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20232026
most citedLossy Neural Compression for Geospatial Analytics: A Review

5 citations · 10 across the 18 of their papers we have counts for

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Showing 2025 · cs.CVShow all

6 papers · 2 filters

cs.CV2025

Detection and Simulation of Urban Heat Islands Using a Fine-Tuned Geospatial Foundation Model for Microclimate Impact Prediction

Jannis Fleckenstein, David Kreismann, Tamara Rosemary Govindasamy +3

As urbanization and climate change progress, urban heat island effects are becoming more frequent and severe. To formulate effective mitigation plans, cities require detailed air t…

cs.CV2025

Quantizing Space and Time: Fusing Time Series and Images for Earth Observation

Gianfranco Basile, Johannes Jakubik, Benedikt Blumenstiel +2

We propose a task-agnostic framework for multimodal fusion of time series and single timestamp images, enabling cross-modal generation and robust downstream performance. Our approa…

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

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

Beyond the Visible: Multispectral Vision-Language Learning for Earth Observation

Clive Tinashe Marimo, Benedikt Blumenstiel, Maximilian Nitsche +2

Vision-language models for Earth observation (EO) typically rely on the visual spectrum of data as the only model input, thus failing to leverage the rich spectral information avai…