Results 91 to 100 of about 78,859 (235)

Post-processing Kriging with External Drift Estimates [PDF]

Geologia USP. Série Científica, 2009
Kriging with an external drift has been used for estimating a poorly sampled variable based on an exhaustively sampledsecondary variable. Even considering the information coming from secondary data, the estimates present smaller variancethan the sample ...
Jorge Kazuo Yamamoto
doaj  

Geostatistical Investigations of Displacements on the Basis of Data from the Geodetic Monitoring of a Hydrotechnical Object

Studia Geotechnica et Mechanica, 2017
Geostatistical methods make the analysis of measurement data possible. This article presents the problems directed towards the use of geostatistics in spatial analysis of displacements based on geodetic monitoring.
Namysłowska-Wilczyńska Barbara, Wynalek Janusz   +1 more
doaj   +1 more source

Expected Improvement in Efficient Global Optimization Through Bootstrapped Kriging - Replaces CentER DP 2010-62 [PDF]

This article uses a sequentialized experimental design to select simulation input com- binations for global optimization, based on Kriging (also called Gaussian process or spatial correlation modeling); this Kriging is used to analyze the input/output ...
Beers, W.C.M. van, Kleijnen, Jack P.C., Nieuwenhuyse, I. van   +2 more
core   +1 more source

Structured machine learning modeling to support conservation of deep‐sea benthic biodiversity

Conservation Biology, EarlyView.
Abstract Biodiversity monitoring programs need to deliver accurate, timely, and actionable predictions. To establish a predictive monitoring program for deep‐sea benthos of the Santos Basin, Brazil, we developed a two‐stage structured model that allowed comparison of biodiversity predictions obtained from environmental simulations (2M‐Sim).
Gustavo Fonseca, Danilo C. Vieira, Juliane C. Carneiro, Renato S. Carreira, Milena Ceccopieri, Thais N. Corbisier, Adriana Galindo Dalto, Alberto G. Figueiredo Jr., Fabiane Gallucci, Paula Gheller, Simone Brito de Jesus, Helena Passeri Lavrado, Letícia Lazzari, Eduardo Hilzendeger Marcon, Daniel Leite Moreira, Rafael Bendayan de Moura, Ellen Pape, Ana Cláudia Aoki Santarosa, João Regis dos Santos Filho, Silvia Helena de Mello e Sousa, Thaisa Marques Vicente, Luciana Erika Yaginuma, Cinthia Yamashita, Wandrey Watanabe   +23 more
wiley   +1 more source

Geostatistical mapping and spatial variability of surficial sediment types on the Beaufort Sea shelf based on grain size data [PDF]

, 2012
The nearshore Beaufort Sea is a sensitive marine environment that is also the focus of oil and gas exploration. Offshore, the Beaufort Sea contains large potential reserves of hydrocarbons.
Blasco, S. M., Jerosch, Kerstin, Kostylev, V. E.   +2 more
core  

On Spatial Point Processes With Composition‐Valued Marks

International Statistical Review, EarlyView.
Summary Methods for marked spatial point processes with scalar marks have seen extensive development in recent years. While the impressive progress in data collection and storage capacities has yielded an immense increase in spatial point process data with highly challenging non‐scalar marks, methods for their analysis are not equally well developed ...
Matthias Eckardt, Mari Myllymäki, Sonja Greven   +2 more
wiley   +1 more source

Influence of parameter estimation uncertainty in Kriging: Part 1 - Theoretical Development [PDF]

Hydrology and Earth System Sciences, 2001
This paper deals with a theoretical approach to assessing the effects of parameter estimation uncertainty both on Kriging estimates and on their estimated error variance.
E. Todini, E. Todini
doaj  

A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces

International Statistical Review, EarlyView.
Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri, Bernardo Nipoti, Emilio Porcu, Philip White   +3 more
wiley   +1 more source

Evaluating Spatio-Temporal Kriging with Machine Learning Considering the Sources of Spatio-Temporal Variation

ISPRS International Journal of Geo-Information
Integrating spatio-temporal kriging with machine learning improves estimation accuracy by addressing complex spatial and temporal variations in spatio-temporal phenomena.
Min Jeong, Hyeongmo Koo
doaj   +1 more source

How Accurately Do Species Distribution Models Predict the Expansion of Invasive Insects, and Does Climate Data Choice Matter? Insights From the Invasion of Dryocosmus kuriphilus

Journal of Applied Entomology, EarlyView.
ABSTRACT Species distribution models (SDMs) are widely used to predict the spread of invasive species, yet their accuracy over time and the influence of climate data resolution remain unclear. Here, we examine the capacity of SDMs to predict the distribution and short‐term expansion of the invasive gall wasp Dryocosmus kuriphilus, and compare the ...
José Carlos Pérez‐Girón, Fernando Castedo‐Dorado, María Josefa Lombardero, Pedro Álvarez‐Álvarez   +3 more
wiley   +1 more source