Dataset for Land/Water Semantic Segmentation in Tonga and other Pacific regions

Description

Dataset for training CNN models (e.g. U-Net) for land/water semantic segmentation of Sentinel-2 images. Features 424 Sentinel-2 TOA images of size 256x256 pixels, with corresponding targets (binary segmentation maps). The channels included are Sentinel-2 bands B2, B3, B4, B5, B6, B7, B8, B8A, B11, B12, plus NDWI and NDVI (in this order). Weight maps are included for training using a weighted loss function, in order to improve segmentation on important features, specifically small volcanic islands. The weights of the pre-trained models used for our research are included as .keras files. Code snippets include essential functionality to load the models, and pre-process Earth Engine images for input.

Institutions

• Universita degli Studi di Trieste Dipartimento di Matematica e Geoscienze
• Universita degli Studi di Trieste

Categories

Licence