Results 31 to 40 of about 8,734 (183)

Spatio‐temporal data integration for species distribution modelling in R‐INLA

Methods in Ecology and Evolution
Species distribution modelling is a highly used tool for understanding and predicting biodiversity change, and recent work has emphasised the importance of understanding how species distributions change over both time and space.
Fiona M. Seaton, Susan G. Jarvis, Peter A. Henrys   +2 more
doaj   +2 more sources

Correction to: A Bayesian Model for Estimating the Effects of Human Disturbance on Wildlife Habitats Based on Nighttime Light Data and INLA‑SPDE [PDF]

Applied Spatial Analysis and Policy, 2022
Changbai Xi, Zhao-ning Wu, Tianlu Qian, Lu Liu, Jie-chen Wang   +4 more
semanticscholar   +2 more sources

Predicting outflow ratios on rainfall estimation through the SPDE approach with R-INLA

都市計画報告集, 2022
Kazumasa Fujimura
exaly   +2 more sources

Spatially Dependent Bayesian Modeling of Geostatistics Data and Its Application for Tuberculosis (TB) in China

Mathematics, 2023
Geostatistics data in regions always have highly spatial heterogeneous, yet the regional features of the data itself cannot be ignored. In this paper, a novel latent Bayesian spatial model is proposed, which incorporates the spatial dependence of ...
Zongyuan Xia, Bo Tang, Long Qin, Huiguo Zhang, Xijian Hu   +4 more
doaj   +1 more source

مدل‌بندی داده‌های فضایی-زمانی با گمشدگی غیرقابل چشم پوشی [PDF]

مدل‌سازی پیشرفته ریاضی, 2020
غلب داده‌های فضایی و فضایی-زمانی به واسطه شرایطی که تحت آن اندازه‌گیری‌ها صورت می‌گیرد حاوی مقادیر گمشده هستند. مقادیر گمشده‌ای که در فواصل مکانی یا زمانی نزدیک‌تر نسبت به مشاهدات قرار دارند شامل اطلاعات مفیدی هستند که درنظر گرفتن آن‌ها می‌تواند منجر به ...
محسن محمدزاده, سمیرا زحمت کش   +1 more
doaj   +1 more source

Modeling Influence of Soil Properties in Different Gradients of Soil Moisture: The Case of the Valencia Anchor Station Validation Site, Spain

Remote Sensing, 2021
The prediction of spatial and temporal variation of soil water content brings numerous benefits in the studies of soil. However, it requires a considerable number of covariates to be included in the study, complicating the analysis.
Ester Carbó, Pablo Juan, Carlos Añó, Somnath Chaudhuri, Carlos Diaz-Avalos, Ernesto López-Baeza   +5 more
doaj   +1 more source

Incorporating Biotic Information in Species Distribution Models: A Coregionalized Approach

Mathematics, 2021
In this work, we discuss the use of a methodological approach for modelling spatial relationships among species by means of a Bayesian spatial coregionalized model.
Xavier Barber, David Conesa, Antonio López-Quílez , Joaquín Martínez-Minaya , Iosu Paradinas, Maria Grazia Pennino   +5 more
doaj   +1 more source

A geostatistical model for combined analysis of point-level and area-level data using INLA and SPDE

Spatial Statistics, 2017
Paula Moraga, Susanna M Cramb, Kerrie Mengersen   +2 more
exaly   +2 more sources

Accounting for unobserved spatial variation in step selection analyses of animal movement via spatial random effects

Methods in Ecology and Evolution, 2023
Step selection analysis (SSA) is a common framework for understanding animal movement and resource selection using telemetry data. Such data are, however, inherently autocorrelated in space, a complication that could impact SSA‐based inference if left ...
Rafael Arce Guillen, Finn Lindgren, Stefanie Muff, Thomas W. Glass, Greg A. Breed, Ulrike E. Schlägel   +5 more
doaj   +1 more source

Prediction and Surveillance Sampling Assessment in Plant Nurseries and Fields

Applied Sciences, 2022
In this paper, we propose a structured additive regression (STAR) model for modeling the occurrence of a disease in fields or nurseries. The methodological approach involves a Gaussian field (GF) affected by a spatial process represented by an ...
Nora C. Monsalve, Antonio López-Quílez
doaj   +1 more source