16 citations · 22 across the 7 of their papers we have counts for
8 papers
Transferability and operational reliability of a Prithvi crop classification foundation model under phenological and geographic shift across three continents
Venkatesh Kolluru, Rajat Shinde, Abdelhak Marouane +7
Fine-tuned geospatial foundation models (GeoFMs) pretrained on large satellite archives have been shown to improve crop classification accuracy and geographic transferability. Howe…
Land cover and flood type govern the detection limits of satellite-based flood mapping across diverse global flood events
Venkatesh Kolluru, Rajat Shinde, Abdelhak Marouane +6
Floods are among the most destructive natural hazards, and their increasing frequency under climate change makes satellite-based inundation mapping essential for disaster response.…
SuryaBench: Benchmark Dataset for Advancing Machine Learning in Heliophysics and Space Weather Prediction
Sujit Roy, Dinesha V. Hegde, Johannes Schmude +22
This paper introduces a high resolution, machine learning-ready heliophysics dataset derived from NASA's Solar Dynamics Observatory (SDO), specifically designed to advance machine…
Toward Open Earth Science as Fast and Accessible as Natural Language
Marquita Ellis, Iksha Gurung, Muthukumaran Ramasubramanian +1
Is natural-language-driven earth observation data analysis now feasible with the assistance of Large Language Models (LLMs)? For open science in service of public interest, feasibi…
Challenges in Guardrailing Large Language Models for Science
Nishan Pantha, Muthukumaran Ramasubramanian, Iksha Gurung +2
The rapid development in large language models (LLMs) has transformed the landscape of natural language processing and understanding (NLP/NLU), offering significant benefits across…
INDUS: Effective and Efficient Language Models for Scientific Applications
Bishwaranjan Bhattacharjee, Aashka Trivedi, Masayasu Muraoka +33
Large language models (LLMs) trained on general domain corpora showed remarkable results on natural language processing (NLP) tasks. However, previous research demonstrated LLMs tr…
Leveraging Citizen Science for Flood Extent Detection using Machine Learning Benchmark Dataset
Muthukumaran Ramasubramanian, Iksha Gurung, Shubhankar Gahlot +3
Accurate detection of inundated water extents during flooding events is crucial in emergency response decisions and aids in recovery efforts. Satellite Remote Sensing data provides…
Foundation Models for Generalist Geospatial Artificial Intelligence
Johannes Jakubik, Sujit Roy, C. E. Phillips +30
Significant progress in the development of highly adaptable and reusable Artificial Intelligence (AI) models is expected to have a significant impact on Earth science and remote se…