Another analogy I use a lot: satellite imagery is like salt. The dish can have lots of ingredients (in a military context: HUMINT, OSINT, SIGINT, etc.) And the satellite imagery can make the whole dish. But you never want to consume it in isolation, that would be disgusting.
Forget the algorithm. They need to fix their customer service, their sales process. Customers want pixels, but they need basic services: simple and a predictable price. I want to give a location (pix+radius, four corners or whatever) and a delivery schedule (once a week etc). But when I try to buy that stuff I get package deals, "ask for a quote", and vague statements about times. That doesn't work. Normal customers, ie not intelligence agencies, don't want a drawn-out negotiation process. The first company that can provide a basic web interface for purchasing imagery quickly and piecemeal will win the market.
Top of the list for small customers are probably high-end real estate agents. They want to monitor their neighborhoods for houses that are under delayed construction or backyards/pools that are being neglected (sure signs of someone ready to sell).
Civil litigation attorneys: I want everything you have about this particular intersection. Cops: I want any images you have of this house between these dates. News agencies: There is a Russian ship on fire at X location. When can you get us an image? And a great many other small customers I cannot think of at the moment.
These guys seem to be doing what you're interested in from the ordering side at least (Perth, Australia startup now gone to North America too).
But they use plane based images, so anything in a warzone is out
I know satellites are getting cheaper but there are still limits to the cost of targeted image acquisition right? Is the price at which these customers are able and willing to pay enough to cover those costs?
For example it'd be a cool feature to check where my food delivery man is at in real time through satellite imaging but that can't possibly be a profitable use case.
Pixels are there anyway, and infinitely scalable - you can sell exact same pixels to infinite number of people.
So why not to make a very easy UX to extract the pixels of your choice as per customized timeline.
It almost sounds foolish not to do it.
This is the requirement. The timeline could be once a week, once a month or once a .. - the point is not frequency but predictability. With Google Earth, Open Source, et al there is no predictability, that's why they are not answer for THIS potential customer.
This is basically corporate surveillance and I’m not at all comfortable with it. If you changed ‘real estate agent’ to ‘large landlord company’, the public would find this exceptionally unpalatable.
That's not generally true in the United States. If you are on public property, you can take a photo of anything or anyone you can see. You do not need their permission.
There may be local laws that restrict this, but they are not the common case.
https://en.wikipedia.org/wiki/Photography_and_the_law#United...
More detail:
Do you think you have a reasonable expectation of privacy anywhere ?
Sorry, can't seem to find it on the net after a quick DDG
Market segmentation by ability to pay can mean cheaper imagery for a chunk of the market than a flat fee.
So for example non-SLA "once a week" might really mean "once a week except if any of these 4 million other things take precedence" and translate to intervals being skipped on a regular basis, photos being days or weeks old, etc. SLA'd once-a-week would really be once a week and not a second late, but truly prohibitively expensive.
I'm reminded of the early US telephone systems in the 60s and 70s around WWII etc where Important People could pick up a phone and always get a connection even if that booted off a few tens or hundreds of calls on a shared trunk in the call path. Satellite is like an order-of magnitude-worse version of that problem because of the associated eye-watering costs and subsequent plain old near-zero availability.
Or are we thinking of a satellite that can actually be targeted at things on demand - selling time or fuel?
Certainly that’s true with eg the petroleum industry, and big ag.
But this is a good problem. It's like saying "the problem with motors is that everyone who uses them has a niche use case" (submarines, cars, airplanes, industrial machinery...). Or that "the problem with microscopy is that everyone who wants it has a niche use case". And indeed it does! Microscopes for biologists are different to those for chemists, engineers, medical doctors, physicists, etc.
The concept of "space imagery" is extremely wide. It is natural that earth observation satellites become specialized. I wouldn't be surprised to see in the near future some "CH4" or "CO2" satellites that acquire light in a handful of extremely narrow particular bands on the short wave infrared spectrum that are useful only for observing plumes of these gases. Right now, people use hyperspectral imagers (which have a dense sampling of some parts of the spectrum) and throw away most of the image data.
What you don't do is presume that you know everything about how people want to use motors, and offer a subscription to a design service that does all of their engineering design for them, as a way to sell your motors.
The false assumption I deal with that drives me insane with so many individuals is that everyone thinks their specialized use case is a small variation on the major use case that already benefits from economies of scale. That often isn't the case and a significant R&D effort needs to go underway on just how one can leverage existing technology for their use case.
There's very often at least one, if not many, mission critical functional requirements from existing tech that require significant effort to make the jump from the existing tech to the desired use case. And guess what, all the non-niche users don't want to pay for that, so you need to be prepared to pony up the capital, accept risk of failure, and be ready to take the plunge.
I tell people with this mentality that they need to work in reverse, first understand the technology they think is close and find the problem sets that have the best match up and focus on those. These efforts can costs hundreds of thousands very easily if not millions to tens of millions if you just play it by ear that "...this thing is sorta like what we want so it can't possibly be that difficult to adapt." (Basically what I hear with technology management, many business people, and clients)
Many people pretend software and tech are just Lego blocks and since it's virtual, there's no capital needed. Good luck, because the skills needed to deal with this tech isn't cheap and the complexity often isn't low meaning expensive and difficult to find labor for long periods of time, often with a fairly good chance of failure.
Or, abandon all of that. A space imagery company is a media company. They generate content. So do what other content creators do. Take everything you have and shovel it in front of people as fast as possible. Deliver it by any and every means available. Ask questions, but do so AFTER they have already made a purchase. Then judge what your customers want by what they choose to consume.
Say I'm a farmer and for examples sake I want regular aerial images to estimate crop yield for a plot of land. That would require high resolution imaging of a particular patch everyday for maybe a few months. That would require purposeful data capturing at regular time intervals during overhead satellite passes.
From what i understand satellite imaging companies won't happen to just have those images containing the region of interest you want just lying around on their hard-drives which they can pull out with some query. If they make all the images they have available to the public, I'm guessing most of it will be useless to people considering it needs to cover the desired region of interest across time and space.
This is a good analogy. How many companies say “I’ll build a sweet motor and then find a customer for it”? They don’t. They build the motor for the application. (More often, they build something close to the final product.)
When you look at smaller motors (e.g. DC motors in handheld consumer products), they're basically jellybean parts targeted towards the highly specific use case of making a shaft turn.
Wrong. They absolutely do. In fact I’d wager the vast majority of motors are essentially commodity goods. Even if you were thinking of just combustion engines, its really not the case, most engines get reused many times. Which makes sense, its an outsized engineering problem to optimize so you’d want to maximize your return.
For example. https://www.mcmaster.com/electric-motors/
>individual farms might want to look at relative growth rates of corn in their fields, or soil moisture levels, etc.
a LOT of people want this, but they would never pay $x,xxx/month for that, ever.
Eos (iirc it’s been a while) actually let me buy some imagery, but they would only give me pictures, not actual georeferenced rasters.
The actual manipulation and use of the data, even for machine learning, is pretty straightforward these days with ArcGIS. So yes, I want pixels.
And I can imagine the cheaper customers are a lot less educated and don't have the right expectations, like how often their target area is covered in clouds.
I work for John Deere. I can't speak for the company. I'll confirm we are intersted in imagining, but I won't comment on our plans to deal with the above issues.
I've realised that that might still be a viable option once I started to map the forrest cover in my geographic area based on 150-years-old maps (these excellent maps [1] drawn by the Austrians in the 1860s). Some JS-code for the front-end that helped me "draw out" the forests, then send that data to a Django/Python backend and call it a day. It took me a while to draw those forests out but the job was very easily scalable in terms of human-power, i.e. 10 more me would have probably finished it 10 times faster with a little coordination (for anyone curious the data is in here [2], I'd say it was almost 90% done when I passed on to my next project, as I often do). I was first looking at using some heuristics in order to "automate" some part of the job, but both the false-positives and the false-negatives were just too high, the outputs would have been horrible in terms of accuracy.
[1] https://maps.arcanum.com/en/map/secondsurvey-wallachia/?laye...
[2] https://github.com/mihaitc/forrests/tree/master/counties
OpenStreetMap needs good imagery for mapping trails and buildings.
Off-roaders and overlanders need good imagery to verify the existence and state of trails.
That's just me, so I'm sure that there are tons of similar low key use cases.
Plus, it doesn’t appear to be needed. The Russian military is proving to be god-awful at even basic field ops like camouflaging their vehicles.
But the actual satellites can be seen with the naked eye, and their orbits are known. The resolution is a linear function of their height, so it can be easily inferred, or at least bounded, by that of a "hubble" at a much lower height. If they are really worried about this scalar piece of data, they can easily blur the images before transferring them to ukraine. Not that it makes a lot of difference to see a column of tanks at 30cm or at 15cm pixels.
Incorrect. Even in the consumer camera space, resolution is a function of distance, native sensor resolution, lens magnification, lens quality, shutter speed (because the target is moving), stability of the tripod, etc. Same thing is true of orbital imagery: your effective resolution is a function of your optics, your sensor, the ability of your attitude control system to hold a steady pointing vector, etc.
Also, "capability" != "resolution". What frequency bands is that satellite imaging in? Visible, SWIR, LWIR, ultraviolet? What is the effective magnification of its optics? Is it an optical system at all, or is it an RF bird? Is it all of the above? Does it just take top down snapshots, or can it track moving targets? If the latter how fast can it track? Fast enough to keep up with a tank, or fast enough to keep up with a fighter plane? How many frames per pass can it take? How fast can it slew to get multiple objects in the same pass? Etc.
Is there some way to email you? There isn't any contact information on your profile.
Trump already did this when that Iranian something-or-another blew up (missile silo? nuclear reactor?) a few years ago, and he provided classified satellite images to the pubic
Beyond that, sure
https://news.yahoo.com/trump-tweeted-classified-satellite-im...
Is this really true? I guess I can believe it, but it seems strange that the United States is sending over $800 million in weaponry, but won't send over satellite imagery.
I'd guess this is because you can't publish satellite imagery without revealing a lot about your intelligence gathering capabilities.
Why not? It's been a while since the west has had a war where the moral details are so clear. If I had a company like this I'd be jumping on the opportunity.
Interested to hear Mr. glen's opinion about that approach.
History has shown that when you sell something for less then you pay for it; hoping that users don’t fully use their credits to cover that loss; that time is not on your side.
They are already the walking dead.
This is basically right. The problem with space imagery is that almost everyone who wants it has a niche use case, and those few organizations without a niche use case (the US Weather Service, various militaries, etc) generally want imagery that's so specialized to their own problem that they have to spec, buy, and operate their own orbital assets.
Take Ukraine as an example. Leaving aside the moral question of whether a satellite imagery company should be profiting off the Ukrainian war, Ukraine appears to be using commercial orbital imagery providers to figure out Russian troop movements. That use case is not one any commercial provider anywhere is going to build an ML model for. But analysts working on behalf of Ukraine can absolutely either use raw pixels or develop their own ML algorithms that run on top of the raw pixels to find Russian tanks.
And almost every other potential user is similar. They're all looking for something different. Oil companies want to pre-screen drilling locations. NGOs want to look at deforestation in Brazil or methane leaks in Saudi Arabia. You could even go all the way down to individuals -- at the right price, individual farms might want to look at relative growth rates of corn in their fields, or soil moisture levels, etc. Or they might want to count heads of cattle or sheep, or... or... or.
The point being, outside of weather, which we already know how to get to end users without having them subscribe to an orbital imagery provider service, every customer is different, and what they want from the pixels is different. It's basically the long-tail problem. In order to be profitable you have to fill an enormous number of niche use cases.