Results 111 to 120 of about 7,767 (249)

An Adaptive Moving Window Kriging Based on K-Means Clustering for Spatial Interpolation

Algorithms
Ordinary kriging (OK) is a popular interpolation method for its ability to simultaneously minimize error variance and deliver statistically optimal and unbiased predictions. In this work, the adaptive moving window kriging with K-means clustering (AMWKK)
Nattakan Supajaidee, Nawinda Chutsagulprom, Sompop Moonchai   +2 more
doaj   +1 more source

Kriging with Unknown Variance Components for Regional Ionospheric Reconstruction

Sensors, 2017
Ionospheric delay effect is a critical issue that limits the accuracy of precise Global Navigation Satellite System (GNSS) positioning and navigation for single-frequency users, especially in mid- and low-latitude regions where variations in the ...
Ling Huang, Hongping Zhang, Peiliang Xu, Jianghui Geng, Cheng Wang, Jingnan Liu   +5 more
doaj   +1 more source

Key sources of uncertainty in process‐based modeling of live fuel moisture content

New Phytologist, EarlyView.
Location of the selected live fuel moisture content (LFMC) sampling sites. Summary Process‐based models that mechanistically represent water‐carbon balances in the atmosphere‐soil–plant continuum are an attractive tool for monitoring live fuel moisture content (LFMC) dynamics, a key variable when assessing fire danger.
Rodrigo Balaguer‐Romano, Albert Sañé, Nicolas Martin‐StPaul, Julien Ruffault, Eva Gabriel, Xavier Castro, François Pimont, Xiangzhuo Liu, Arsène Druel, Sylvain Delzon, Miquel De Cáceres   +10 more
wiley   +1 more source

Sediment transport and depositional hydrodynamics on the eastern Korean continental margin revealed by surface sediment granulometry

Sedimentology, EarlyView.
ABSTRACT Terrigenous sediments are transported from coastal areas and shelves to deeper continental margins by multiple processes. Understanding these processes is critical for evaluating the ecological impacts of fine‐grained sediment deposition and predicting future changes in sediment dispersal under rapid climate change.
Gyu Tae Sim, Jang Jun Bahk, Haedo Baek, Jun Ho Jang, In Kwon Um, Dong Eun Lee   +5 more
wiley   +1 more source

Remote sensing aided spatial prediction of forest stem volume [PDF]

, 2003
Modern technology such as the Global Positioning System (GPS) and Geographical Information Systems (GIS) provide new opportunities for forest inventory.
Jörgen Wallerman, Wallerman, Jörgen
core  

Mapping High‐Rate Clusters of Animal Contact‐Related Human Salmonella enterica Single‐State Outbreaks in the United States, 2009–2022: A Spatial Epidemiological Approach to Inform Public Health Surveillance

Zoonoses and Public Health, EarlyView.
ABSTRACT Introduction Nontyphoidal Salmonella enterica (NTS) is a major zoonotic enteric pathogen. Animal contact‐related NTS outbreaks have increased in the United States over the last decade. Geospatial analysis can identify locations with elevated risk of NTS outbreaks where public health authorities can focus their NTS prevention and intervention ...
Hammad Ur Rehman Bajwa, Suman Bhowmick, Csaba Varga   +2 more
wiley   +1 more source

Benchmarking Knowledge-assisted Kriging for Automated Spatial Interpolation of Wind Measurements

- We have benchmarked a novel knowledge-assisted kriging algorithm that allows regions of spatial cohesion to be specified and variograms calculated for each region.
Zlatev, Zlatko, Middleton, Stuart, Veres, Galina   +2 more
core  

Bayesian Implementation of the Factor‐Analytic Mixed Model and Application to Embeddings

Stat, Volume 15, Issue 3, September 2026.
ABSTRACT Mixed models and neural networks each offer complementary frameworks for prediction. Theoretically grounded in inference, mixed models can unveil latent variance structure notably with the factor‐analytic approach. In this article, we propose to bridge the gap between the two frameworks, leveraging embedding data from a neural network encoder ...
Alexandre Marchal, Maxence Lamure, Tanguy Lefort, Frank Imbach   +3 more
wiley   +1 more source

Kriging for Interpolation in Random Simulation

Whenever simulation requires much computer time, interpolation is needed. There are several interpolation techniques in use (for example, linear regression), but this paper focuses on Kriging.This technique was originally developed in geostatistics by D ...
Kleijnen, J.P.C., Beers, W.C.M. van
core  

CESAR: A Convolutional Echo State AutoencodeR for High‐Resolution Wind Forecasting

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract An accurate and timely assessment of wind speed and energy output allows an efficient planning and management of this resource on the power grid. Wind energy, especially at high resolution, calls for the development of nonlinear statistical models able to capture complex dependencies in space and time. This work introduces a Convolutional Echo
Matthew Bonas, Paolo Giani, Paola Crippa, Stefano Castruccio   +3 more
wiley   +1 more source