| ▲ | cuno 12 hours ago |
| So after transforming multispectral satellite data into a 128-dimensional embedding vector you can play "Where's Wally" to pinpoint blackberry bushes? I hope they tasted good! I'm guessing you can pretty much pinpoint any other kind of thing as well then? |
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| ▲ | avsm 12 hours ago | parent | next [-] |
| Yes it's very good fun just exploring the embeddings! It's all wrapped by the geotessera Python library, so with uv and gdal installed just try this for your favourite region to get a false-colour map of the 128-dimensional embeddings: # for cambridge
# https://github.com/ucam-eo/geotessera/blob/main/example/CB.geojson
curl -OL https://raw.githubusercontent.com/ucam-eo/geotessera/refs/heads/main/example/CB.geojson
# download the embeddings as geotiffs
uvx geotessera download --region-file CB.geojson -o cb2
# do a false colour PCA down to 3 dimensions from 128
uvx geotessera visualize cb2 cb2.tif
# project onto webmercator and visualise using leafletjs over openstreetmap
uvx geotessera webmap cb2.tif --output cb2-map --serve
Because the embeddings are precomputed, the library just has to download the tiles from our server. More at: https://anil.recoil.org/notes/geotessera-pythonDownstream classifiers are really fast to train (seconds for small regions). You can try out a notebook in VSCode to mess around with it graphically using https://github.com/ucam-eo/tessera-interactive-map The berries were a bit sour, summer is sadly over here! |
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| ▲ | throwup238 11 hours ago | parent [-] | | This is all far outside of my wheel house but I'm curious if there's any way to use this for rocks and geology? Identifying dikes and veins on cliff sides from satellites would be really cool. | | |
| ▲ | jofer 9 hours ago | parent | next [-] | | A major limitation is that most different rock types look essentially identical in visual+NIR spectral ranges. Things separate once you get out to SWIR bands. Sentinel2 does have some SWIR bands and it may work reasonably well with embeddings. But a lot of the signal the embeddings are going to be focused on encoding may not be the right features to distinguish rock types. Methods more focused specifically on the SWIR range are more likely to work reliably. E.g. simple band ratios of SWIR bands may give a cleaner signal than general purpose embeddings in this case. Hyperspectral in the SWIR range is what you really want for this, but that's a whole different ball game. | | |
| ▲ | throwup238 9 hours ago | parent [-] | | > Hyperspectral in the SWIR range is what you really want for this, but that's a whole different ball game. Are there any hyperspectral surveys with UAVs etc instead of satellites? | | |
| ▲ | jofer 8 hours ago | parent [-] | | Usually airplanes because the instruments are heavy. But yeah, that's the most common case. Hyperspectral sats are much rarer than aerial hyperspectral. |
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| ▲ | sadiq 11 hours ago | parent | prev | next [-] | | It might work. TESSERA's embeddings are at a 10 metre resolution, so it might depend on the size of the features you are looking for. If those features have distinct changes in colour or texture over time or they scatter radar in different ways compared with their surroundings then you should be able to discriminate them. The easiest way to test is to try out the interactive notebook and drop some labels in known areas. | | |
| ▲ | throwup238 9 hours ago | parent [-] | | Is there a way to cluster the embeddings spatially or look for patterns isolated so some dimensions? (Again, way out of my wheel house) What I mean is a vein is usually a few meters wide but can be hundreds of meters long so ten meter resolution is probably not very helpful unless the embeddings can encode some sort of pattern that stretches across many cells. |
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| ▲ | tony_cannistra 11 hours ago | parent | prev [-] | | almost definitely! |
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| ▲ | Waterluvian 12 hours ago | parent | prev | next [-] |
| I haven’t done this kind of thing since undergrad, but hyperspectral data is really frickin cool this way. Not only can you use spectral signatures to identify specific things, but also figure out what those things are made out of by unmixing the spectra. For example, figure out what crop someone’s growing and decide how healthy it is. With sufficient temporal resolution, you can understand when things are planted and how well they’re growing, how weedy or infiltrated they are by pest plants, how long the soil remains wet or if rainwater runs off and leaves the crop dry earlier than desired. Etc. If you’re a good guy, you’d leverage this data to empower farmers. If you’re an asshole, you’re looking to see who has planted your crop illegally, or who is breaking your insurance fine print, etc. |
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| ▲ | sadiq 12 hours ago | parent | next [-] | | Hyperspectral data is really neat though it's worth pointing out that TESSERA is only trained on multispectral (optical + SAR) data. You are very right on the temporal aspect though, that's what makes the representation so powerful. Crops grow and change colour or scatter patterns in distinct ways. It's worth pointing out the model and training code is under an Apache2 license and the global embeddings are under a CC-BY-A. We have a python library that makes working with them pretty easy: https://github.com/ucam-eo/geotessera | |
| ▲ | CrazyStat 12 hours ago | parent | prev [-] | | > If you’re a good guy, you’d leverage this data to empower farmers. If you’re an asshole, you’re looking to see who has planted your crop illegally, or who is breaking your insurance fine print, etc. How does using it to speculate on crop futures rank? | | |
| ▲ | Waterluvian 12 hours ago | parent | next [-] | | Every time someone explains the way short selling or speculative markets work, I have a “oh, I get it…” moment and then forget months later. Same with insurance… socialized risk for our food supply is objectively good, and protecting the insurance mechanism from fraud is good. People can always bastardize these things. | |
| ▲ | wbl 12 hours ago | parent | prev [-] | | It is good to enable people to hedge against bad harvests. |
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| ▲ | sadiq 12 hours ago | parent | prev | next [-] |
| Yes! TESSERA is very new so we're still exploring how well it works for various things. We're hoping to try it with a few different things for our next field trip, maybe some that are much harder to find than brambles. |
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| ▲ | 0_____0 12 hours ago | parent | prev [-] |
| I've wondered this about finding hot springs. |
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