Annual Earth-observation embeddings encode wildfire disturbance and support simplified burned area mapping
cs.CV
Submitted: 2026-09-22
Updated: 2026-09-22
Code: https://github.com/ucam-eo/geotessera
Terminology
Sources
- AlphaEarth Foundations: An embedding field model for accurate and efficient global mapping from sparse label data
- TESSERA: Temporal Embeddings of Surface Spectra for Earth Representation and Analysis
- TESSERA v2: Scaling Pixel-wise Earth Foundation Models
- Foundation Models for Generalist Geospatial Artificial Intelligence
- CITYREP: A Unified Benchmark for Urban Representations Across Cities, Tasks, and Modalities
- PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models
- Better Together: Evaluating the Complementarity of Earth Embedding Models
- U-Net: Convolutional Networks for Biomedical Image Segmentation
- Deep Learning-Based Burned Area Mapping Using Bi-Temporal Siamese Networks and AlphaEarth Foundation Datasets
- Recurrent Video Masked Autoencoders
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