NEWS

geodl 0.3.0 (2025-11-12)

Support for three model architectures: UNet, UNet with MobileNetv2 encoder, and UNet3+
UNet with MobileNetv2 encoder is no longer limited to three input predictor variables
Assessment and prediction functions now expect a nn_module object as opposed to a luz fitted object
Dynamically generate chips during training process as opposed to saving them to disk beforehand (still experimental)
Ignore outer rows and columns of cells when calculating loss or assessment metrics if desired
Use R torch to calculate several different land surface parameters (LSPs) from a digital terrain model: slope, hillshade, aspect, northwardness, eastwardness, transformed solar radiation aspect index (TRASP), site exposure index (SEI), topographic position index (TPI), and surface curvatures (mean, profile, and planform)
Calculate three-band terrain visualization raster grid from a DTM using torch or terra
New specialized model for extracting geomorphic features from digital terrain models (DTMs)
New function to count the number of trainable parameters in a model
Fixed issue with chip generation pipeline that caused some chips with NA cells to be written
Updated atrous spatial pyramid pooling (ASPP) module to align with the version used within DeepLabv3+