Geospatial ML2024Shipped

Glacier U-Net

Glacier boundaries segmented from 5-band Sentinel-2 imagery.

A U-Net for binary semantic segmentation of glacier boundaries on 5-band Sentinel-2 imagery, with a custom geospatial loader that tiles multispectral GeoTIFFs and normalizes each band against training-set statistics.

livelast push

~/glacier

Project Telemetry

Dice

0.87

IoU

0.78

Training patches

1,200

Spectral bands

5

How it works

~/glacier/architecture · step 1/2

01

5-band GeoTIFFs

02

tiling + band norm

03

U-Net

04

mask stitching

05

Dice / IoU on held-out regions

01Reported Dice and IoU on spatially disjoint held-out regions. Pixel accuracy is uninformative at ≈12% glacier pixels.
02Compared BCE, Dice and combined weighted losses, and analysed operating points via ROC.

Project Info

DomainMachine Learning
RoleAuthor
Year2024
StatusShipped

Tech Stack

PythonPyTorchU-NetSentinel-2GeoTIFF