Results 41 to 50 of about 20,099 (254)

On the uncertainty of stream networks derived from elevation data: the error propagation approach [PDF]

, 2010
DEM error propagation methodology is extended to the derivation of vector-based objects (stream networks) using geostatistical simulations. First, point sampled elevations are used to fit a variogram model.
Hengl, T., Heuvelink, G.B.M., Loon, E.E., van   +2 more
core   +2 more sources

Advancing Cave Survey Methods: High‐Precision Mapping in Drakotrypa Cave, Greece

Archaeological Prospection, EarlyView.
ABSTRACT Cave floor mapping plays a vital role across various scientific disciplines by enabling the identification and interpretation of features shaped by both natural processes and human activity. In cave archaeology, floor mapping is crucial to decode and reconstruct human‐induced morphological features.
Christos Pennos, Fotis Georgiadis, Sofia Pechlivanidou, Rannveig Ø. Skoglund, Nenad Buzjak, Stein‐ Erik Lauritzen   +5 more
wiley   +1 more source

Geostatistics and artificial intelligence coupling: advanced machine learning neural network regressor for experimental variogram modelling using Bayesian optimization

Frontiers in Earth Science
Experimental variogram modelling is an essential process in geostatistics. The use of artificial intelligence (AI) is a new and advanced way of automating experimental variogram modelling.
Saâd Soulaimani, Saâd Soulaimani, Ayoub Soulaimani, Kamal Abdelrahman, Abdelhalim Miftah, Mohammed S. Fnais, Biraj Kanti Mondal   +6 more
doaj   +1 more source

On the spatial clustering of behavioural phenotypes: matching movement tactics with landscape structure in a large herbivore

Oikos, EarlyView.
In the wild, individuals consistently differ in movement and space use behaviours, depending on their personality. This variation can lead to personality–habitat associations and spatial structuring, potentially generating individual niche segregation.
Inès Khazar, Nadège C. Bonnot, A. J. Mark Hewison, Nathan Ranc, Arnaud Bonnet, Yannick Chaval, Bruno Lourtet, Nicolas Morellet   +7 more
wiley   +1 more source

A geostatistical model based on Brownian motion to Krige regions in R2 with irregular boundaries and holes [PDF]

, 2019
Master's Project (M.S.) University of Alaska Fairbanks, 2019Kriging is a geostatistical interpolation method that produces predictions and prediction intervals.
Bernard, Jordy
core  

Kriging Interpolating Cosmic Velocity Field

, 2015
[abridged] Volume-weighted statistics of large scale peculiar velocity is preferred by peculiar velocity cosmology, since it is free of uncertainties of galaxy density bias entangled in mass-weighted statistics.
Jing, Yipeng, Yu, Yu, Zhang, Jun, Zhang, Pengjie   +3 more
core   +1 more source

A composite‐loss graph neural network for the multivariate post‐processing of ensemble weather forecasts

Quarterly Journal of the Royal Meteorological Society, EarlyView.
The dual graph neural network (dualGNN), trained with a composite loss combining the energy score (ES) and variogram score (VS), consistently outperformed models optimized solely for ES or the continuous ranked probability score in the multivariate setting, as well as empirical copula approaches.
Mária Lakatos
wiley   +1 more source

Critical Analysis of the Snow Survey Network According to the Spatial Variability of Snow Water Equivalent (SWE) on Eastern Mainland Canada

Hydrology, 2019
In Eastern Canada, the snow survey network is highly optimized at the operational scale. However, it is commonly accepted that the network is limited when it comes to studying the spatial variability of the snow water equivalent (SWE), which forms ...
Yawu Noumonvi Sena, Karem Chokmani, Erwan Gloaguen, Monique Bernier   +3 more
doaj   +1 more source

Surface roughness measurements using UAV LiDAR and analysis of uncertainty factors

River, EarlyView.
Abstract Surface root mean square height (SRMSH) is a key parameter characterizing surface roughness; it reflects soil hydrological properties and influences related physical processes. LiDAR offers an effective means for measuring SRMSH over large areas, yet the method involves several uncertainty factors that require further investigation.
Xiangdong Qin, Zhiguo Pang, Jingxuan Lu
wiley   +1 more source

A geostatistical approach for predicting the top producing formation in oil fields

Geodesy and Cartography, 2012
Drilling engineer's understanding of the subsurface conditions of oil-rich regions in Iran is based on experience and through quantitative assessment of these valuable data.
Mohammad Abdideh, Majed Abyat
doaj   +1 more source