Preprints
Filtering by Subject: Computer Sciences
A Vision for the Future Low-Temperature Geochemical Data-scape
Published: 2020-11-21
Subjects: Biogeochemistry, Computer Sciences, Databases and Information Systems, Earth Sciences, Environmental Sciences, Geochemistry, Geology, Geomorphology, Hydrology, Other Computer Sciences, Other Earth Sciences, Soil Science
Data sharing benefits the researcher, the scientific community, and most importantly, the public by enabling more impactful analysis of data and greater transparency in scientific research. However, like many other scientists, the low-temperature geochemistry (LTG) community has generally not developed protocols and standards for publishing, citing, and versioning datasets. This paper is the [...]
An attempt at improving atmospheric corrections in InSAR using cycle-consistent adversarial networks
Published: 2020-11-09
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Geophysics and Seismology
Interferometry from satellite radar has thrived as a major asset to study surface deformations from earthquakes, volcanoes, aquifers, glaciers, landslides, etc. Most signals recorded in an interferogram have precise enough models to remove them almost completely. Yet, current models still fail to capture the full range and scales of variations of atmospheric perturbations. This work explores the [...]
Transitioning Machine Learning from Theory to Practice in Natural Resources Management
Published: 2020-10-22
Subjects: Agriculture, Computer Sciences, Environmental Education, Environmental Sciences, Environmental Studies, Forest Management, Forest Sciences, Natural Resources and Conservation, Natural Resources Management and Policy, Water Resource Management
Advances in sensing and computation have accelerated at unprecedented rates and scales, in turn creating new opportunities for natural resources managers to improve adaptive and predictive management practices by coupling large environmental datasets with machine learning (ML). Yet, to date, ML models often remain inaccessible to managers working outside of academic research. To identify [...]
Pangeo Benchmarking Analysis: Object Storage vs. POSIX File System
Published: 2020-10-21
Subjects: Computer Sciences, Earth Sciences, Physical Sciences and Mathematics
Pangeo is a community of scientists and software developers collaborating to enable Big Data Geoscience analysis interactively in the public cloud and on high-performance computing (HPC) systems. At the core of the Pangeo software stack is (1) Xarray, which adds labels to metadata such as dimensions, coordinates and attributes for raw array-oriented data, (2) Dask, which provides parallel [...]
Bridging the gap between geophysics and geology with Generative Adversarial Networks (GANs)
Published: 2020-08-16
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Databases and Information Systems, Earth Sciences, Environmental Monitoring, Environmental Sciences, Geology, Geomorphology, Geophysics and Seismology, Natural Resource Economics, Oil, Gas, and Energy, Other Earth Sciences, Physical Sciences and Mathematics, Sedimentology, Water Resource Management
Inverse mapping from geophysics to geology is a difficult problem due to the inherent uncertainty of geophysical data and the spatially heterogeneous patterns (structure) in geology. We describe GANSim, a type of generative adversarial networks (GANs) that discovers the mapping between remotely-sensed geophysical information and geology with realistic patterns, with a specially designed loss [...]
GeospatialVR: A Web-based Virtual Reality Framework for Collaborative Environmental Simulations
Published: 2020-08-08
Subjects: Civil and Environmental Engineering, Computer Sciences, Databases and Information Systems, Engineering, Environmental Engineering, Environmental Indicators and Impact Assessment, Environmental Monitoring, Environmental Sciences, Graphics and Human Computer Interfaces, Physical Sciences and Mathematics
This research introduces GeospatialVR, an open-source collaborative virtual reality framework to dynamically create 3D real-world environments that can be served on any web platform and accessed via desktop and mobile devices and virtual reality headsets. The framework can generate realistic simulations of desired locations entailing the terrain, elevation model, infrastructures, dynamic [...]
Forecasting the localized bilateral effects of ocean acidification on the counter carbonate pump using recurrent neural networks
Published: 2020-07-08
Subjects: Artificial Intelligence and Robotics, Chemistry, Computer Sciences, Environmental Chemistry, Numerical Analysis and Scientific Computing, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics
The counter carbonate pump(CCP) is responsible for carbon dioxide sequestration and cycling forms of carbon in the ocean. It is primarily driven by calcifying plankton, such as foraminifera, coccolithophores, and pteropods. These organisms are particularly vulnerable to ocean acidification, which can have disastrous effects on their skeletons and productivity, upsetting the marine carbon cycle in [...]
Application of the tilt derivative transform to bathymetric data for structural lineament mapping
Published: 2020-07-08
Subjects: Computer Sciences, Earth Sciences, Geomorphology, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Tectonics and Structure
High-resolution bathymetry surveys provide an opportunity to analyse local geological structure where onshore areas afford limited exposure. Semi-automated lineament detection methods are necessary for areas of large coverage where a manual analysis would be subjective and time-consuming. However, semi-automated approaches are dependent on effective feature extraction methods to identify genuine [...]
GANSim: Conditional Facies Simulation Using an Improved Progressive Growing of Generative Adversarial Networks (GANs)
Published: 2020-07-05
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Geology, Hydrology, Mathematics, Physical Sciences and Mathematics, Sedimentology, Statistical Models, Statistics and Probability
Conditional facies modeling combines geological spatial patterns with different types of observed data, to build earth models for predictions of subsurface resources. Recently, researchers have used generative adversarial networks (GANs) for conditional facies modeling, where an unconditional GAN is first trained to learn the geological patterns using the original GANs loss function, then [...]
Deep spatial transformers for autoregressive data-driven forecasting of geophysical turbulence
Published: 2020-07-05
Subjects: Artificial Intelligence and Robotics, Atmospheric Sciences, Climate, Computer Sciences, Dynamical Systems, Earth Sciences, Environmental Sciences, Fluid Dynamics, Geophysics and Seismology, Mathematics, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Physics
A deep spatial transformer based encoder-decoder model has been developed to autoregressively predict the time evolution of the upper layers stream function of a two-layered quasi-geostrophic (QG) system without any information about the lower layers stream function. The spatio-temporal complexity of QG flow is comparable to the complexity of 500hPa Geopotential Height (Z500) of fully coupled [...]
Machine learning and fault rupture: a review
Published: 2020-07-02
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Geophysics and Seismology, Mathematics, Physical Sciences and Mathematics, Theory and Algorithms
Geophysics has historically been a data-driven field, however in recent years the exponential increase of available data has lead to increased adoption of machine learning techniques and algorithm for analysis, detection and forecasting applications to faulting. This work reviews recent advances in the application of machine learning in the study of fault rupture ranging from the laboratory to [...]
Modelling massive AIS streams with quad trees and Gaussian Mixtures
Published: 2020-06-29
Subjects: Computer Sciences, Other Computer Sciences, Physical Sciences and Mathematics
Pressing issues related to the movement of people and goods can be tackled today thanks to improvements in tracking and communications technology that have made it possible to collect movement data on a big scale. Maritime data from the Automatic Identification System (AIS) is one of the fast growing sources of movement data. Existing approaches for AIS data [...]
Fully Automated Carbonate Petrography Using Deep Convolutional Neural Networks
Published: 2020-06-23
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Geology, Paleobiology, Paleontology, Physical Sciences and Mathematics, Sedimentology
Carbonate rocks are important archives of past ocean conditions as well as hosts of economic resources such as hydrocarbons, water, and minerals. Geologists typically perform compositional analysis of grain, matrix, cement and pore types in order to interpret depositional environments, diagenetic modification, and reservoir quality of carbonate strata. Such information can be obtained primarily [...]
An Ethical Decision-Making Framework with Serious Gaming: Smart Water Case Study on Flooding
Published: 2020-06-23
Subjects: Artificial Intelligence and Robotics, Civil and Environmental Engineering, Civil Engineering, Computer Sciences, Databases and Information Systems, Engineering, Engineering Education, Environmental Engineering, Hydraulic Engineering, Physical Sciences and Mathematics, Theory and Algorithms
Sensors and control technologies are being deployed extensively in both urban water networks and rural river systems, leading to unprecedented ability to sense and control our water environment. Because these sensor networks and control systems allow for higher resolution monitoring and decision making in both time and space, greater discretization of control will allow for an unprecedented [...]
Geological Facies Modeling Based on Progressive Growing of Generative Adversarial Networks (GANs)
Published: 2020-06-22
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Geology, Geophysics and Seismology, Hydrology, Physical Sciences and Mathematics, Sedimentology, Stratigraphy
Geological facies modeling has long been studied to predict subsurface resources. In recent years, generative adversarial networks (GANs) have been used as a new method for geological facies modeling with surprisingly good results. However, in conventional GANs, all layers are trained concurrently, and the scales of the geological features are not considered. In this study, we propose to train [...]