Results 51 to 60 of about 609 (154)

A joint Bayesian space–time model to integrate spatially misaligned air pollution data in R-INLA [PDF]

, 2020
In air pollution studies, dispersion models provide estimates of concentration at grid level covering the entire spatial domain and are then calibrated against measurements from monitoring stations. However, these different data sources are misaligned in
Cameletti, M.
core   +1 more source

Estimating Velocities of Infectious Disease Spread Through Spatio‐Temporal Log‐Gaussian Cox Point Processes

International Statistical Review, EarlyView.
Summary Understanding the spread of infectious diseases such as COVID‐19 is crucial for informed decision‐making and resource allocation. A critical component of disease behaviour is the velocity with which disease spreads, defined as the rate of change between time and space.
Fernando Rodriguez Avellaneda, Jorge Mateu, Paula Moraga   +2 more
wiley   +1 more source

Coherent Disaggregation and Uncertainty Quantification for Spatially Misaligned Data

Environmetrics, Volume 37, Issue 2, March 2026.
ABSTRACT Spatial misalignment arises when datasets are aggregated or collected at different spatial scales, leading to information loss. We develop a Bayesian disaggregation framework that links misaligned data to a continuous‐domain model through an iteratively linearised integration scheme implemented with the Integrated Nested Laplace Approximation (
Man Ho Suen, Mark Naylor, Finn Lindgren
wiley   +1 more source

Assessing the risk of extreme precipitation in Japan through GEV distribution and spatial modeling

Journal of Hydrology: Regional Studies
Study region: Japan, characterized by diverse climatic zones and complex topography, has experienced increasing frequency and severity of extreme precipitation events in recent decades.
Zhichao Jiao, Jihui Yuan, Craig Farnham, Kazuo Emura   +3 more
doaj   +1 more source

Desempeño predictivo de R-INLA SPDE para el Mapeo Digital de Suelos

, 2021
El mapeo digital de suelos (MDS) permite describir la variabilidad espacial de una propiedad edáfica a treves de modelos de predicción espacial que explican la relación que existe entre la variable de interés y covariables sitio-especificas. Entre los modelos estadísticos más incipientes en aplicaciones de MDS está la regresión bayesiana ajustada con ...
Giannini Kurina, Franca, Suarez, Franco Marcelo, Paccioretti, Pablo Ariel, Macchiavelli, Raul, Balzarini, Monica Graciela   +4 more
openaire   +1 more source

Comparison of approaches to interpolating climate observations in steep terrain with low-density gauging networks [PDF]

, 2019
The accuracy of hydrological assessments in mountain regions is often hindered by the low density of gauges coupled with complex spatial variations in climate. Increasingly, spatial datasets (i.e. satellite and other products) and new computational tools
Cameletti, Michela
core   +1 more source

Where Are the Important Hotspots for Forest Biodiversity? A Detailed Spatial Analysis for the Australian State of Victoria

Austral Ecology, Volume 51, Issue 2, February 2026.
ABSTRACT Identifying areas of high biodiversity value is critical for effective conservation. Similarly, identifying gaps in existing protected area networks is fundamental to determining where new areas are needed to better conserve biodiversity. We conducted a spatial prioritisation analysis for forest and woodland‐dependent species across Victoria ...
Chris Taylor, David Lindenmayer
wiley   +1 more source

Patterns and Drivers of Pest and Disease Occurrence in UK Treescapes

Global Change Biology, Volume 32, Issue 2, February 2026.
Tree pests and diseases can be very damaging to natural and commercial forests. We studied how the risk of tree pests and diseases varies across mainland Great Britain and explored how factors such as urbanisation and recreational visits affect the level of risk in different places.
Peter S. Stewart, Louise J. Barwell, Katharine Turvey, Jane Barbrook, Sarah Green, Ana Pérez‐Sierra, Bethan V. Purse, Daniel Chapman   +7 more
wiley   +1 more source

Data-driven soil salinization mapping: risk prediction and uncertainty quantification based on Bayesian inference

Geoderma
Soil salinization poses a serious global threat to agricultural production and has emerged as a critical issue of land degradation. To comprehensively investigate the risks and uncertainty quantification associated with soil salinization, Yucheng County,
Yujian Yang, Ying Zhao, Rongjiang Yao, Xueqin Tong   +3 more
doaj   +1 more source

Seroprevalence for dengue virus in a hyperendemic area and associated socioeconomic and demographic factors using a cross-sectional design and a geostatistical approach, state of São Paulo, Brazil

BMC Infectious Diseases, 2019
Background São José do Rio Preto is one of the cities of the state of São Paulo, Brazil, that is hyperendemic for dengue, with the presence of the four dengue serotypes. Objectives: to calculate dengue seroprevalence in a neighbourhood of São José do Rio
Francisco Chiaravalloti-Neto, Rafael Alves da Silva, Nathalia Zini, Gislaine Celestino Dutra da Silva, Natal Santos da Silva, Maisa Carla Pereira Parra, Margareth Regina Dibo, Cassia Fernanda Estofolete, Eliane Aparecida Fávaro, Karina Rocha Dutra, Manlio Tasso Oliveira Mota, Georgia Freitas Guimarães, Ana Carolina Bernardes Terzian, Marta Blangiardo, Mauricio Lacerda Nogueira   +14 more
doaj   +1 more source