Filtering by Subject: Artificial Intelligence and Robotics
Published: 2023-01-13
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Geophysics and Seismology
During the RESOLVE project ("High-resolution imaging in subsurface geophysics: development of a multi-instrument platform for interdisciplinary research"), continuous surface displacement and seismic array observations were obtained on Glacier d'Argentière in the French Alps for 35 days during May in 2018. This unique data set offers the chance to perform a detailed, local study of targeted [...]
Published: 2023-01-10
Subjects: Artificial Intelligence and Robotics, Climate, Environmental Engineering, Environmental Monitoring, Geomorphology, Hydrology, Numerical Analysis and Scientific Computing, Oceanography, Sedimentology, Statistical Models
Given the current context of climate change and the increasing population densities at coastal zones around the globe, there is an increasing need to be able to predict the development of our coasts. Recent advances in artificial intelligence allow for automatic analysis of observational data. Symbolic Regression (SR) is a type of Machine Learning algorithm that aims to find interpretable [...]
Published: 2022-11-17
Subjects: Artificial Intelligence and Robotics, Environmental Monitoring, Hydrology
Landsat is the longest-running environmental satellite program and has been used for surface water mapping of large water bodies since its launch in 1972. Remote sensing image resolution is increasingly being enhanced through single image super resolution (SR), a machine learning task typically performed by neural networks. Here, we show that a 10x SR model (Enhanced Super Resolution GAN, or [...]
Published: 2022-10-29
Subjects: Artificial Intelligence and Robotics, Computer Engineering, Geomorphology
In order to develop reliable models, the geoscientific community requires high-resolution data sets. However, the collection of such data is a persistent challenge due to the limitations of resources. The concept of super-resolution, a method from the field of machine learning, can be used to predict a high-resolution version of a low-resolution dataset to improve usability in geoscientific [...]
Published: 2022-08-31
Subjects: Artificial Intelligence and Robotics, Climate, Other Statistics and Probability, Plant Sciences, Probability, Quantum Physics, Research Methods in Life Sciences, Soil Science, Statistical, Nonlinear, and Soft Matter Physics, Sustainability, Systems Biology
In this brief communication, biomolecular plant breeding multi-classification inference is discussed when leveraging the advantages of Physics-informed Neural Network (PiNN) architecture. Albeit, the expected utility of Partial Differential Equation (PDE) inspired neural networks resides in its performance under limited data availability; a variety of neural network configurations result from PDE [...]
Published: 2022-08-31
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Environmental Sciences, Oceanography and Atmospheric Sciences and Meteorology, Other Earth Sciences, Other Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Sustainability
We introduce a method for long-distance maritime route planning in polar regions, taking into account complex changing environmental conditions. The method allows the construction of optimised routes, describing the three main stages of the process: discrete modelling of the environmental conditions using a non-uniform mesh, the construction of mesh-optimal paths, and path smoothing. In order to [...]
Published: 2022-08-23
Subjects: Artificial Intelligence and Robotics, Categorical Data Analysis, Climate, Earth Sciences, Ecology and Evolutionary Biology, Environmental Indicators and Impact Assessment, Environmental Monitoring, Multivariate Analysis
Climate change and development of data-oriented methods are appealing for new climate classification schemes. Based on the most widely used Köppen-Geiger scheme, this article proposes a neural network based climate classification method from a data science perspective. In conventional schemes, empirically handcrafted rules are used to divide climate data into climate types, resulting in certain [...]
Published: 2022-08-22
Subjects: Artificial Intelligence and Robotics, Databases and Information Systems, Environmental Sciences, Numerical Analysis and Scientific Computing
To maintain a sustainable society, environmental friendliness is necessary, an effort that all countries must take part in. The effort must be pioneered by developed nations with the resources to enact sustainable policies, reduce emissions and conserve energy, from which developing nations will follow the eroded path. Recognizing the factors that promote environmental friendliness is necessary [...]
Published: 2022-07-15
Subjects: Artificial Intelligence and Robotics, Earth Sciences, Statistical Methodology
A simple method for adding uncertainty to neural network regression tasks in earth science via estimation of a general probability distribution is described. Specifically, we highlight the sinh-arcsinh-normal distributions as particularly well suited for neural network uncertainty estimation. The methodology supports estimation of heteroscedastic, asymmetric uncertainties by a simple modification [...]
Published: 2022-06-17
Subjects: Artificial Intelligence and Robotics, Dynamic Systems, Hydrology, Natural Resources and Conservation
Machine learning (ML) is becoming an ever more important tool in hydrologic modeling. Many studies have shown the higher prediction accuracy of the ML models over traditional process-based ones. However, there is another advantage of ML which is its lower computer time of execution. This is important for the applications such as hydraulic soil erosion estimation over a large area and at a finer [...]
Published: 2022-06-02
Subjects: Artificial Intelligence and Robotics, Atmospheric Sciences
Heatwaves are extreme near-surface temperature events that can have substantial impacts on ecosystems and society. Early Warning Systems help to reduce these impacts by helping communities prepare for hazardous climate-related events. However, state-of-the-art prediction systems can often not make accurate forecasts of heatwaves more than two weeks in advance, which are required for advance [...]
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 [...]
Published: 2022-05-19
Subjects: Artificial Intelligence and Robotics, Geology, Geophysics and Seismology
Numerous studies have demonstrated the capability of supervised deep learning techniques for predicting geological features of interest from seismic sections, including features that are difficult to identify using traditional interpretation methods. However, successful application of these techniques in practice has been limited by the difficulty of obtaining large training dataset where seismic [...]
Published: 2022-05-13
Subjects: Artificial Intelligence and Robotics, Geology, Geophysics and Seismology, Tectonics and Structure
Understanding where normal faults are is critical to an accurate assessment of seismic hazard, the successful exploration for and production of natural (including low-carbon) resources, and for the safe subsurface storage of CO2. Our current knowledge of normal fault systems is largely derived from seismic reflection data imaging intra-continental rifts and continental margins. However, [...]
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 [...]