Kriging and Gaussian Process Interpolation for Georeferenced Data Augmentation Article Swipe
Frédérick Fabre Ferber
,
Dominique Gay
,
J Soulié
,
Jean Diatta
,
Odalric-Ambrym Maillard
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2501.07183
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2501.07183
Data augmentation is a crucial step in the development of robust supervised learning models, especially when dealing with limited datasets. This study explores interpolation techniques for the augmentation of geo-referenced data, with the aim of predicting the presence of Commelina benghalensis L. in sugarcane plots in La R{é}union. Given the spatial nature of the data and the high cost of data collection, we evaluated two interpolation approaches: Gaussian processes (GPs) with different kernels and kriging with various variograms. The objectives of this work are threefold: (i) to identify which interpolation methods offer the best predictive performance for various regression algorithms, (ii) to analyze the evolution of performance as a function of the number of observations added, and (iii) to assess the spatial consistency of augmented datasets. The results show that GP-based methods, in particular with combined kernels (GP-COMB), significantly improve the performance of regression algorithms while requiring less additional data. Although kriging shows slightly lower performance, it is distinguished by a more homogeneous spatial coverage, a potential advantage in certain contexts.
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- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2501.07183
- https://arxiv.org/pdf/2501.07183
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4406204722
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4406204722Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2501.07183Digital Object Identifier
- Title
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Kriging and Gaussian Process Interpolation for Georeferenced Data AugmentationWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-01-13Full publication date if available
- Authors
-
Frédérick Fabre Ferber, Dominique Gay, J Soulié, Jean Diatta, Odalric-Ambrym MaillardList of authors in order
- Landing page
-
https://arxiv.org/abs/2501.07183Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2501.07183Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2501.07183Direct OA link when available
- Concepts
-
Kriging, Georeference, Interpolation (computer graphics), Gaussian process, Process (computing), Gaussian, Variogram, Computer science, Geodesy, Mathematics, Statistics, Remote sensing, Geography, Computer graphics (images), Physical geography, Physics, Quantum mechanics, Operating system, AnimationTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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