We're volunteer driven and currently rely on personal donations, so we're scrappy. We could probably justify somewhere in the region of $10k/yr. The jets/balloon angle is interesting, thanks - hadn't occurred to me, and I'll search through what's out there.
See if you can negotiate reselling the imagery they sell you. It might be hard to get agreement with this as the vendor will have you both as a customer and compeditor but if you pull it off, you could recoup your costs and then some. For a few weeks, no one else in the private sector will have the freshness and/or quality of imagery you do.
Maybe I'm missing something obvious, but what about drones? Probably would have to get permits most likely, but still might be cheaper than alternatives (although balloons are hard to beat when it comes to costs, not always reusable though).
We do use a drone when we know of a site where deforestation has taken place. The gap we're trying to fill is early detection of forest intervention, so that we can alert appropriate agencies (who are generally under-resourced) and get an inspection to take place while activity is ongoing.
How many years away are we from a cheap drone that will takeoff, land, solar recharge, repeat until it returns to you a few weeks later with a few tb of SD cards of high res imagery?
Pretty close. Sesame Energy[0] make these shipping container boxes with solar panels + batteries so you can just drop them where you need no-supply chain energy. The boxes also synthesize hydrogen which can be used to power drones. The talk I heard from the CEO said the automated swapping of hydrogen canisters was not yet there, but they were working on it. Nothing in robotics is easy, but this feels like a very attainable goal that the military would pay to get working.
A lot of the barriers are regulatory in the Western world. In rainforests you might not have to worry about that, but there aren't many shade free spots to land
Really busy, from satellite constellation tasking to planet and co basemaps to the sentinel family to aerial imagery to helicopters, drones and even blimps.
They all have their unique combination of cost, resolution, area coverage, revisit rate and spectral modes. Quite difficult sometimes to find a good fit for the underlying problem. What‘s clear is that resolution and revisit rate correlate with cost. Shit‘s expensive.
I can't get the vector basemap to render in QGIS properly with any other projection. I love using EPSG:3301 for Europe, etc.. but loads of strange things happen. Even 4326 is an issue.
There should be enough SQL in the blog to re-purpose extracting out the Wildberries locations and seeing where they land on top of. I've never heard of this firm before you mentioned it.
From Google:
> Citibank operates over 2,300 ATMs within more than 600 U.S. branches, with a total network of over 65,000 fee-free ATMs
So the 57,163 Citibank locations are probably a combination of their branches and ATMs.
Update: I reviewed Alltheplaces a while back, they scrape company websites for store locations. They reported 68,227 locations for Wildberries. ATP is one of the sources Overture use but they seem to use 1.55M of the records from their 19M-record dataset. https://tech.marksblogg.com/alltheplaces.html
I contribute to ATP and can confirm that the author of the wildberries spider was deliberately trying to collect https://wiki.openstreetmap.org/wiki/Tag:shop%3Doutpost (online order pickup locations). It's not a common occurrence within the current set of ATP spiders to capture such features. A quick search indicates that OSM doesn't appear to have tags designed to capture pickup/dropoff partnerships between retail brands, for example, an agreement from a pet supply shop to allow collection of parcels from select fuel stations of a partner brand. Thus I think the author of the wildberries spider has used shop=outpost as the closest tag available in OSM, and Overture Map's filters wouldn't be able to omit these features from their dataset unless Overture Maps adds wildberries to their exclusion list.
Ideally ATP's "located_in" and "located_in:wikidata" fields would be populated for these wildberries pickup locations, making it clear the pickup location is part of a parent feature (e.g. fuel station, supermarket). These fields are specific to ATP and are not OSM fields. OSM would expect features to be merged and a hypothetical field such as "pickup_brands:wikidata=Q1;Q2;Q3" be used instead on the parent feature.
ATP has a much more inclusive set of features it can extract than what Overture Maps, TomTom et al care about. As Overture Maps is more opinionated on what they aggregate they will filter out ATP extracted features such as individual power poles, park bench seats, local government managed street and park trees, stormwater drain manholes, cemetery plots, weather stations, tsunami buoys, etc. I think there might be some exceptions if it helps TomTom et al with their products such as speed camera locations, national postal provider drop-off/pick-up locations within other branded retail shops, etc.
Defcon had a great talk on all the different navigational systems pilots can use and a note at the end that these shouldn't be decommissioned at the rate they're experiencing atm https://www.youtube.com/watch?v=wSVdfOn737o
From what I've seen in news reports, China has built a lot of tower blocks that are 10s of floors, rather than the 4-5-floor buildings I saw when I worked in and travelled around India.
India has ~4x the population of the US so the ratio of buildings isn't much of a surprise.
The US has only used 25% of its land. Overture published a land use dataset a while back that could go some way to verify how much land on earth is urban, covered in forest, etc.. That might only need a single SQL statement given how they structured their data.
I had to look into ~19 imagery firms for some telco work in Canada last year.
There are private jets that can capture 10cm imagery and can pick the ideal weather window to fly in.
There are also firms that fly balloons 20 - 80 KM off the ground that can capture 4cm imagery.
The space is pretty busy.
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