Filtering by Subject: Multivariate Analysis

Space-time landslide size modelling in Taiwan

Zhice Fang, Yi Wang, Cees J. van Westen, et al.

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

Ji Luo

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

Zhice Fang, Yi Wang, Cees J. van Westen, et al.

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

Wen Pan, Carlos Torres-Verdín, Ian J Duncan, et al.

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

Noelia Otero, Olivia Martius, Sam Allen, et al.

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

Norbert Marwan, Jonathan F. Donges, Reik V. Donner, et al.

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

Fengming Hu, Ramon Hanssen, Pier Siebesma, et al.

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

Or M. Bialik, Emilia Jarochowska, Michal Grossowicz

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

Kévin Jacq, Rapuc William, Benoit Alexandre, et al.

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

Dominik Paprotny, Heidi Kreibich, Oswaldo Morales-Nápoles, et al.

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

John Hillier, Richard Dixon

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, [...]

Comparison of permeability predictions on cemented sandstones with physics-based and machine learning approaches

Frank Male, Jerry L. Jensen, Larry W. Lake

Published: 2020-02-06
Subjects: Chemical Engineering, Earth Sciences, Engineering, Hydrology, Multivariate Analysis, Petroleum Engineering, Physical Sciences and Mathematics, Statistics and Probability

Permeability prediction has been an important problem since the time of Darcy. Most approaches to solve this problem have used either idealized physical models or empirical relations. In recent years, machine learning (ML) has led to more accurate and robust, but less interpretable empirical models. Using 211 core samples collected from 12 wells in the Garn Sandstone from the North Sea, this [...]

Advanced ML and AI Approaches for Proxy-based Optimization of CO2-Enhanced Oil Recovery in Heterogeneous Clastic Reservoirs

Watheq J Al-Mudhafar, Dandina N Rao, Sanjay Srinivasan

Published: 2019-12-04
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Design of Experiments and Sample Surveys, Earth Sciences, Multivariate Analysis, Other Earth Sciences, Physical Sciences and Mathematics, Programming Languages and Compilers, Statistics and Probability

Constructing a simpler model to represent a complex reservoir simulation that will be employed to define the optimum future development plans have been achieved through the use of different simulation techniques that include EOS-compositional reservoir simulation, Proxy Modeling as well as Design of Experiments. Once reliable history matching was achieved, the key five operational decision [...]

Statistics and segmentation: Using Big Data to assess Cascades Arc compositional variability

Bradley William Pitcher, Adam J Kent

Published: 2018-09-24
Subjects: Applied Mathematics, Applied Statistics, Earth Sciences, Geochemistry, Geology, Multivariate Analysis, Physical Sciences and Mathematics, Statistics and Probability, Volcanology

Primitive lavas erupted in the Cascades arc of western North America demonstrate significant patterns of along-arc heterogeneity. Such compositional diversity may be the result of differences in mantle melting processes, subduction geometry, regional tectonics, or compositions of the slab, mantle or overlying lithosphere. Previous authors have partitioned the arc into four geochemically distinct [...]

Higher potential compound flood risk in Northern Europe under anthropogenic climate change

Emanuele Bevacqua, Douglas Maraun, Michalis I. Vousdoukas, et al.

Published: 2018-07-18
Subjects: Applied Mathematics, Atmospheric Sciences, Climate, Earth Sciences, Environmental Sciences, Hydrology, Multivariate Analysis, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Other Oceanography and Atmospheric Sciences and Meteorology, Other Physical Sciences and Mathematics, Physical Sciences and Mathematics, Physics, Statistics and Probability

The published version of this article is available at Compound flooding (CF) is an extreme event taking place in low-lying coastal areas as a result of co-occurring high sea level and large amounts of runoff, caused by precipitation. The impact from the two hazards occurring individually can be significantly lower than the result of their [...]

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