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20222025
most citedPrithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications

22 citations · 50 across the 12 of their papers we have counts for

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7 papers · 1 filter

cs.CV2025★ 1 cited

Hyperspectral Vision Transformers for Greenhouse Gas Estimations from Space

Ruben Gonzalez Avilés, Linus Scheibenreif, Nassim Ait Ali Braham +8

Hyperspectral imaging provides detailed spectral information and holds significant potential for monitoring of greenhouse gases (GHGs). However, its application is constrained by l…

cs.CV2025

Fine-tune Smarter, Not Harder: Parameter-Efficient Fine-Tuning for Geospatial Foundation Models

Francesc Marti-Escofet, Benedikt Blumenstiel, Linus Scheibenreif +2

Earth observation (EO) is crucial for monitoring environmental changes, responding to disasters, and managing natural resources. In this context, foundation models facilitate remot…

cs.CV2025

TerraMesh: A Planetary Mosaic of Multimodal Earth Observation Data

Benedikt Blumenstiel, Paolo Fraccaro, Valerio Marsocci +8

Large-scale foundation models in Earth Observation can learn versatile, label-efficient representations by leveraging massive amounts of unlabeled data. However, existing public da…

cs.CV2025

TerraMind: Large-Scale Generative Multimodality for Earth Observation

Johannes Jakubik, Felix Yang, Benedikt Blumenstiel +13

We present TerraMind, the first any-to-any generative, multimodal foundation model for Earth observation (EO). Unlike other multimodal models, TerraMind is pretrained on dual-scale…

cs.CV2025★ 3 cited

TerraTorch: The Geospatial Foundation Models Toolkit

Carlos Gomes, Benedikt Blumenstiel, Joao Lucas de Sousa Almeida +7

TerraTorch is a fine-tuning and benchmarking toolkit for Geospatial Foundation Models built on PyTorch Lightning and tailored for satellite, weather, and climate data. It integrate…

eess.SP2025★ 5 cited

Lossy Neural Compression for Geospatial Analytics: A Review

Carlos Gomes, Isabelle Wittmann, Damien Robert +24

Over the past decades, there has been an explosion in the amount of available Earth Observation (EO) data. The unprecedented coverage of the Earth's surface and atmosphere by satel…

eess.IV2025

Multispectral to Hyperspectral using Pretrained Foundational model

Ruben Gonzalez, Conrad M Albrecht, Nassim Ait Ali Braham +6

Hyperspectral imaging provides detailed spectral information, offering significant potential for monitoring greenhouse gases like CH4 and NO2. However, its application is constrain…