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I wish the press release had a bit more detail about what this model actually does and whether it's actually useful for the suggested use cases. However, make
by philosophygeek 3y ago
I wish the press release had a bit more detail about what this model actually does and whether it's actually useful for the suggested use cases.
However, make no mistake: this is for the scientific community and will not help geospatial data to be commercialized. No one cares about your geospatial crop model or that you can identify energy infrastructure or that there's some activity around that copper mine. Well, at least no one cares that will actually pay you.
(FWIW, I cofounded a geospatial analytics company)
Satellite data is extremely idiosyncratic. It's coarse (~10m at best), infrequent (every few days at best), and oh you have to deal with the fact that the planet is covered in 50% clouds at any moment. Satellite data works best on things that don't move, that are fairly large, and change infrequently. If you find a use case that satisfies those conditions and want to make money, then you need to find a problem that terrestrial sensors haven't solved. And if you find that problem, the cost of building, training, and running your model (plus the cost of the data!) has to be less than the marginal value of your model. Good luck finding those use cases.
The US Government is special. We don't know what's going on in North Korea or Ukraine or the South China Sea so we buy high resolution imagery over those areas (30cm) at great cost. Large ag companies and oil companies know what's going on within their own facilities; and price gives them information about the rest of the supply chain.
In other words, this might be an interesting announcement for scientists, but it won't change the geospatial market at all.
- mrbgty 3y agowhat happened with your company?
- justinwp 3y agohe ran into the ground without a vision and excess spending on bar tabs and the startup life
- throwaway20222 3y agoDid you work there and know this as a fact?
- gulyams 3y agoIf I'm correct and philosophygeek is Mark Johnson, he cofounded Descartes Labs. It was a pretty cool company with some quite impressive technology. He (they) did a lot. I'm not far from bashing the VC scene and the adjacent startup culture, but your overly cynical comment was too much even for me. More intellectual humility and less cheap soundbites would benefit society a lot. If you're interested, he wrote about it: https://philosophygeek.medium.com/meditations-a-requiem-for-descartes-labs-8b913b5e898 https://philosophygeek.medium.com/meditations-a-requiem-for-...
- RosanaAnaDana 3y agoDescarte labs folded? Oh man. I had no idea! These guys were some of my prime competition for years. The true cost of venture capitol revealed.
- numair 3y agohttps://philosophygeek.medium.com/meditations-a-requiem-for-descartes-labs-8b913b5e898 https://philosophygeek.medium.com/meditations-a-requiem-for-...
- blincoln 3y ago> Satellite data is extremely idiosyncratic. It's coarse (~10m at best), infrequent (every few days at best), and oh you have to deal with the fact that the planet is covered in 50% clouds at any moment. Are the coarseness and cloud aspects going to become less of a factor now that there are commercial high-resolution synthetic aperture radar imagery providers? I'm just a hobbyist, but the imagery I've seen is <i>sharp</i>, and it even caught the NRO's attention.[1] [1] https://spacenews.com/national-reconnaissance-office-signs-agreements-with-five-commercial-radar-satellite-operators/ https://spacenews.com/national-reconnaissance-office-signs-a...
- nico 3y agoSuper interesting. Hadn’t heard of SAR before. Quickly reading about it, it seems like it works like lidar, what’s the difference between the two techniques? Is SAR like “lidar for space”?
- changoplatanero 3y agoI think one difference is that with SAR the sensor needs to be moving.
- deleted 3y ago[deleted]
- RosanaAnaDana 3y agoLike... no? InfSar (InSar, SAR, whatever we're calling it these days) isn't a drop in replacement for anything. Its really neither here nor there when it comes to the utility of other dataset. Infsar is amazing, dgmw, but its stands on its own and has its own advantages/ disadvantages. The ocs point stands. Satellite data is tough because there is a shit ton of atmosphere between you and the target. That issue doesn't go away with infsar and especially not if it isnt coincidentally collected with higher resolution spectral data. I've been in the industry for around 15 years. Things have gotten better, but really, its important to understand the context and limitations of specific platforms. Afaik, there is no panacea.
- bookofjoe 3y ago>Satellite data is extremely idiosyncratic. It's coarse (~10m at best) >The best commercially available spatial resolution for optical imagery is 25 cm, which means that one pixel represents a 25-by-25-cm area on the ground—roughly the size of your laptop. https://spectrum.ieee.org/commercial-satellite-imagery https://spectrum.ieee.org/commercial-satellite-imagery
- RosanaAnaDana 3y agoI regularly use up to 3cm aerial imagery. There are many very nice commercial products available.
- DennisP 3y agoAre there any products available for casual users, just paying for a few images?
- crucialfelix 3y agoThere are many now. You can buy a single image, even schedule to take a live shot at a specific time. https://skywatch.com/earthcache/ https://skywatch.com/earthcache/
- woeirua 3y agoI think it is very important for people to understand that terrestrial sensors are orders of magnitude cheaper for most applications, and are typically far more accurate too. There's a reason why most remote sensing companies go out of business fairly quickly.
- pmarreck 3y agoYou have a sibling comment from PlanetScope that claims ~30-50% profit margin, depending on the quarter.
- dharmab 3y agoPlanetScope is 3.7m and captures the full land area of the earth daily (minus cloud cover, of course): https://www.planet.com/products/planet-imagery/ https://www.planet.com/products/planet-imagery/ Disclaimer: I work for Planet. I also disagree with the assertion "no one will actually pay you." Read pages 26-28 of the quarterly report for more information.
- fnands 3y agoI work for a customer of Planet and can confirm, we pay Planet a lot of money each year.
- marcopicentini 3y agoThe Planet stock is down -70% since IPO (from 10$ in 2022 IPO to 3$ today). NYSE: PL
- fnands 3y agoAnd it took Amazon nearly a decade to get back to their internet bubble highs. PL got SPACed onto the stock market during the SPAC bubble. That being said, while I do believe that Planet has one of the best business models in the industry, I do sometimes worry that they are a bit early, and their customers aren't ready for them yet. As someone who has to work with their data (among others), Planet has some of the best APIs in the industry (it's a low bar though).
- marcopicentini 3y agoWhy do you think they haven’t rebounded during the last bull market (see Nvidia, MSFT, etc..)
- fnands 3y agoNot really seen as an AI play. The bull market has been mostly driven by FAANG + Nvidia. I'm mostly just playing devils advocate here, and the point I'm trying to make is share price alone isn't everything. Planet is growing its revenue YoY, and they might even be profitable soon (lol). Also, my original point was that the company I work for buys a lot of data from Planet, which is something that's just increasing as we grow.
- fnands 3y agoI'm an ML engineer working for a geospatial company and I can assure you, we are looking into this. > Satellite data is extremely idiosyncratic. It's coarse (~10m at best) 10m is the best free imagery, in the commercial domain it goes down to 30cm. > Well, at least no one cares that will actually pay you. There are plenty of things people will pay you for. But you gotta find those niches. > In other words, this might be an interesting announcement for scientists, but it won't change the geospatial market at all. Maybe, we'll definitely check if it can be fine-tuned on higher res data. We do sometimes use Sentinel-2 (not a lot though), but can help with those cases.