Filtering by Subject: Statistical Models
Published: 2023-01-18
Subjects: Applied Statistics, Earth Sciences, Geomorphology, Geophysics and Seismology, Physical Sciences and Mathematics, Soil Science, Statistical Models, Statistics and Probability
Ground motion simulations solve wave equations in space and time, thus producing detailed estimates of the shaking time series. This is essentially uncharted territory for geomorphologists, for we have yet to understand which ground motion (synthetic or not) parameter, or combination of parameters, is more suitable to explain the coseismic landslide distribution. To address this gap, we developed [...]
Published: 2023-01-11
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: 2022-10-19
Subjects: Longitudinal Data Analysis and Time Series, Non-linear Dynamics, Planetary Sciences, Statistical Models
Herein we present the Energy Balance Model – Kalman Filter (EBM-Kalman), a hybrid model of the global mean surface temperature (GMST), which combines a theoretical energy balance equation based in Earth science literature and a statistical extended Kalman Filter incorporating observed and/or climate model simulated GMST data. This synthesis is possible because climate models and historical [...]
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 [...]
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 [...]
Published: 2022-07-22
Subjects: Environmental Monitoring, Soil Science, Statistical Models
Environmental models often require soil maps to represent the spatial variability of soil properties. However, mapping soils using conventional in situ survey protocols is time-consuming and costly. As an alternative, Digital Soil Mapping (DSM) offers a fast-mapping approach that has the potential to estimate soil properties and their interrelationships over large areas. In this study, we address [...]
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 [...]
Published: 2022-06-29
Subjects: Earth Sciences, Environmental Monitoring, Environmental Sciences, Hydrology, Statistical Models
Plastic pollution in aquatic ecosystems has increased dramatically in the last five decades, with strong impacts on human and aquatic life. Recent studies endorse the need for innovative approaches to monitor the presence, abundance, and types of plastic in these ecosystems. One approach gaining rapid traction is the use of multi- and hyperspectral cameras. However, most experiments using this [...]
Published: 2022-06-18
Subjects: Atmospheric Sciences, Climate, Environmental Monitoring, Mechanical Engineering, Oil, Gas, and Energy, Statistical Methodology, Statistical Models
Thorough characterization of probabilities of detection (POD) and quantification uncertainties is fundamentally important to understand the place of aerial measurement technologies in alternative means of emission limitation (AMEL) or alternate fugitive emissions management programs (Alt-FEMP); monitoring, reporting, and verification (MRV) efforts; and surveys designed to support [...]
Published: 2022-03-23
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 [...]
Published: 2021-12-09
Subjects: Environmental Public Health, Environmental Sciences, Environmental Studies, Statistical Models
Wildfires have increased in frequency and severity over the past two decades, threatening to undo substantial air quality improvements. We investigate the effect of wildfire smoke exposure on learning outcomes across the US using standardized test scores from 2009-2016 for nearly 11,700 school districts and satellite-derived estimates of daily smoke exposure. Relative to a school year with no [...]
Published: 2021-11-27
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 [...]
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 [...]
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 [...]
Published: 2021-10-12
Subjects: Environmental Monitoring, Environmental Public Health, Environmental Studies, Statistical Models
The impacts of environmental change on human outcomes often depend on local exposures and behavioral responses that are challenging to observe with traditional administrative or sensor data. We show how data from private pollution sensors, cell phones, social media posts, and internet search activity yield new insights on exposures and behavioral responses during large wildfire smoke events [...]