An Industrial Think Tank Focused on Developing and Promoting AI Technology for Geospatial Applications
Let's get this thing rolling!
Starting out: lets have a look at the previous tutorials from GDA2030 to get an idea where we can begin. There we can learn some basics of using google colab, we can see some basic image loading examples in python, see an example of accessing landsat data, see some more advanced image maniuplation techniques, and finally get an example of building a model in scikitlearn.
let's do this!
Check out our latest 'Hello Earth' satellite classification and other weird tests in our experiments section...
kind of... You can see a website of sorts at https://nscc-cogs.github.io/Aestheta/
To get going fast, try the following in a new Google Colab notebook
!git clone https://github.com/NSCC-COGS/Aestheta.git
import Aestheta.Library.core as core
core.getTile(source = 'google_sat', show=True)
You should see earth appear - represented as a small numpy array! Stay tuned for more simple examples of what were doing with this data.
We reccomend 64-bit python version 3.7.10 and higher. We use scikit-learn which includes numpy, imageIO.
To get access the magical GIS tools in GDAL, rasterio, and fiona on windows - we recommend you donwload the appropriate wheel files for your vesrion on python from the glorious website of Christoph Gohlke.
Once you have these wheel files, you can run the following commands in command line ...
cd c:\downloads
py -3.9 -m pip install GDAL-3.2.2-cp39-cp39-win_amd64.whl
py -3.9 -m pip install rasterio-1.2.1-cp39-cp39-win_amd64.whl
py -3.9 -m pip install Fiona-1.8.18-cp39-cp39-win_amd64.whl
these are for example having downloaded the wheel files to c:\downloads and for 64bit python version 3.9
We're teaching an AI to understand what it means to be looking at our lovely planet.
There is lots of great data available and tools we can use! Early results are very promising.
