On machine learning from environmental data

The application of machine learning (ML) algorithms for analyzing, modelling, and visualizing geospatial data has seen remarkable growth in recent years. Many ML techniques have proven to be both effective and efficient in addressing complex challenges within the geosciences. Selected topics on adaptation and application of ML to environmental data are briefly discussed in this research.

Authors

Publication Details

Journal
Cahiers du Centre de Linguistique et des Sciences du Langage
Published
2025-06-27
DOI
https://doi.org/10.26034/la.cdclsl.2025.8351
Primary Topic
Big Data Technologies and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

On machine learning from environmental data

Mikhaïl Kanevski
Cahiers du Centre de Linguistique et des Sciences du Langage
Big Data Technologies and Applications
article

On machine learning from environmental data

Mikhaïl Kanevski
article en

Abstract

The application of machine learning (ML) algorithms for analyzing, modelling, and visualizing geospatial data has seen remarkable growth in recent years. Many ML techniques have proven to be both effective and efficient in addressing complex challenges within the geosciences. Selected topics on adaptation and application of ML to environmental data are briefly discussed in this research.

Cahiers du Centre de Linguistique et des Sciences du Langage(69)
Openalex Percentile: Top 78%
Big Data Technologies and Applications
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On machine learning from environmental data — Mikhaïl Kanevski · Cahiers du Centre de Linguistique et des Sciences du Langage (2025) | TGRS Research Map | TGRS