Preprints

Filtering by Subject: Applied Statistics

A data-driven framework for landslide size space-time modelling

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 [...]

Machine learning for understanding inland water quantity, quality, and ecology

Alison Paige Appling, Samantha Kay Oliver, Jordan S. Read, et al.

Published: 2022-09-03
Subjects: Applied Statistics, Fresh Water Studies, Hydrology

This chapter provides an overview of machine learning models and their applications to the science of inland waters. Such models serve a wide range of purposes for science and management: predicting water quality, quantity, or ecological dynamics across space, time, or hypothetical scenarios; vetting and distilling raw data for further modeling or analysis; generating and exploring hypotheses; [...]

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 [...]

The Lock-Down Effects of COVID-19 on the Air Pollution Indices in Iran and Its Neighbors

Mohammad Fayaz

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 [...]

Space-time landslide hazard modeling via Ensemble Neural Networks

Ashok Dahal, Hakan Tanyas, Cees J. van Westen, et al.

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 [...]

A univariate extreme value analysis and change point detection of monthly discharge in Kali Kupang, Central Java, Indonesia

Sandy Hardian Susanto Herho

Published: 2022-05-19
Subjects: Applied Statistics, Hydrology, Probability, Water Resource Management

This study presents how Extreme Value Analysis (EVA) can be used to predict future extreme hydrological events and how dynamic-programming based change point detection algorithm can be used to detect the abrupt transition in discharge events variability in Kali Kupang, Central Java, Indonesia. By using the annual block maxima, we can predict the upper extreme discharge probability from the Gumbel [...]

Global dynamics of the offshore wind energy sector monitored with Sentinel-1: Turbine count, installed capacity and site specifications

Thorsten Hoeser, Claudia Kuenzer

Published: 2022-04-26
Subjects: Applied Statistics, Earth Sciences, Environmental Sciences, Natural Resource Economics, Natural Resources Management and Policy, Oil, Gas, and Energy, Other Earth Sciences, Statistics and Probability

With the promotion of renewable energy production and a planned phaseout of fossil fuels until 2040, the offshore wind energy sector has started to expand and will continue to increase its capacity in the upcoming decades. This study presents how the installed capacity can be derived from radar imagery provided by the Sentinel-1 mission for all offshore wind turbines on the entire Earth. By [...]

GEDI Launches a New Era of Biomass Inference from Space

Ralph Dubayah, John Armston, Sean Healey, et al.

Published: 2022-04-20
Subjects: Applied Statistics, Earth Sciences, Other Earth Sciences, Other Forestry and Forest Sciences, Terrestrial and Aquatic Ecology

Accurate estimation of aboveground forest biomass stocks is required to assess the impacts of land use changes such as deforestation and subsequent regrowth on concentrations of atmospheric CO2. The Global Ecosystem Dynamics Investigation (GEDI) is a lidar mission launched by NASA to the International Space Station in 2018. GEDI was specifically designed to retrieve vegetation structure within a [...]

Place-level urban-rural indices for the United States from 1930 to 2018

Johannes H. Uhl, Lori M. Hunter, Stefan Leyk, et al.

Published: 2022-02-28
Subjects: Applied Statistics, Geographic Information Sciences, Geography, Human Geography, Longitudinal Data Analysis and Time Series, Social and Behavioral Sciences, Spatial Science

Rural-urban classifications are essential for analyzing geographic, demographic, environmental, and social processes across the rural-urban continuum. Most existing classifications are, however, only available at relatively aggregated spatial scales, such as at the county scale in the United States. The absence of rurality or urbanness measures at high spatial resolution poses significant [...]

Uncertainty and sensitivity analysis for probabilistic weather and climate risk modelling: an implementation in CLIMADA v.3.1.

Chahan M. Kropf, Alessio Ciullo, Laura Otth, et al.

Published: 2022-02-23
Subjects: Applied Statistics, Climate, Design of Experiments and Sample Surveys, Earth Sciences, Environmental Studies, Natural Resources Management and Policy, Nature and Society Relations, Numerical Analysis and Computation, Numerical Analysis and Scientific Computing, Risk Analysis, Statistical Methodology

Modelling the risk of natural hazards for society, ecosystems, and the economy is subject to strong uncertainties, even more so in the context of a changing climate, evolving societies, growing economies, and declining ecosystems. Here we present a new feature of the climate risk modelling platform CLIMADA which allows to carry out global uncertainty and sensitivity analysis. CLIMADA underpins [...]

Estuarine-deltaic controls on coastal carbon burial in the western Ganges-Brahmaputra delta over the last 5,000 years

Rory Patrick Flood, Margaret Georgina Milne, Graeme T Swindles, et al.

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 [...]

C3S Energy: an operational service to deliver power demand and supply for different electricity sources, time and spatial scales over Europe

Laurent Dubus, Yves-Marie Saint-Drenan, Alberto Troccoli, et al.

Published: 2021-11-17
Subjects: Applied Statistics, Climate, Earth Sciences, Environmental Sciences, Statistical Models

The EU Copernicus Climate Change Service (C3S) has produced an operational climate service, called C3S Energy, designed to enable the energy industry and policy makers to assess the impacts of climate variability and climate change on the energy sector in Europe. The C3S Energy service covers different time horizons, for the past forty years and the future. It provides time series of electricity [...]

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, [...]

Beyond prediction: methods for interpreting complex models of soil variation

Alexandre M.J.-C. Wadoux, Christoph Molnar

Published: 2021-10-27
Subjects: Applied Statistics, Soil Science, Statistical Models

Understanding the spatial variation of soil properties is central to many sub-disciplines of soil science. Commonly in soil mapping studies, a soil map is constructed through prediction by a statistical or non-statistical model calibrated with measured values of the soil property and environmental covariates of which maps are available. In recent years, the field has gradually shifted attention [...]

Ten Simple Rules for Researchers Who Want to Develop Web Apps

Sheila M. Saia, Natalie G. Nelson, Sierra N. Young, et al.

Published: 2021-07-18
Subjects: Agricultural Science, Agriculture, Applied Statistics, Artificial Intelligence and Robotics, Bioresource and Agricultural Engineering, Computer Sciences, Databases and Information Systems, Environmental Monitoring, Graphics and Human Computer Interfaces, Natural Resources and Conservation, Software Engineering, Terrestrial and Aquatic Ecology, Water Resource Management

Growing interest in data-driven, decision-support tools across the life sciences and physical sciences has motivated development of web applications, also known as web apps. Web apps can help disseminate research findings and present research outputs in ways that are more accessible and meaningful to the general public--from individuals, to governments, to companies. Specifically, web apps enable [...]

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