other sensing, closing link budgets (data you're sending or signals you're sensing) - Range^3: SAR - Range^4: Active sensing (lidar, radar, etc) - Speed: Comms latency, time to intercept - If you can build systems fast/cheap, this physics unlock creates a new paradigm for system architectures (compared to traditional cost/schedule/performance tradeoffs)

2. Diversification is important for resilience/deterrence - Drag self cleans debris - It's below the belts where radiation gets trapped after a nuclear detonation. Makes for not only a survivable orbit, but one with assured reconstitution

Yes, exactly. Space safety :)

Ultimately it's about the ballistic coefficient. You want high mass, low cross-sectional area, and low drag coefficient (Cd). With propulsion for station-keeping, it's challenging to capture the VLEO benefits with a regular cubesat. That said, there are VLEO architectures different than Clarity that make sense for other mission areas.

Yes it's a big contributor. The atmosphere in VLEO behaves as free molecular flow instead of a continuous fluid.

The lesson there - dig multiple levels deep in supply chain

Alas.. the speed & resources of a startup. But we're learning.

Clarity is designed for a GSD (ground sample distance) of 10 cm. Generally the industry uses resolution<>GSD interchangeably. Agree it's not the true definition of resolution. But I'd argue the diffraction limit is an incomplete metric as well, like how spatial sampling is balanced with other MTF contributors (e.g. jitter/smear). For complete metrics, we like 1) NIIRS or 2) % contrast for a given object size on the ground (i.e. system MTF translated to ground units, not image-space units).

The main performance goal for us was NIIRS 7, and we decomposed GSD/MTF/SNR contributors optimized for affordability when we architected the system

Moving fast to make launch, we had missed a harness checkout step that would’ve caught a missing comms connection into an FPGA, and it was masked because our redundant comms channel made everything look nominal.

On orbit, we fixed it by pushing an FPGA update and adding software-level switching between the channels to prove the update applied and isolate the hardware path — which worked. Broader lesson, it is possible to design a sw stack capable of making updates to traditionally burned-in components.

Founder/CEO of Albedo here. We published a detailed write-up of our first VLEO satellite mission (Clarity-1) — including imagery, what worked, what broke, and learnings we're taking forward. Happy to answer questions.

https://albedo.com/post/clarity-1-what-worked-and-where-we-g...

Great question. Orbit Fab plans to launch fuel depots into space, somewhat aligned with orbits of their customers. For most cubesat/smallsat constellations, it probably does make more sense to just launch a new fleet. Our satellites will be refrigerator size and a bit pricier, so it makes more sense to refuel and extend the life. Yeah check out our careers page!

Great question. The 3 tiers correspond to how much imagery is ordered per year, the more you order the cheaper the per unit price is. The "minimum order" corresponds to the area size on the ground for a single tasking order (a single image).

The comparison shot was taken with a drone at an altitude that corresponds to our 10cm resolution. The 30cm version was obtained through downsampling the 10cm image accordingly. I wish we had a real 10cm satellite image to use, but our satellites won't be on orbit until 2024, so we are using a drone to show examples in the meantime.

I don't have any papers offhand, but the wikipedia page on microbolometers is great. Traditional sensors for thermal imaging are made of materials like InSb and HgCdTe, which require cooling to cryogenic temperatures in order to limit dark noise. These types of sensors are similar to visible sensors where an electron is generated for each incident photon. Microbolometers operate fundamentally differently, where electrical resistance in response to temperature changes. While most space thermal sensors today still use traditional materials, most terrestrial thermal cameras (night-vision, thermal drones) use microbolometers when imaging in LWIR.

I totally agree the 9x is somewhat marketing speak, but I do think that the way GSD has historically been characterized by the 1-dimensional measurement does not do spatial resolution improvements enough justice. Electro-optical imaging systems are analogous to any digital sampling system. If you were sampling a sine wave at 90 Hz instead of 10 Hz, that's clearly a 9x improvement as you end up with 9x more samples. The same is true for imaging, you're digitally sampling an object with discrete pixels (of course there's more to overall image quality than just spatial resolution). Another side note is that the government NIIRS imagery rating system captures this squared effect through the log2(GSD) term in the equation. Photographers also think more about it in 2D, as they characterize resolution in total Megapixels in the image. Ok I'm done, I'll get off my resolution soapbox :)

It is a raw drone image. I probably should have picked a different option, as this was collected just after sunset, which gives a nice uniform lighting but also leads to more noise and some of those artifacts you mention.

The resolution improvement has nothing to do with software (although there are super-resolution methods to improve it). It has to do with both flying very low as well as building a larger telescope than normal. While the satellites will still be much smaller than the traditional approach to capturing 10cm resolution, they will be larger than the new space smallsat movement we've been seeing the last few years.

Exactly. Lots of trade-offs in remote sensing. We're bullish on SAR to clean up on monitoring applications, due to the ability to see through clouds and at night. As that plays out, high res optical will be even more important for context when SAR detects some sort of change (then optical can be used to see what caused the change).

Glad to hear that! We have details on our coverage and specs here, https://www.albedo.space/product-specs

There is a ton of effort currently being put into the on-orbit servicing world. Orbit Fab is leading the way on providing the fuel depots, and a number of other companies are developing the robotics required to send servicing satellites in between Orbit Fab depots and the satellites they are filling up. Worst case, if the refueling is still a few years out by the time we need it, we would increase our orbit to extend our satellite lifetime (at the cost of lower spatial resolution).

Great points! The GPS analogy is definitely not 1-to-1. Our main point with the analogy is this: when GPS technology was developed, there was no foresight of applications like Tinder, Uber, Pokemon Go, which all would not be possible without GPS. So in that sense, we expect that if we are able to push satellite imagery in the direction of becoming a commodity, this will unlock applications we have no foresight of today. SVB & Space Capital released a great report on this idea called The GPS Playbook

We appreciate you bringing this up - we’re acutely aware of the privacy implications and potential for abuse/misuse. There isn’t a straightforward or easy answer to this, but we want to be ahead of the curve and not repeat the mistakes that other companies have made in the past. We expect this to be an on-going, evolving issue over time, but also something we want to start thinking about from day one. As far as practical steps, we’ll be approving new customers on a case-by-case basis, building our robust internal tools to find bad actors, as well as the obvious measures of adding punitive clauses to our terms and conditions. We know that’s not enough and we’d love to hear any other ideas folks have on this. The positive applications related to climate and human rights issues are exciting, but we realize we have to properly address privacy and misuse prevention before we can start to open those former conversations. In terms of personal privacy, 10cm resolution does enable one to identify a person (you can detect people in good sun conditions, but not identify).

Thanks for the suggestion! We are currently working with some partner customers on featuring their applications on our site.

Quick definition of how revisit rate is used across the industry: it denotes how often a satellite has the opportunity to image an area. So with our full constellation, we'll have a revisit rate of 2-3 times per day for latitudes < 60 deg N/S (info on the website), meaning you could put a tasking order over a certain area for that frequency. Although we expect most of our applications to need something more like a weekly cadence for image collects.

100p! Human rights issues is an area where we think higher resolution will be super helpful, and we are planning to make our archive data freely available for these types of applications as well as large discounts on tasking.

Great observation! One of the biggest challenges for high resolution satellite imaging, even beyond the optics, is getting all those pixels down. Fortunately, the ground station infrastructure has blown up recently with Big Tech offerings like AWS Ground Station and Azure Orbital, plus legacy providers like KSAT, so there is plenty of access to get data down through Ka-band.

Yeah great point, there are a number of agriculture applications that have no need for this level of spatial resolution. Certain high value crops only use drones today due to the resolution, so we'll be able to support those applications. Additionally, there's ways to combine visible + thermal to evaluate water crop stress to detect potential irrigation issues or improvements.

Feel free to fill out the Contact Us form on the website and we'll keep you updated as we get closer towards commercial release!

It's a good question, and I while I obviously have no definitive information on other satellite companies, I will say that spatial resolution isn't everything. The higher you go, you give up temporal resolution and area coverage, which is key for Planet's monitoring mission. There's also plenty of other phenomenologies to go after - for example Blacksky announced their next-gen constellation will have SWIR. And for us, the thermal is really only possible since we are already capturing such high resolution visible (due to the long wavelength of LWIR).

Thanks! Our initial constellation will be 24 satellites, which will enable 2-3 revisits per day to areas of interest.

We used a drone to capture this image at our representative resolution (10cm), but it only captures in JPEG so there could be compression artifacts from that. The image on the right is a 1/3 downsampled version to show 30cm resolution.

Al-bee-dough. Origin: it's a term for how much light is reflected off of a surface (the average for earth is 30%)

The comparison shot was taken with a drone at an altitude that corresponds to our 10cm resolution. The 30cm version was obtained through downsampling the 10cm image.

Other companies could potentially drive towards higher resolution, but spatial resolution isn't everything. You give up temporal resolution (revisit rates) and overall area coverage, so we expect some companies to continue to cater to the lower resolution type applications.

It is rather ambiguous, apologies. Imaging is a 2-dimensional measurement, so spatial resolution improvements follow a squared nature. Our GSD will be 10cm, so we arrive at 9x by (30^2/10^2). Said another way, nine 10cm pixels will fit in one 30cm pixel. The 9x refers to the visible imagery, whereas our thermal (LWIR) GSD will be 2m, and the best available today is 70m.

For thermal, we're only doing broadband 7.5um - 13.5um. You're correct in that direct emissions measurements is best made with SWIR. However, there are applications where heat signatures can be used to calculate emissions. For example, if you know the surface material and fuel type of a power plant, you can calculate carbon emission from the heat signature in the thermal image. Climate Trace will use our data for this.