[HN Gopher] Can a model trained on satellite data really find br...
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Can a model trained on satellite data really find brambles on the
ground?
Author : sadiq
Score : 78 points
Date : 2025-09-25 19:28 UTC (3 hours ago)
(HTM) web link (toao.com)
(TXT) w3m dump (toao.com)
| cuno wrote:
| 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?
| Waterluvian wrote:
| 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.
| CrazyStat wrote:
| > 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 wrote:
| 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 wrote:
| It is good to enable people to hedge against bad harvests.
| sadiq wrote:
| 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
| sadiq wrote:
| 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.
| 0_____0 wrote:
| I've wondered this about finding hot springs.
| avsm wrote:
| That's should be a pretty good usecase; if you do just a few
| labels manually of known hotsprings you should be able to
| find others quite quickly using the TESSERA interactive
| notebook. The embeddings capture the annual spectral-temporal
| signature, so a hotspring should be fairly distinctive vs the
| surroundings.
|
| Video of the notebook in action
| https://crank.recoil.org/w/mDzPQ8vW7mkLjdmWsW8vpQ and the
| source https://github.com/ucam-eo/tessera-interactive-map
| avsm wrote:
| 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-python
|
| Downstream 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!
| throwup238 wrote:
| 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.
| tony_cannistra wrote:
| almost definitely!
| sadiq wrote:
| 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.
| pbhjpbhj wrote:
| Not much detail on the method? Like what data it takes from
| iNaturalist - for example if it's taking in GPS coordinates of
| observations of brambles then it's not clear what there is for
| the ML model to do.
|
| What detail was in the satellite images, was it taking signals of
| the type of spaces brambles are in, or was it just visually
| identifying bramble patches?
|
| In the UK you get brambles in pretty much every non-cultivated
| green space. I wonder how well the classifier did?
|
| Interesting project.
| sadiq wrote:
| Hi! You can find a bit more about Gabriel's model through some
| of his posts over the last few weeks:
| https://gabrielmahler.org/posts/
|
| When it comes to the satellite images, the model actually used
| TESSERA (https://arxiv.org/abs/2506.20380) which is a model we
| trained to produce embeddings for every point on earth that
| encodes the temporal-spectral properties over a year.
|
| Think of it like a compression of potentially fifty or a
| hundred observations of a particular point in earth down to a
| single 128 dimension vector.
|
| Happy to answer any other questions.
| whalesalad wrote:
| FarmLogs (YC 12) did exactly this. We used sat imagery in the
| near-infrared spectrum to determine crop health remotely. Modern
| farming utilizes a practice called precision ag - where your
| machine essentially has a map of zones on the field for where
| treatments are or aren't needed and controllers that can turn
| spray nozzles on/off depending on boundaries. We used sat imagery
| as the base for an automated prescription system, too. So a
| farmer can reduce waste by only applying fertilizer or herbicide
| in specific areas that need it.
| jcims wrote:
| Seems like it could be pretty useful for archaeology as well.
| sadiq wrote:
| That's actually a great idea! I wonder what kind of feature
| size would be needed though - TESSERA's embeddings are at a 10
| metre resolution so for larger structures you might need some
| kind of spatial aggregation.
| spogbiper wrote:
| Related, I think? Satellite + AI = finding things, not sure if
| similar beyond that
|
| https://www.pnas.org/doi/10.1073/pnas.2407652121
| siva7 wrote:
| can it find me truffles?
| sadiq wrote:
| If you have some GPS locations of truffles, you could use the
| notebook Anil mentioned here
| https://news.ycombinator.com/item?id=45378855 and give it a go.
|
| There is the issue of just how visible truffles are from space
| though, if they grow under cover. That said, it may still work
| because you can find habitats that are very likely to have
| truffles. We've had some promising results looking at fungal
| biomass.
| ggm wrote:
| If it can find sloes it's going to make sloe gin foragers very
| very angry. Generally when they find a usable crop they don't
| share it.
| cjensen wrote:
| The in-person verification of hotspots was good, but in-person
| verification of non-hotspots was not done, and might be
| difficult.
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