Using multispectral satellite imagery and machine learning to automate agroforestry soil organic carbon and biodiversity prediction across Europe

Poster presented by Dr Colin Tosh at the second European Carbon Farming Summit in Dublin 04-06 March, 2025. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency (REA). Neither the European Union nor the granting authority can be held responsible for them.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-04
DOI
https://doi.org/10.5281/zenodo.14968882
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.00
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article

Using multispectral satellite imagery and machine learning to automate agroforestry soil organic carbon and biodiversity prediction across Europe

Zenodo (CERN European Organization for Nuclear Research)
Remote Sensing in Agriculture
article

Using multispectral satellite imagery and machine learning to automate agroforestry soil organic carbon and biodiversity prediction across Europe

article en

Abstract

Poster presented by Dr Colin Tosh at the second European Carbon Farming Summit in Dublin 04-06 March, 2025. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency (REA). Neither the European Union nor the granting authority can be held responsible for them.

Zenodo (CERN European Organization for Nuclear Research)
Life in Land
Openalex Percentile: Top 50%
Remote Sensing in Agriculture
DOIOpen Access PDFOpenAlex
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Using multispectral satellite imagery and machine learning to automate agroforestry soil organic carbon and biodiversity prediction across Europe · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS