5 papers
Now We Know? A Systematic Comparison of TerraMind and THOR
Frederick Schindlegger, Kenzo Bounegta, Eva Gmelich Meijling +5
Benchmarks for Geospatial Foundation Models (GFMs) increasingly rank models by aggregate score, but such rankings obscure why models differ: how much of the gap is architecture, ho…
NOFE - Neural Operator Function Embedding
Lars Uebbing, Harald L. Joakimsen, Siyan Chen +6
Most dimensionality reduction methods treat data as discrete point clouds, ignoring the continuous domain structure inherent to many real-world processes. To bridge this gap, we in…
THOR: A Versatile Foundation Model for Earth Observation Climate and Society Applications
Theodor Forgaard, Jarle H. Reksten, Anders U. Waldeland +4
Current Earth observation foundation models are architecturally rigid, struggle with heterogeneous sensors and are constrained to fixed patch sizes. This limits their deployment in…
DiffFuSR: Super-Resolution of all Sentinel-2 Multispectral Bands using Diffusion Models
Muhammad Sarmad, Arnt-Børre Salberg, Michael Kampffmeyer
This paper presents DiffFuSR, a modular pipeline for super-resolving all 12 spectral bands of Sentinel-2 Level-2A imagery to a unified ground sampling distance (GSD) of 2.5 meters.…
Uncertainties of Satellite-based Essential Climate Variables from Deep Learning
Junyang Gou, Arnt-Børre Salberg, Mostafa Kiani Shahvandi +9
Accurate uncertainty information associated with essential climate variables (ECVs) is crucial for reliable climate modeling and understanding the spatiotemporal evolution of the E…