Preprints
Filtering by Subject: Multivariate Analysis
An ensemble neural network approach for space-time landslide predictive modelling
Published: 2024-02-27
Subjects: Artificial Intelligence and Robotics, Geomorphology, Multivariate Analysis
There is an urgent need for accurate and effective Landslide Early Warning Systems (LEWS). Most LEWS are currently based on a single temporally-aggregated measure of rainfall derived from either in-situ measurements or satellite-based rainfall estimates. Relying on a summary metric of precipitation may not capture the complexity of the rainfall signal and its dynamics in space and time in [...]
Assessing the Influence of Temperature on Slope Stability in a Temperate Climate: A Nationwide Spatial Probability Analysis in Italy
Published: 2024-01-18
Subjects: Geomorphology, Geotechnical Engineering, Multivariate Analysis
Among the factors controlling the stability of slopes, the role of temperature remains poorly understood, especially in temperate climates. Experiments reveal the coupled thermo-hydro-mechanical (THM) nature of clay behaviours; however, field evidence of thermally-induced landslides is scarce. The complexity of THM processes hinders the construction of a temperature-related variable, usable in [...]
Soil geochemistry of hydrogen and other gases along the San Andreas Fault
Published: 2023-07-23
Subjects: Environmental Chemistry, Geochemistry, Geology, Multivariate Analysis, Oil, Gas, and Energy, Soil Science
Natural hydrogen has generated great interest as a potential clean and renewable energy source. To understand the occurrence of natural hydrogen, 103 1-m deep soil gas samples were acquired near the San Andreas Fault at Jasper Ridge and Portola Valley, California, USA. The gas samples were analyzed for hydrogen, helium, carbon dioxide, light hydrocarbons, and fixed gas concentrations. Statistical [...]
The applicability of G-BASE stream sediment geochemistry as a combined geological mapping, and prospective exploration tool for As-Co-Cu-Ni mineralisation across Cumbria, UK.
Published: 2023-01-18
Subjects: Earth Sciences, Geochemistry, Geology, Multivariate Analysis, Physical Sciences and Mathematics, Statistics and Probability
Stream sediment geochemistry is a useful tool to analyse the geochemistry of the local geology within the source catchment area. This has significant applicability within the field of mineral exploration where understanding regional lithological geochemistry is needed, facilitating the identification of critical metal deposits. Successful identification of these deposits is essential to help [...]
A data-driven framework for landslide size space-time modelling
Published: 2022-10-10
Subjects: Applied Statistics, Geomorphology, Multivariate Analysis, Statistical Models
Landslide susceptibility assessment using data-driven models has predominantly focused on predicting where landslides may occur and not on how large they might be. The spatio-temporal evaluation of landslide susceptibility has only recently been addressed, as a basis for predicting where and when landslides might occur. The present study combines these new developments by proposing a data-driven [...]
Köppen meets Neural Network: Revision of the Köppen Climate Classification by Neural Networks
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 [...]
Space-time landslide susceptibility modelling in Taiwan
Published: 2022-07-27
Subjects: Applied Statistics, Geomorphology, Multivariate Analysis, Statistical Models
Portraying spatiotemporal variations in landslide susceptibility patterns is crucial for landslide prevention and management. In this study, we implement a space-time modeling approach to predict the landslide susceptibility on a yearly basis across the main island of Taiwan, from 2004 to 2018. We use a Bayesian version of a binomial generalized additive model, which assumes that landslide [...]
Reducing the Uncertainty of Multi-Well Petrophysical Interpretation from Well Logs via Machine-Learning and Statistical Models
Published: 2022-03-22
Subjects: Analysis, Earth Sciences, Engineering, Geophysics and Seismology, Mining Engineering, Multivariate Analysis, Statistical Methodology, Statistical Models
Well-log interpretation provides in situ estimates of formation properties such as porosity, hydrocarbon pore volume, and permeability. Reservoir models based on well-log-derived formation properties deliver reserve-volume estimates, production forecasts, and help with decision making in reservoir development. However, due to measurement errors, variability of well logs due to multiple [...]
A copula-based assessment of renewable energy droughts across Europe
Published: 2021-12-05
Subjects: Multivariate Analysis, Oil, Gas, and Energy, Other Earth Sciences
Meeting carbon-reduction targets will require thorough consideration of climate variability and climate change due to the increasing share of climate-sensitive renewable energy sources (RES). One of the main concerns arises from situations of low renewable production and high demand, which can hinder the power system. We analysed energy droughts, defined as periods of low energy production (wind [...]
Nonlinear time series analysis of palaeoclimate proxy records
Published: 2021-11-08
Subjects: Applied Statistics, Climate, Dynamic Systems, Earth Sciences, Geology, Longitudinal Data Analysis and Time Series, Multivariate Analysis, Non-linear Dynamics, Physical Sciences and Mathematics, Sedimentology, Statistical, Nonlinear, and Soft Matter Physics
Identifying and characterising dynamical regime shifts, critical transitions or potential tipping points in palaeoclimate time series is relevant for improving the understanding of often highly nonlinear Earth system dynamics. Beyond linear changes in time series properties such as mean, variance, or trend, these nonlinear regime shifts can manifest as changes in signal predictability, [...]
Evaluating Short-Term Spatio-Temporal Tropospheric Variability in Multi-Temporal SAR Interferograms Using LES Models
Published: 2021-07-13
Subjects: Aerospace Engineering, Atmospheric Sciences, Computational Engineering, Earth Sciences, Fluid Dynamics, Longitudinal Data Analysis and Time Series, Meteorology, Multivariate Analysis, Signal Processing
Atmospheric delay has a significant impact on synthetic aperture radar (SAR) interferometry, inducing spatial phase errors and decorrelation in extreme weather condition. For Low Earth Orbit (LEO) SAR missions, the atmosphere can be considered as being spatio-temporally frozen due to the short integration time. Geosynchronous (GEO) SAR missions, however, have short revisit times and extensive [...]
Ordination analysis in sedimentology, geochemistry and paleoenvironment - background, current trends and recommendations
Published: 2021-02-01
Subjects: Biogeochemistry, Earth Sciences, Environmental Indicators and Impact Assessment, Environmental Monitoring, Geochemistry, Geology, Geomorphology, Geophysics and Seismology, Glaciology, Multivariate Analysis, Oil, Gas, and Energy, Other Earth Sciences, Paleobiology, Paleontology, Sedimentology
Ordination is the name given to a group of methods used to analyze multiple variables without preceding hypotheses. Over the last few decades the use of these methods in Earth science in general, and notably in analyses of sedimentary sources, has dramatically increased. However, with limited resources oriented towards Earth scientists on the topic, the application of ordination analysis is at [...]
Sedimentary structures discriminations with hyperspectral imaging on sediment cores
Published: 2020-07-17
Subjects: Analytical Chemistry, Chemistry, Earth Sciences, Environmental Chemistry, Environmental Monitoring, Environmental Sciences, Multivariate Analysis, Optics, Physical Sciences and Mathematics, Physics, Sedimentology, Statistical Models, Statistics and Probability
Hyperspectral imaging (HSI) is a non-destructive high-resolution sensor, which is currently under significant development to analyze geological areas with remote devices or natural samples in a laboratory. In both cases, the hyperspectral image provides several sedimentary structures that need to be separated to temporally and spatially describe the sample. Sediment sequences are composed of [...]
Exposure and vulnerability estimation for modelling flood losses to commercial assets in Europe
Published: 2020-07-05
Subjects: Earth Sciences, Hydrology, Multivariate Analysis, Physical Sciences and Mathematics, Statistics and Probability
Commercial assets comprise buildings, machinery and equipment, which are susceptible to floods. Existing damage models and exposure estimation methods for this sector have limited transferability between flood events. In this study we introduce two methodologies aiming at broader applicability: (1) disaggregation of economic statistics to obtain detailed building-level estimates of replacement [...]
Seasonal impact-based mapping of compound hazards
Published: 2020-06-17
Subjects: Applied Mathematics, Atmospheric Sciences, Climate, Earth Sciences, Environmental Sciences, Hydrology, Mathematics, Multivariate Analysis, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Statistics and Probability
Impact-based, seasonal mapping of compound hazards is proposed. It is pragmatic, identifies phenomena to drive the research agenda, produces outputs relevant to stakeholders, and could be applied to many hazards globally. Illustratively, flooding and wind damage can co-occur, worsening their joint impact, yet where wet and windy seasons combine has not yet been systematically mapped. Here, [...]