Preprints
Filtering by Subject: Other Statistics and Probability
A SCALABLE MACHINE LEARNING MODELLING TOOL FOR MAPPING LANDSLIDE RUNOUT USING A CASE STUDY IN HAWKES BAY, NEW ZEALAND
Published: 2025-05-02
Subjects: Climate, Earth Sciences, Geology, Geotechnical Engineering, Other Statistics and Probability
Understanding landslide runout is crucial for land use planning, utility networks, and assessing infrastructure resilience on slopes. Recent guidance recommends incorporating landslide runout models along with climate change implications when assessing land for development. The advancement of machine learning (ML) techniques can offer new insights and a tool to be used alongside current methods. [...]
Ensemble Kalman, Adaptive Gaussian Mixture, and Particle Flow Filters for Optimized Earthquake Forecasting
Published: 2024-06-01
Subjects: Dynamical Systems, Geophysics and Seismology, Other Statistics and Probability
Probabilistic forecasts are regarded as the highest achievable goal when predicting earthquakes, but limited information on stress, strength, and governing parameters of the seismogenic sources affects their accuracy. Ensemble data-assimilation methods, such as the Ensemble Kalman Filter (EnKF), estimate these variables by combining physics-based models and observations.While the EnKF has [...]
The Potential for Fuel Reduction to Offset Climate Warming Impacts on Wildfire Intensity in California
Published: 2024-02-21
Subjects: Climate, Earth Sciences, Environmental Sciences, Forest Management, Forest Sciences, Meteorology, Oceanography and Atmospheric Sciences and Meteorology, Other Statistics and Probability, Physical Sciences and Mathematics, Probability, Statistical Methodology, Statistical Models, Statistics and Probability
Increasing fuel aridity due to climate warming has and will continue to increase wildfire danger in California. In addition to reducing global greenhouse gas emissions, one of the primary proposals for counteracting this increase in wildfire danger is a widespread expansion of hazardous fuel reductions. Here, we quantify the potential for fuel reduction to reduce wildfire intensity using [...]
Pygoda: a graphical interface to efficiently visualise and explore large sets of geolocated time series
Published: 2023-10-24
Subjects: Categorical Data Analysis, Climate, Computer Sciences, Databases and Information Systems, Earth Sciences, Environmental Monitoring, Environmental Sciences, Environmental Studies, Fresh Water Studies, Geographic Information Sciences, Geophysics and Seismology, Glaciology, Graphics and Human Computer Interfaces, Hydrology, Longitudinal Data Analysis and Time Series, Meteorology, Other Earth Sciences, Other Statistics and Probability, Spatial Science
Modern-day data sets in geosciences may comprise hundreds or thousands of geolocated time series. Despite all the automated tools and new algorithms now available to process and prepare those data before using them in research projects, it can be useful or even necessary to visualise and investigate them manually. Whether it be for data quality assessment, for the preparation of a training data [...]
Strategic Logic of Unilateral Climate Intervention
Published: 2023-05-22
Subjects: Atmospheric Sciences, Climate, International and Area Studies, Other Statistics and Probability, Risk Analysis
Climate change and unabated greenhouse gas emissions are increasing the possibility that the world will turn to climate intervention to curb ever-increasing global temperatures. To date, most work on this topic has imagined that an international organization like the United Nations or an international coalition of states will synchronize their efforts to deploy climate intervention at ideal [...]
Variational inference of ice shelf rheology with physics-informed machine learning
Published: 2022-09-06
Subjects: Earth Sciences, Glaciology, Other Mathematics, Other Statistics and Probability, Physical Sciences and Mathematics
Floating ice shelves that fringe the coast of Antarctica resist the flow of grounded ice into the ocean. One of the key factors governing the amount of flow-resistance provided by an ice shelf is the rigidity of the ice that constitutes it. Ice rigidity is highly heterogeneous and must be calibrated from spatially-continuous surface observations assimilated into an ice flow model. Moreover, [...]
Plant Breeding Biomolecular Classification in Quantum Bayesianism (QBism) Physics-Informed Neural Network Architecture
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 [...]
The Lock-Down Effects of COVID-19 on the Air Pollution Indices in Iran and Its Neighbors
Published: 2022-07-02
Subjects: Applied Statistics, Environmental Public Health, Environmental Sciences, Environmental Studies, Near and Middle Eastern Studies, Other Statistics and Probability, Statistical Methodology, Statistical Models
Introduction The Covid-19 restrictions have a lot of various peripheral negative and positive effects like economic shocks and decreasing air pollution, respectively. Many studies showed NO2 reduction in most parts of the world. Method Iran and its land and maritime neighbors have about 7.4% of the world population and 6.3% and 5.8% of World COVID-19 cases and deaths, respectively. The air [...]
Estuarine-deltaic controls on coastal carbon burial in the western Ganges-Brahmaputra delta over the last 5,000 years
Published: 2021-11-26
Subjects: Applied Statistics, Biogeochemistry, Earth Sciences, Environmental Sciences, Geochemistry, Geology, Geomorphology, Other Earth Sciences, Other Environmental Sciences, Other Statistics and Probability, Physical Sciences and Mathematics, Sedimentology, Statistical Methodology, Statistical Models, Statistics and Probability, Water Resource Management
The Ganges–Brahmaputra fluvial system drains the Himalayas and is one of the largest sources of terrestrial biosphere carbon to the ocean. It represents a major continental reservoir of CO2 associated with c. 1–2 billion tons of sediment transported each year. Shallow coastal environments receive substantial inputs of terrestrial carbon (900 Tg C yr−1), with allochthonous carbon capture on [...]
Hierarchical Cluster Analysis by R language for Pattern Recognition in the Bathymetric Data Frame: a Case Study of the Mariana Trench, Pacific Ocean
Published: 2019-01-25
Subjects: Applied Statistics, Earth Sciences, Environmental Education, Environmental Monitoring, Environmental Sciences, Environmental Studies, Geographic Information Sciences, Geography, Geology, Geomorphology, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Other Earth Sciences, Other Oceanography and Atmospheric Sciences and Meteorology, Other Statistics and Probability, Physical and Environmental Geography, Physical Sciences and Mathematics, Social and Behavioral Sciences, Spatial Science, Statistics and Probability, Tectonics and Structure
The geographic focus of the current study Mariana trench, the deepest point of the Earth located in the west Pacific Ocean. Mariana trench has unique structure and features formed in the complex process of the trench development. There is a range of the environmental factors affecting trench structure and functioning: bathymetry, geography, geology and tectonics. Current research aimed to study [...]
Landscape classification with deep neural networks.
Published: 2018-06-18
Subjects: Computer and Systems Architecture, Computer Engineering, Earth Sciences, Engineering, Environmental Monitoring, Environmental Sciences, Geology, Geomorphology, Other Statistics and Probability, Physical Sciences and Mathematics, Statistics and Probability
The application of deep learning, specifically deep convolutional neural networks (DCNNs), to the classification of remotely sensed imagery of natural landscapes has the potential to greatly assist in the analysis and interpretation of geomorphic processes. However, the general usefulness of deep learning applied to conventional photographic imagery at a landscape scale is, at yet, largely [...]