Preprints

Filtering by Subject: Computer Sciences

Space-time landslide hazard modeling via Ensemble Neural Networks

Ashok Dahal, Hakan Tanyas, Cees J. van Westen, et al.

Published: 2022-06-02
Subjects: Applied Statistics, Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Geomorphology, Physical Sciences and Mathematics, Statistics and Probability

For decades, a full numerical description of the spatio-temporal dynamics of a landslide could be achieved only via physics-based models. The part of the geomorphology community focusing on data-driven model has instead focused on predicting where landslides may occur via susceptibility models. Moreover, they have estimated when landslides may occur via models that belong to the [...]

Democratizing Deep Learning Applications in Earth and Climate Sciences on the Web: EarthAIHub

Muhammed Sit, Ibrahim Demir

Published: 2022-04-20
Subjects: Computer Sciences, Earth Sciences, Engineering, Environmental Sciences

Most deep learning application studies have limited accessibility and reproducibility for researchers and students in many domains, especially in earth and climate sciences. In order to provide a step towards improving accessibility to deep learning models in such disciplines, this study presents a community-driven framework and repository, EarthAIHub, that is powered by TensorFlow.js, where deep [...]

A computational framework for time dependent deformation in viscoelastic magmatic systems

Cody Rucker, Brittany Angela Erickson, Leif Karlstrom, et al.

Published: 2022-04-01
Subjects: Applied Mathematics, Computer Sciences, Earth Sciences, Mathematics

Time-dependent ground deformation is a key observable in active magmatic systems, but is challenging to characterize. Here we present a numerical framework for modeling transient deformation and stress around a subsurface, spheroidal pressurized magma reservoir within a viscoelastic half-space with variable material coefficients, utilizing a high-order finite-element method and explicit [...]

Practical Reproducibility in Geography and Geosciences

Daniel Nüst, Edzer Pebesma

Published: 2022-03-28
Subjects: Computer Sciences, Earth Sciences, Environmental Sciences, Higher Education

Reproducible research is often perceived as a technological challenge, but it is rooted in the challenge to improve scholarly communication in an age of digitisation. When computers become involved and researchers want to allow other scientists to inspect, understand, evaluate, and build upon their work, they need to create a research compendium that includes the code, data, computing [...]

Automated machine learning to evaluate the information content of tropospheric trace gas columns for fine particle estimates over India: a modeling testbed

Zhonghua Zheng, Arlene M. Fiore, Daniel M. Westervelt, et al.

Published: 2022-03-20
Subjects: Artificial Intelligence and Robotics, Atmospheric Sciences, Civil and Environmental Engineering, Computer Sciences, Earth Sciences, Environmental Engineering, Environmental Sciences, Oceanography and Atmospheric Sciences and Meteorology

India is largely devoid of high-quality and reliable on-the-ground measurements of fine particulate matter (PM2.5). Ground-level PM2.5 concentrations are estimated from publicly available satellite Aerosol Optical Depth (AOD) products combined with other information. Prior research has largely overlooked the possibility of gaining additional accuracy and insights into the sources of PM using [...]

Forecasting Marine Heatwaves using Machine Learning

Ayush Prasad, Sanxchep Sharma, Harshvardhan Agarwal

Published: 2022-02-05
Subjects: Computer Sciences, Earth Sciences, Oceanography and Atmospheric Sciences and Meteorology

Recently, severe warm-water episodes have occurred frequently against a background trend of global ocean warming. Sea Surface Temperature anomalies have an impact on the integrity of marine ecosystems which is an important part of the Earth’s climate system. The drastic effects of Marine Heatwaves on aquatic life have been on a steady incline in the recent years, damaging aquatic ecosystems [...]

WaterBench: A Large-scale Benchmark Dataset for Data-Driven Streamflow Forecasting

Ibrahim Demir, Zhongrun Xiang, Bekir Zahit Demiray, et al.

Published: 2021-12-31
Subjects: Civil and Environmental Engineering, Computer Sciences, Earth Sciences, Hydrology

This study proposes a comprehensive benchmark dataset for streamflow forecasting, WaterBench, that follows FAIR data principles that is prepared with a focus on convenience for utilizing in data-driven and machine learning studies, and provides benchmark performance for state-of-art deep learning architectures on the dataset for comparative analysis. By aggregating the datasets of streamflow, [...]

Towards Progressive Geospatial Information Processing on Web Systems: A Case Study for Watershed Analysis in Iowa

Muneeb Shahid, Yusuf Sermet, Ibrahim Demir

Published: 2021-12-26
Subjects: Computer Sciences, Earth Sciences, Environmental Engineering, Environmental Sciences

Geographic Information Systems (GIS) are available as stand-alone desktop applications as well as web platforms for vector- and raster-based geospatial data processing and visualization. While each approach offers certain advantages, limitations exist that motivate the development of hybrid systems that will increase the productivity of users for performing interactive data analytics using [...]

Massive-Parallel Trajectory Calculations version 2.2 (MPTRAC-2.2): Lagrangian transport simulations on Graphics Processing Units (GPUs)

Lars Hoffmann, Paul F. Baumeister, Zhongyin Cai, et al.

Published: 2021-11-10
Subjects: Atmospheric Sciences, Computer Sciences, Meteorology, Numerical Analysis and Scientific Computing, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics

Lagrangian models are fundamental tools to study atmospheric transport processes and for practical applications such as dispersion modeling for anthropogenic and natural emission sources. However, conducting large-scale Lagrangian transport simulations with millions of air parcels or more can become numerically rather costly. In this study, we assessed the potential of exploiting graphics [...]

Airborne laser scanning proxies of canopy light transmission in forests

Adam Michael Erickson, Nicholas Coops

Published: 2021-10-29
Subjects: Biodiversity, Biogeochemistry, Computer Sciences, Earth Sciences, Ecology and Evolutionary Biology, Environmental Sciences, Forest Sciences, Life Sciences, Physical Sciences and Mathematics, Plant Sciences, Software Engineering, Statistics and Probability

Reliable estimates of canopy light transmission are critical to understanding the structure and function of vegetation communities but are difficult and costly to attain by traditional field inventory methods. Airborne laser scanning (ALS) data uniquely provide multi-angular vertically resolved representation of canopy geometry across large geographic areas. While previous studies have proposed [...]

Bridging knowledge gaps with hybrid machine-learning forest ecosystem models (ML-FEMs): inferential simulation of past understory light regimes

Adam Michael Erickson, Craig Nistchke

Published: 2021-10-29
Subjects: Artificial Intelligence and Robotics, Biodiversity, Biogeochemistry, Computer Sciences, Earth Sciences, Ecology and Evolutionary Biology, Forest Sciences, Life Sciences, Physical Sciences and Mathematics, Plant Sciences

Soil moisture is a key limiting factor of plant productivity in boreal and montane regions, producing additional climate feedbacks through evaporation, regeneration, mortality, and respiration. Understory solar irradiation – the primary driver of surface temperature and evaporative demand – remains poorly represented in vegetation models due to a lack of 3-D canopy geometry. Existing models are [...]

Near-term forecasts of stream temperature using process-guided deep learning and data assimilation

Jacob Zwart, Samantha Kay Oliver, William David Watkins, et al.

Published: 2021-08-13
Subjects: Computer Sciences, Hydrology, Statistics and Probability, Water Resource Management

Near-term forecasts of environmental outcomes can inform real-time decision making. Data assimilation modeling techniques can be used for forecasts to leverage real-time data streams, where the difference between model predictions and observations can be used to adjust the model to make better predictions tomorrow. In this use case, we developed a process-guided deep learning and data [...]

Ten Simple Rules for Researchers Who Want to Develop Web Apps

Sheila M. Saia, Natalie G. Nelson, Sierra N. Young, et al.

Published: 2021-07-18
Subjects: Agricultural Science, Agriculture, Applied Statistics, Artificial Intelligence and Robotics, Bioresource and Agricultural Engineering, Computer Sciences, Databases and Information Systems, Environmental Monitoring, Graphics and Human Computer Interfaces, Natural Resources and Conservation, Software Engineering, Terrestrial and Aquatic Ecology, Water Resource Management

Growing interest in data-driven, decision-support tools across the life sciences and physical sciences has motivated development of web applications, also known as web apps. Web apps can help disseminate research findings and present research outputs in ways that are more accessible and meaningful to the general public--from individuals, to governments, to companies. Specifically, web apps enable [...]

A Multiphysics approach to constrain the dynamics of the Altiplano-Puna magmatic system

Arne Spang, Tobias S. Baumann, Boris J.P. Kaus

Published: 2021-06-25
Subjects: Computer Sciences, Earth Sciences, Geology, Geophysics and Seismology, Numerical Analysis and Scientific Computing, Volcanology

Continuous Interferometric Synthetic Aperture Radar (InSAR) monitoring (> 25 years) has revealed a concentric surface deformation pattern above the Altiplano-Puna magma body (APMB) in the central Andes. Here, we use a joint interpretation of seismic imaging, gravity anomalies and InSAR data to constrain location, 3D geometry and density of the magma body. By combining gravity modelling, [...]

Knowledge graph construction and application in geosciences: A review

Xiaogang Ma

Published: 2021-04-30
Subjects: Artificial Intelligence and Robotics, Computer Engineering, Computer Sciences, Databases and Information Systems, Earth Sciences, Environmental Sciences

Knowledge graph (KG) is a topic of great interests to geoscientists as it can be deployed throughout the data life cycle in data-intensive geoscience studies. Nevertheless, comparing with the large amounts of publications on machine learning applications in geosciences, summaries and reviews of geoscience KGs are still limited. The aim of this paper is to present a comprehensive review of KG [...]

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