Preprints
Filtering by Subject: Artificial Intelligence and Robotics
Deep Neural Network-Based Inversion of Turbidites in Confined Basins
Published: 2026-07-11
Subjects: Artificial Intelligence and Robotics, Fluid Dynamics, Geology, Sedimentology
Turbidites generated by large earthquakes and other geological events are commonly preserved in small, topographically confined basins along active continental margins. Reconstructing flow conditions from these deposits is essential for assessing past hazards; however, existing inverse models have been validated only for unconfined settings, and their applicability to confined basins remains [...]
A machine learning approach for detecting biofouling in oceanographic data
Published: 2026-07-11
Subjects: Artificial Intelligence and Robotics, Fluid Dynamics, Numerical Analysis and Computation, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics
Autonomous ocean observing platforms collect long-term biogeochemical time series, but sensor degradation from biofouling introduces progressive biases that contaminate the climate record. This work focuses on the BGC-Argo fleet of profiling floats, where optical sensors measuring chlorophyll-a and backscatter are particularly susceptible to biofouling. Current detection relies on per-float [...]
Deep learning methods for the simulation and optimization of shallow geothermal energy systems
Published: 2026-07-01
Subjects: Applied Mathematics, Artificial Intelligence and Robotics, Computational Engineering, Geology, Natural Resources Management and Policy
Shallow geothermal energy (SGE) systems are crucial for decarbonizing the heating and cooling sector. Their planning, design and operation, however, rely on the simulation of heat transport in the subsurface, a task that is computationally demanding and particularly prohibitive for multi-query applications such as sensitivity analysis and optimization. Deep learning (DL) has recently emerged as a [...]
Spectrally structured CNN encoding for interpretable and edge-ready fractional vegetation cover mapping using UAS multispectral and imaging spectroscopy
Published: 2026-06-30
Subjects: Artificial Intelligence and Robotics, Biogeochemistry, Computer Sciences, Earth Sciences, Engineering, Environmental Monitoring, Environmental Sciences, Natural Resources and Conservation, Physical Sciences and Mathematics, Remote Sensing
Fractional vegetation cover (FVC) is a key indicator of semi-arid ecosystem condition, but non-photosynthetic vegetation (NPV) remains difficult to map because dry or senescent vegetation, litter, woody debris, and standing dead material can overlap spectrally with photosynthetic vegetation (PV) and bare ground (BE), especially where shadows, exposed bare earth surfaces, and mixed vegetation-soil [...]
Two decades of kilometer-scale daily PM2.5 from satellite observations and machine learning reveal geographically diverging exposure in Ghana
Published: 2026-06-05
Subjects: Artificial Intelligence and Robotics, Atmospheric Sciences, Civil and Environmental Engineering, Earth Sciences, Engineering, Environmental Engineering, Environmental Monitoring, Environmental Public Health, Environmental Sciences, Geographic Information Sciences, Geography, Oceanography and Atmospheric Sciences and Meteorology, Other Earth Sciences, Remote Sensing, Spatial Science
Exposure to fine particulate matter (PM2.5) is a major contributor to global burden of disease, yet air quality data remain sparse in many low- and middle-income countries, limiting nationwide monitoring and effective policy development. We address this gap by developing a high-resolution gridded (1 km × 1 km) dataset for daily surface PM2.5 concentrations in Ghana from 2005 to 2025 by training [...]
Engineering AI-Assisted Client-Side Scientific Workflows: WebGPU Inference Architecture and Framework for Privacy-Preserving Hydrological Analysis
Published: 2026-05-30
Subjects: Artificial Intelligence and Robotics, Environmental Sciences, Hydrology, Software Engineering
Deep learning has demonstrated strong potential for improving hydrological predictions, yet its practical adoption remains limited by software complexity, infrastructure requirements, data governance constraints, and fragmented analytical workflows. This study presents Hydro AI Lab, an AI-assisted client-side scientific workflow platform that enables end-to-end hydrological analysis, including [...]
A benchmark deep learning dataset for the classification of supraglacial lake drainage mechanism across the central-west Greenland Ice Sheet
Published: 2026-05-29
Subjects: Artificial Intelligence and Robotics, Earth Sciences, Glaciology, Numerical Analysis and Scientific Computing, Physical Sciences and Mathematics
Supraglacial lakes on the Greenland Ice Sheet drain through physically distinct pathways: hydrofracture, moulins, lateral stream routing, and crevasse-fields. Each drainage mechanism carries unique implications for ice sheet dynamics. Existing automated classifications reduce each lake's drainage behavior to a time-series of scalar values representing the observed water surface-area and classify [...]
CryoSentinel: A Multimodal Foundation-Model Segmenter for Glacial Lakes in High Mountain Asia from Sentinel-1 SAR, Sentinel-2 Optical, and Copernicus DEM Imagery
Published: 2026-05-16
Subjects: Artificial Intelligence and Robotics, Environmental Monitoring, Geomorphology, Glaciology, Hydrology
Glacial-lake outburst floods (GLOFs) are the dominant climate-driven hazard in High Mountain Asia, and reliable lake-extent segmentation is the prerequisite for every downstream early-warning workflow. We present CryoSentinel, a multimodal foundation-model semantic segmenter built on the IBM/ESA TerraMind 1.0 Large encoder (1.1 B parameters) with a UperNet decoder, fine-tuned on 5,614 [...]
A Blueprint for Integrated Climate Intelligence
Published: 2026-05-13
Subjects: Artificial Intelligence and Robotics, Environmental Indicators and Impact Assessment, Environmental Monitoring, Planetary Sciences, Sustainability
Climate information is advancing faster than the decision systems designed to use it. Emergency response operates on timescales of hours, whereas societal adaptation unfolds over decades. Yet climate science, impact assessment and policy remain poorly integrated, limiting coherent action across timescales. We argue that artificial intelligence should be developed not only as a domain-specific [...]
From 2D labels to 3D structure: Scalable label transfer and benchmarking of 3D vegetation models in rangeland ecosystems
Published: 2026-05-02
Subjects: Artificial Intelligence and Robotics, Biogeochemistry, Computer Sciences, Earth Sciences, Engineering, Environmental Monitoring, Environmental Sciences, Natural Resources and Conservation, Physical Sciences and Mathematics, Remote Sensing
Three-dimensional (3D) characterisation of vegetation structure at the level of individual growth forms is critical for understanding ecosystem function and resilience, yet remains challenging in rangelands because vegetation is sparse, low-stature, and structurally heterogeneous. Recent 3D deep-learning models perform strongly in forests, but their transfer beyond closed-canopy benchmarks is [...]
An End-to-End Workflow for Processing Multilingual Stakeholder Workshop Data: A Soil Health Case Study
Published: 2026-04-11
Subjects: Artificial Intelligence and Robotics, Environmental Monitoring, Soil Science
Stakeholder workshops often produce diverse qualitative and ordinal data that are difficult to process consistently, transparently, and reproducibly, particularly in multilingual settings. To address these challenges, we developed an end-to-end workflow for systematic processing of multilingual participatory workshop data. The workflow integrates multilingual preprocessing, structured data [...]
Frictional weakening in the highly mobile 2025 Blatten (Switzerland) rock–ice avalanche
Published: 2026-03-17
Subjects: Artificial Intelligence and Robotics, Dynamics and Dynamical Systems, Geomorphology, Geophysics and Seismology, Geotechnical Engineering, Multivariate Analysis, Numerical Analysis and Computation, Numerical Analysis and Scientific Computing, Planetary Geomorphology, Planetary Geophysics and Seismology, Risk Analysis
Cascading slope failures in alpine environments are intensifying as glaciers retreat and slope stability adjusts to a warming climate. Yet, the mechanisms governing such large, rapidly evolving events remain poorly understood. The 28 May 2025 rock–ice avalanche from Birch Glacier, Switzerland ($\approx9.3\times10^{6}~\mathrm{m^3}$), which devastated part of the village of Blatten, provides a [...]
Sub-pixel mapping of disturbance and tree mortality dynamics from Sentinel-2 time series around the globe
Published: 2026-02-24
Subjects: Artificial Intelligence and Robotics, Biogeochemistry, Computer Sciences, Earth Sciences, Engineering, Environmental Monitoring, Environmental Sciences, Natural Resources and Conservation, Physical Sciences and Mathematics
Elevated forest disturbances and excess tree mortality are increasingly reported worldwide. Yet existing assessments are either based on patchy terrestrial observations or on large-scale satellite products, which are limited in resolution to pixel-level, binary tree loss detection. This leaves a blind spot on fine-scale disturbances where only a few trees are declining in an otherwise intact [...]
Emergent Spatio-Semantic Structure in Large Language Model Embedding Spaces
Published: 2026-02-24
Subjects: Artificial Intelligence and Robotics, Geographic Information Sciences
Large Language Models (LLMs) are increasingly used in geospatial applications typically as generators of geographic text or as natural language interfaces to spatial data. Here, we explore whether LLM embedding spaces can instead function as geospatial representations that can be exploited directly. Using embeddings extracted from Airbnb property descriptions in London, we show that [...]
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 [...]