Planet Labs' open satellite feed(tech.marksblogg.com) |
Planet Labs' open satellite feed(tech.marksblogg.com) |
If you are looking for evidentiary purposes, does the Sentinel-1 + Nimbo data give you enough to filter the forest-wide data down to specific areas of interest you might want more spatial/temporal resolution? (or as a former colleague once put it when looking for evidence of more localised and heterogenous environmental damage "to find the needle in the haystack, you first remove the haystack"). Particularly if identifying specific areas of interest is a potential route for you to escalate to another party with an active interest and bigger budget...
Your other route to the commercial data you ideally want would be via partnership with EO consultancies with publicly funded R&D projects to showcase their capabilities (easier if you're European, but not a prerequisite). ESA, for example, devotes a lot of funding for private consortia to demonstrate that Copernicus data (coupled with other data where necessary) yields useful results...
It's a while since I worked in this field (in a non-technical role) but happy to share what I learned in more detail - email in profile.
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.
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.
Disclosure: this is run by my team.
https://www.iceye.com/blog/deforestation-solution-9-essentia...
https://www.iceye.com/newsroom/press-releases/iceye-and-the-...
I suppose you could even train it (maybe) on multiple years / time periods of historical high and low res data before using the latest Sentinel stuff ?
Edit: I'm sure you already know this but I bet for the above the false color IR data could also be especially useful
I ran the shoelace formula over the Nepal Pelican footprint from the post. The bounding box around it comes out about 40% larger in area, so somewhere over a quarter of that box is ground with no pixels behind it. That scene is only 3.8 degrees off-nadir as well. The summarize table further down has some going up to 28.9, and those would be further off.
Indexing the bbox is the obvious move because it's four numbers and any database will put an R-tree on it. But coverage queries then hand you scenes for an AOI and the file turns up empty over that part of it. Took me longer than it should have to work out why there was a hole in my mosaic.
Separately, eo:cloud_cover is one number for the whole scene. Sorting on it to find your clearest option over a small area doesn't hold up. 85% cloud can still be clear over the part you want. The UDM2s give you it per pixel, but that's a second raster open per candidate before you can rank anything.
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).