Locally varying geostatistical machine learning for spatial prediction-Reference-Cited by-同舟云学术

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Locally varying geostatistical machine learning for spatial prediction

Published:2024-12 Issue: Volume:5 Page:100081
ISSN:2666-5441
Container-title:Artificial Intelligence in Geosciences
language:en
Short-container-title:Artificial Intelligence in Geosciences

Author:

Fouedjio Francky^ORCID,Arya Emet^ORCID

Publisher

Elsevier BV

Reference39 articles.

1. Random forests for spatially dependent data;Arkajyoti Saha;J. Amer. Statist. Assoc.,2023

2. Spatial modelling with Euclidean distance fields and machine learning;Behrens;Eur. J. Soil Sci,2018

3. Easy-to-use spatial random-forest-based downscaling-calibration method for producing precipitation data with high resolution and high accuracy;Chen;Hydrol. Earth Syst. Sci,2021

4. Geostatistics: Modeling Spatial Uncertainty;Chiles,2012

5. Geographically convolutional neural network weighted regression: A method for modeling spatially non-stationary relationships based on a global spatial proximity grid;Dai;Int. J. Geogr. Inf. Sci.,2022

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