I suggest changing the link to https://huggingface.co/ibm-nasa-geospatial . The currently linked press release is an insufferable corporate PR word salad.
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IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
21–30 of 90 posts
Re: IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
#22This may be a silly question as I'm quite inexperienced w/ ML and a lot of the words in this article don't mean anything to me yet: But, could this "model" be used for something like monitoring land use in a city? The specific example I'm thinking of is getting a percentage breakdown of what land devoted to paved surfaces (parking/roads), to vacant undeveloped lots, and to built structures. It would also be interesti…
The thing you are asking for does not sound hard if you have multispectral satelite data of your target area.
The typical trick is to look for areas which absorb visible red while reflect near infrared to identify vegetation. If all you have is rgb imagery then you can use machine learning techniques to develop a classification system.
It does not look like this model means a breakthrough in your application area. Definietly not out of the box, maybe with more work you can refine it to do the classification you are looking for.
Do you have access to satelite images of areas where you would be interested in these percentages?
Re: IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
#23Keep in mind, even though this is the largest geospatial model, it's still a tiny model, with only 100M parameters. I'd be excited to see what a more substantial, state-of-the-art model could do with geospatial data. Say, a model based on something like ViT-22B, with 22 billion parameters: https://arxiv.org/abs/2302.05442 .
I'm not disagreeing with you but just pointing out that it's kind of wild that "100M parameters" isn't considered SotA anymore. Amazing how far we've come in such a short time.
Re: IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
#24I suggest changing the link to https://huggingface.co/ibm-nasa-geospatial . The currently linked press release is an insufferable corporate PR word salad.
As someone who is not a Hugging Face user your link is much less clear than the submitted link. Really esoteric UI. What am I even looking at? What are Spaces?
Re: IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
#25This may be a silly question as I'm quite inexperienced w/ ML and a lot of the words in this article don't mean anything to me yet: But, could this "model" be used for something like monitoring land use in a city? The specific example I'm thinking of is getting a percentage breakdown of what land devoted to paved surfaces (parking/roads), to vacant undeveloped lots, and to built structures. It would also be interesti…
The thing you are asking for does not sound hard if you have multispectral satelite data of your target area. The typical trick is to look for areas which absorb visible red while reflect near infrared to identify vegetation. If all you have is rgb imagery then you can use machine learning techniques to develop a classification system. It does not look like this model means a breakthrough in your application area. De…
> Do you have access to satelite images of areas where you would be interested in these percentages?
Answering my own question: it seems one can access the right type of data from the Sentinel satelites relatively freely.
Re: IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
#26Unclear which LICENSE it is.
Apache 2.0 E.g. https://huggingface.co/ibm-nasa-geospatial/Prithvi-100M (Though with all Facebook's shenanigans I understand the need to be sceptical and search for a license when a company claims "open source")
And the finetuned models seems to be CC-BY-4.0 (note there are no NC). IBM actually not lying it seems unlike most of the other "open source" models.
Re: IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
#27the emphasis here is obviously on market-facing customer accounts. Basic LANDSAT NASA data is open to anyone, including big companies. So is this not simply an IBM Watson 2.0, including vague and bombastic impressiveness claims? Floods and fires are bad news, but how does this product actually get used to make things any different ?
Land use classification is one of the features advertised. While some may be capable of putting together a classification system on their own, not everyone can (especially reliably). Land use often directly effects things like flooding and fires. Such classification can be used in conjunction with other models to compare say current vs proposed changes in attempts to reduce things like flooding and fires spreading. You might be talking more about mass flooding and less about, poor water overflow management and things like that in which case sure, some things are largely inactionable for humans currently. There are cases where we can have some tangible effects at least on the scales we do create and manage infrastructure though.
Re: IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
#28Unclear which LICENSE it is.
ML models are not copyrightable and the licenses people choose to try to apply are irrelevant.
Yes, I actually type these by hand. My carping is 100 percent artisanal.
Re: IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
#29Earlier quoted context omitted.
So what's the better word?
What it actually is: https://huggingface.co/ibm-nasa-geospatial/Prithvi-100M “Prithvi is a first-of-its-kind temporal Vision transformer” That is enormously more specific and interesting, and the word model is absent.
Transformer is overly specific. Most people won't care about the actual architecture and would just treat it as a black box.
Re: IBM and NASA Open Source Largest Geospatial AI Foundation Model on Hugging Face
#30This may be a silly question as I'm quite inexperienced w/ ML and a lot of the words in this article don't mean anything to me yet: But, could this "model" be used for something like monitoring land use in a city? The specific example I'm thinking of is getting a percentage breakdown of what land devoted to paved surfaces (parking/roads), to vacant undeveloped lots, and to built structures. It would also be interesti…
If you are just interested in the percentage share (not a map of labeled data), all you need is random sampling. Classifying a couple of hundred coordinates is sufficient, takes at most some hours (more likely <1h), and is required anyway to train your network.