William Lidberg

Geoint is live!

Today is International GIS Day, and we’re taking the opportunity to soft-launch a service that, in just a few minutes, shows whether your idea can be realised using AI trained on laser data:

ml.geoint.se

Docentföreläsningar vid fakulteten för skogsvetenskap | slu.se Välkommen till höstens docentföreläsningar vid S-fakulteten den 11-12 november.

If you are bored, you can watch my Docent lecture today at 11:00: www.slu.se/kalender/202... AI-powered maps and other problems.

Vacation from my research role gives me more time for side-projects

Don't forget to optimize the file size of the .READMEs

I am looking for a phd student to join my research group in Umeå! www.slu.se/en/about-slu...

My landscape cubes now have a modelled groundwater level. Excited to see what my 3D-CNN can learn from this.

I’ve released a prototype of a tool that trains a machine learning model on open geographical data using your own training data.
Upload a point shapefile where the first column contains the values you want to predict.
It's free to experiment with, and no data is stored. geoint.konvergens.se

I have now added the color from IR imagery into my "landscapecubes". Now working to add groundwater under the DEM surface and then I need to figure out a way to encode logic in my 3D-CNN. For example geographical location or runoff data.

I am running some deep-learning models on voxel cubes of remote-sensing data instead of images to map soil moisture. It works but is quite demanding. So far, I have built a proof of concept in Tensorflow using 3D convolutions. Do you have any good advice for me?

Deep learning-enhanced detection of road culverts in high-resolution digital elevation models: Improving stream network accuracy in Sweden Sweden, a mostly forested country with many small forest roads obstructing topographical modelling of shallow groundwater and streams.Maps have tradit…

Paper: www.sciencedirect.com/science/arti... code: github.com/williamlidbe...

When extracting streams from high-resolution digital elevation models, road culverts can be a pain. I explored an approach where a residual attention UNet was used to identify and breach road culverts, utilising ALS data and orthophotos. It works but produces a fair amount of false positives.