Preprints
Filtering by Subject: Artificial Intelligence and Robotics
A Vision for Machine Learning and Artificial Intelligence in Great Lakes Research and Management
Published: 2026-02-06
Subjects: Artificial Intelligence and Robotics, Databases and Information Systems, Environmental Monitoring, Environmental Sciences, Fresh Water Studies, Oceanography and Atmospheric Sciences and Meteorology, Water Resource Management
The Laurentian Great Lakes are a vital freshwater resource and a regionally significant natural system facing complex, persistent, and compounding challenges from climate change, nutrient loading, and invasive species. The increasing availability of observational data, coupled with advances in computational power and machine learning (ML) and artificial intelligence (AI) methods, presents an [...]
Hybrid Physics–AI Ecosystem Simulations Improve Biogeochemical Predictions in Temperate Shelf Seas
Published: 2026-02-02
Subjects: Artificial Intelligence and Robotics, Biochemistry, Biogeochemistry, Environmental Health and Protection, Environmental Indicators and Impact Assessment, Environmental Monitoring, Marine Biology, Numerical Analysis and Scientific Computing, Oceanography, Planetary Biogeochemistry, Terrestrial and Aquatic Ecology
Biogeochemical models form a core part of marine forecasting and climate projections, yet they suffer from persistent biases in predicting key ecosystem variables, creating challenges across regional and global scales. To address this, we developed an AI-augmented three-dimensional hybrid framework that integrates machine-learning corrections directly into a process-based model’s productivity [...]
What Companies Say vs. What Matters: LLM Analysis of Biodiversity Disclosures in Oil and Gas
Published: 2026-01-31
Subjects: Artificial Intelligence and Robotics, Biodiversity, Oil, Gas, and Energy, Sustainability
The power system ecosystem encompasses infrastructure intensive industries such as electric utilities, hydropower operators, oil and gas producers, and mining companies supplying critical minerals. These industries share a common challenge: their physical assets interact extensively with natural ecosystems, creating dependencies and impacts that increasingly draw investor and stakeholder [...]
Automating glacier facies classification: pan-European dataset and deep learning baseline
Published: 2026-01-27
Subjects: Artificial Intelligence and Robotics, Glaciology
Glacier facies play a critical role in understanding the mass balance of glaciers, offering insights into accumulation and melting processes. Accurate mapping of glacier facies is therefore essential for monitoring glacier response to climate change and informing climate policies. In this study, we present the largest glacier facies dataset ever compiled for Europe, comprising 31 glaciers, 92 [...]
Facilitating AI-Driven Sustainability: A Service-Oriented Ar-chitecture for Interoperable Environmental Data Access
Published: 2026-01-12
Subjects: Artificial Intelligence and Robotics, Environmental Health and Protection, Environmental Indicators and Impact Assessment, Environmental Monitoring, Meteorology, Software Engineering, Sustainability
Advances in Artificial Intelligence (AI), particularly agentic AI, have created opportunities to enhance global sustainability by improving the efficiency and accuracy of environmental monitoring and response systems. Agentic AIs autonomously plan and execute towards specific goals with minimal or no human intervention; however, accessing environmental data is challenging and requires expertise, [...]
HyTC-TaNet: A Hybrid Deep Learning Model Capturing Multi-day Temporal Dependencies for Daily Mean Air Temperature Estimation with Spatial Applicability Analysis
Published: 2026-01-06
Subjects: Agriculture, Artificial Intelligence and Robotics
High-resolution seismic reservoir monitoring with multitask and transfer learning
Published: 2026-01-02
Subjects: Artificial Intelligence and Robotics, Computational Engineering, Geophysics and Seismology, Oil, Gas, and Energy, Sustainability
High-resolution real-time monitoring of reservoir changes is essential during CO2 injection or hydrocarbon production. Here, we leverage convolutional neural networks (CNNs) that employ multitask (MTL) and transfer (TL) learning to accurately predict relevant reservoir parameters from time-lapse seismic data. CNNs are initially trained to estimate the P-wave velocity from 2D multicomponent [...]
A variational approach at uncertainty estimation in data-driven rainfall-runoff modeling
Published: 2025-12-27
Subjects: Artificial Intelligence and Robotics, Hydrology
Reliable uncertainty estimation is essential for decision making, evaluating model performance, and defining the limits of what can be inferred from data. While uncertainty estimation typically requires specifying prior assumptions about distributional form, we introduce an approach to learn the structure of uncertainty directly from data. Specifically, we introduce a variational long short-term [...]
Earth Embeddings: Towards AI-centric Representations of our Planet
Published: 2025-12-08
Subjects: Artificial Intelligence and Robotics, Earth Sciences, Environmental Sciences
This paper presents a new perspective for the flexible and efficient representation of geospatial data, tailored to and empowered by AI: Earth embeddings. Earth embeddings provide a unified and accessible vector representation of local geographic characteristics. They fuse different geospatial data sources across time and space, compress highly-correlated raw geospatial data into one dense [...]
The Data Behind AI Coastal Forecasting: Inputs, Sources, and Preprocessing Approaches
Published: 2025-11-13
Subjects: Artificial Intelligence and Robotics, Oceanography
Coastal zones, shaped by marine and terrestrial processes, are home to over 40% of the global population and contribute significantly to the global economy. However, their attractiveness also makes them vulnerable to extreme coastal water levels (ECWLs), which can lead to catastrophic flooding. ECWLs, driven by sea-level changes, waves, and tidal variations, have become more frequent and severe [...]
Recent climate change reduced Spanish forests' carbon sink capacity
Published: 2025-11-13
Subjects: Artificial Intelligence and Robotics, Ecology and Evolutionary Biology, Environmental Sciences, Forest Sciences, Life Sciences
Forests play a crucial role as carbon sinks and are central to climate mitigation strategies, yet their long-term reliability in this function is increasingly uncertain under climate change. Using deep learning techniques on a multi-source dataset—combining multi-spectral satellite data, airborne laser scanning, and ground-based measurements—we produced the most up-to-date high-resolution maps of [...]
Accelerating Geothermal Modeling with Low- and High-Fidelity Fourier Neural Operators
Published: 2025-11-10
Subjects: Artificial Intelligence and Robotics, Oil, Gas, and Energy
Geothermal reservoir models are costly to build and calibrate, and generating a single forecast can take hours. Operators tasked with field planning and optimization are constrained by the speed of these forecast simulations, limiting the number of scenarios they can explore. Machine learning can be a powerful tool to speed up computationally expensive tasks, but standard approaches using Neural [...]
The Tocantins Framework: A Machine Learning-Based Assessment of Intra-urban Thermal Anomalies
Published: 2025-11-10
Subjects: Applied Statistics, Artificial Intelligence and Robotics, Computer Sciences, Environmental Indicators and Impact Assessment, Environmental Sciences, Statistics and Probability, Sustainability
The Urban Heat Island (UHI) effect has been extensively studied at the city scale. Yet, the Intra-Urban Heat Island and the Intra-Urban Cool Island effects remain poorly characterized due to the absence of standardized quantification frameworks. This study introduces the Tocantins Framework, a dual-metric system combining machine learning and spatial morphology to identify and quantify [...]
Multi-Agent Geophysical AI Workflow for Automated Reservoir Characterization
Published: 2025-11-06
Subjects: Artificial Intelligence and Robotics, Computational Engineering, Computer Sciences, Earth Sciences, Engineering, Geophysics and Seismology
Traditional geophysical workflows like reservoir characterization are driven in a collaborative manner where teams of geoscientists share their individual analyses to inform key decisions made by executives. However, these workflows are repetitive, time-consuming, prone to human error, and introduce subjective bias. While researchers have used automation to address these limitations via deep [...]
ForestCast: Forecasting Deforestation Risk at Scale with Deep Learning
Published: 2025-10-31
Subjects: Artificial Intelligence and Robotics, Environmental Monitoring
Deforestation is a major threat to biodiversity and the stability of the climate. Current monitoring solutions provide reactive alerts only after deforestation has occurred, rendering them largely insufficient for prevention. Proactive deforestation prevention necessitates forecasting at-risk areas, however, previous forecasting efforts have been constrained by their reliance on simple [...]