Preprints
Filtering by Subject: Artificial Intelligence and Robotics
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 [...]
A Computer Vision Framework for Estimating Surface Habitability from Mars Using Convolutional Analysis
Published: 2025-10-22
Subjects: Artificial Intelligence and Robotics, Biology, Earth Sciences, Other Planetary Sciences, Planetary Geology, Planetary Geomorphology, Planetary Sciences, Planetary Sedimentology, Statistical Methodology, Theory and Algorithms
Identifying signs of life in extraterrestrial environments is one of the growing challenges in planetary science. Conventional approaches of detecting habitability rely heavily on direct contact with biosignatures or geological analyses, but limited data and mission costs hold back such methods. This work introduces a computer vision-based pipeline that analyzes planetary surface images to [...]
AI-Powered Flood Risk Assessment for Gilgit-Baltistan Using Multi-Source Satellite Data and Machine Learning
Published: 2025-09-20
Subjects: Artificial Intelligence and Robotics, Geography, Geomorphology, Glaciology, Hydrology
Flood disasters are intensifying worldwide due to climate change, with mountainous regions among the most vulnerable yet least studied. This paper presents an AI-powered flood risk assessment framework for Gilgit-Baltistan, Pakistan, a high-mountain region prone to flash floods and glacial lake outburst floods (GLOFs). Multi-source satellite datasets—including CHIRPS precipitation, JRC Global [...]
Efficient Self-Attention Based Joint Optimization for Lithology and Petrophysical Parameter Estimation in the Athabasca Oil Sands
Published: 2025-09-17
Subjects: Artificial Intelligence and Robotics, Earth Sciences, Geology, Geophysics and Seismology
Accurately identifying lithology and petrophysical parameters, such as porosity and water saturation, are essential in reservoir characterization. Manual interpretation of well-log data, the conventional approach, is not only labor-intensive but also susceptible to human errors. To address these challenges of lithology identification and petrophysical parameter estimation in the Athabasca Oil [...]
Geomodelling of multi-scenario non-stationary reservoirs with enhanced GANSim
Published: 2025-08-05
Subjects: Artificial Intelligence and Robotics, Civil and Environmental Engineering, Earth Sciences, Engineering, Geology, Geophysics and Seismology, Hydrology, Mining Engineering, Natural Resources and Conservation, Natural Resources Management and Policy, Oil, Gas, and Energy, Sedimentology, Stratigraphy
Reservoir geomodelling is critical for groundwater management, CO₂ storage, geothermal exploitation, and hydrocarbon exploration, yet traditional geostatistical methods like multiple-point statistics (MPS) struggle with simulating complex geological patterns. GANSim, a Generative Adversarial Networks-based geomodelling method, has proven effective for single-scenario stationary reservoirs, but [...]
Artificial Intelligence in Earth Science: A GeoAI Perspective
Published: 2025-08-03
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Engineering, Environmental Sciences, Physical Sciences and Mathematics
GeoAI, or geospatial artificial intelligence, has transformative potential for Earth science by integrating geospatial data with artificial intelligence to enhance environmental monitoring, predictive modeling, and decision-making. This commentary, based on the Greg Leptoukh Lecture at AGU 2024, explores the evolving role of GeoAI in addressing pressing challenges—from environmental change in the [...]
Validation Challenges in Large-Scale Tree Crown Segmentations from Remote Sensing Imagery Using Deep Learning: A Case Study in Germany
Published: 2025-07-25
Subjects: Artificial Intelligence and Robotics, Forest Sciences
Deep-learning–based individual tree-crown (ITC) mapping has become increasingly prominent in remote sensing, yet rigorous validation of these predictions at large spatial scales remains challenging. Using data from an extensive case study involving the mapping of approximately 218.7 million trees across the German federal states of Sachsen and Sachsen-Anhalt from multispectral aerial imagery, [...]
Aquascan: Graph-Based Learning for Distributed Marine Sensing
Published: 2025-07-04
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Environmental Monitoring, Environmental Sciences, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Water Resource Management
Marine monitoring faces unprecedented challenges as climate change and human activities reshape ocean ecosystems. Traditional tracking methods struggle with the scale and complexity of modern marine sensing needs. This paper proposes distributed networks of low-cost drifting sensors and presents a comparative study of heterogeneous graph neural networks (GNNs) versus Kalman filters for predicting [...]
Natural forests of the world - a 2020 baseline for deforestation and degradation monitoring
Published: 2025-04-29
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Environmental Sciences, Geographic Information Sciences, Remote Sensing
Informed decisions to reduce deforestation, protect biodiversity, and curb carbon emissions require not just knowing where forests are, but understanding their composition. Identifying natural forests, which serve as critical biodiversity hotspots and major carbon sinks, is particularly valuable. We developed a novel global natural forest map for 2020 at 10 m resolution. This map can support [...]
Enhancing and Interpreting Deep Learning for Sea Ice Charting using the AutoICE Benchmark
Published: 2025-04-24
Subjects: Analysis, Artificial Intelligence and Robotics, Environmental Monitoring, Oceanography
Accurate mapping of sea ice is crucial for marine navigation and monitoring climate change. Automating sea ice mapping remains challenging due to remotely-sensed signal ambiguity, the dynamic nature of sea ice, and limited field measurements. The AutoICE challenge recently introduced a benchmark to advance deep learning for sea ice mapping. Top-performing solutions used the U-Net architecture [...]