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Related papers: Towards LLM Agents for Earth Observation

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The Science Operation Department is composed of Astronomers, Telescope Instruments Operators (TIO) and Data Handling Administrators (DHAs). Their main goal is to produce top-quality astronomical data by operating a suite of 9 telescopes, 14…

Instrumentation and Methods for Astrophysics · Physics 2011-01-13 Julio Navarrete

Foundation Models (FMs) are large-scale, pre-trained artificial intelligence (AI) systems that have revolutionized natural language processing and computer vision, and are now advancing geospatial analysis and Earth Observation (EO). They…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Pedram Ghamisi , Weikang Yu , Xiaokang Zhang , Aldino Rizaldy , Jian Wang , Chufeng Zhou , Richard Gloaguen , Gustau Camps-Valls

Unmanned Aerial Vehicles (UAVs) are of crucial importance in search and rescue missions in maritime environments due to their flexible and fast operation capabilities. Modern computer vision algorithms are of great interest in aiding such…

Computer Vision and Pattern Recognition · Computer Science 2021-10-20 Leon Amadeus Varga , Benjamin Kiefer , Martin Messmer , Andreas Zell

Amid the challenges posed by global population growth and climate change, traditional agricultural Internet of Things (IoT) systems is currently undergoing a significant digital transformation to facilitate efficient big data processing.…

Computer Vision and Pattern Recognition · Computer Science 2025-06-05 Dawen Jiang , Zhishu Shen , Qiushi Zheng , Tiehua Zhang , Wei Xiang , Jiong Jin

Recent progress in self-supervision shows that pre-training large neural networks on vast amounts of unsupervised data can lead to impressive increases in generalisation for downstream tasks. Such models, recently coined as foundation…

Climate science demands automated workflows to transform comprehensive questions into data-driven statements across massive, heterogeneous datasets. However, generic LLM agents and static scripting pipelines lack climate-specific context…

Machine Learning · Computer Science 2025-11-26 Hyeonjae Kim , Chenyue Li , Wen Deng , Mengxi Jin , Wen Huang , Mengqian Lu , Binhang Yuan

The next decade will feature a growing number of massive ground-based photometric, spectroscopic, and time-domain surveys, including those produced by DECam, DESI, and LSST. The NOAO Data Lab was launched in 2017 to enable efficient…

Instrumentation and Methods for Astrophysics · Physics 2019-08-05 Knut Olsen , Adam Bolton , Stephanie Juneau , Robert Nikutta , Dara Norman , David Nidever , Stephen Ridgway , Adam Scott , Benjamin Weaver

Recent progress in large language models (LLMs) has enabled tool-augmented agents capable of solving complex real-world tasks through step-by-step reasoning. However, existing evaluations often focus on general-purpose or multimodal…

Recent advances in artificial intelligence (AI) have significantly intensified research in the geoscience and remote sensing (RS) field. AI algorithms, especially deep learning-based ones, have been developed and applied widely to RS data…

Computer Vision and Pattern Recognition · Computer Science 2023-07-14 Yonghao Xu , Tao Bai , Weikang Yu , Shizhen Chang , Peter M. Atkinson , Pedram Ghamisi

Massive amounts of unlabelled data are captured by Earth Observation (EO) satellites, with the Sentinel-2 constellation generating 1.6 TB of data daily. This makes Remote Sensing a data-rich domain well suited to Machine Learning (ML)…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Casper Fibaek , Luke Camilleri , Andreas Luyts , Nikolaos Dionelis , Bertrand Le Saux

Artificial Intelligence (AI) Foundation models (FMs), pre-trained on massive unlabelled datasets, have the potential to drastically change AI applications in ocean science, where labelled data are often sparse and expensive to collect. In…

Computer Vision and Pattern Recognition · Computer Science 2025-09-26 Geoffrey Dawson , Remy Vandaele , Andrew Taylor , David Moffat , Helen Tamura-Wicks , Sarah Jackson , Rosie Lickorish , Paolo Fraccaro , Hywel Williams , Chunbo Luo , Anne Jones

Although machine learning (ML) and artificial intelligence (AI) present fascinating opportunities for innovation, their rapid development is also significantly impacting our environment. In response to growing resource-awareness in the…

Artificial Intelligence · Computer Science 2025-09-29 Raphael Fischer

Interest in sustainability information has surged in recent years. However, the data required for a life cycle assessment (LCA) that maps the materials and processes from product manufacturing to disposal into environmental impacts (EI) are…

In recent years, the rapid advancement of Artificial Intelligence (AI) technologies, particularly Large Language Models (LLMs), has revolutionized the paradigm of scientific discovery, establishing AI-for-Science (AI4Science) as a dynamic…

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 satellite imagery has resulted in large volumes of data that must…

Atmospheric sciences are crucial for understanding environmental phenomena ranging from air quality to extreme weather events, and climate change. Recent breakthroughs in sensing, communication, computing, and Artificial Intelligence (AI)…

Detecting changes on the Earth, such as urban development, deforestation, or natural disaster, is one of the research fields that is attracting a great deal of attention. One promising tool to solve these problems is satellite imagery.…

Computer Vision and Pattern Recognition · Computer Science 2022-03-03 Waku Hatakeyama , Shirou Kawakita , Ryohei Izawa , Masanari Kimura

The detections of small, rocky exoplanets have surged in recent years and will likely continue to do so. To know whether a rocky exoplanet is habitable, we have to characterise its atmosphere and surface. A promising characterisation method…

Earth and Planetary Astrophysics · Physics 2015-06-04 T. Karalidi , D. M. Stam , F. Snik , S. Bagnulo , W. B. Sparks , C. U. Keller

Page Objects (POs) are a widely adopted design pattern for improving the maintainability and scalability of automated end-to-end web tests. However, creating and maintaining POs is still largely a manual, labor-intensive activity, while…

Software Engineering · Computer Science 2026-02-24 Betül Karagöz , Filippo Ricca , Matteo Biagiola , Andrea Stocco
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