A European soil organic carbon monitoring system leveraging Sentinel 2 imagery and the LUCAS soil data base

Research output: Contribution to journalArticleResearchpeer review

Authors

  • Bas van Wesemael
  • Asmaa Abdelbaki
  • Eyal Ben-Dor
  • Sabine Chabrillat
  • Pablo d'Angelo
  • José A.M. Demattê
  • Giulio Genova
  • Asa Gholizadeh
  • Uta Heiden
  • Paul Karlshoefer
  • Robert Milewski
  • Laura Poggio
  • Marmar Sabetizade
  • Adrián Sanz
  • Peter Schwind
  • Nikolaos Tsakiridis
  • Nikolaos Tziolas
  • Julia Yagüe
  • Daniel Žížala

Research Organisations

External Research Organisations

  • Université catholique de Louvain (UCL)
  • Helmholtz Centre Potsdam - German Research Centre for Geosciences (GFZ)
  • Fayoum University (FU)
  • Tel Aviv University
  • German Aerospace Center (DLR)
  • Universidade de Sao Paulo
  • Wageningen University and Research
  • Czech University of Life Sciences Prague
  • GMV Aerospace and Defence S.A.
  • Aristotle University of Thessaloniki (A.U.Th.)
  • University of Florida (UF)
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Details

Original languageEnglish
Article number117113
JournalGEODERMA
Volume452
Early online date26 Nov 2024
Publication statusPublished - Dec 2024

Abstract

The Worldsoils project has developed a pre-operational Soil Organic Carbon (SOC) monitoring system in a cloud environment. The system predicts topsoil organic carbon content at regional and continental scales from Earth Observation (EO) satellite data with a continuous cover over Europe. The system utilizes spectral models for croplands and a digital soil mapping approach for permanently vegetated areas such as grasslands and forests. Models strongly rely on soil reflectance composites from the Sentinel 2 multispectral instrument providing the median reflectance for all valid pixels over a period of three years. The bare soil frequency, a proxy for the degree of crop cover, is clearly lower in a Mediterranean pilot region compared to croplands in temperate regions. This is due to the extensive crop cover in the Mediterranean with winter cereals and fodder crops. The graphical user interface provides SOC content and the prediction interval ratio (i.e. 90 % uncertainty interval divided by the median) for 50 m pixels in three pilot regions and 100 m pixels for the rest of Europe. The SOC prediction algorithms are reasonable compared to others at the continental scale (R2: 0.41 for croplands and 0.28 for permanently vegetated areas). Apart from tree crops in Macedonia (Greece) the soil reflectance composite attributes the correct model to validation sets of cropland and grassland in the pilot regions. The SOC prediction is satisfactory in Wallonia (Belgium; R2 0.51) but is less accurate in Greece and the Czech Republic. In particular in Greece, the poor performance is linked to the low bare soil frequency due to the abundance of tree crops, cereals and fodder crops. The monitoring system can reproduce spatial patterns in SOC content similar to the ones obtained from a detailed regional algorithm using the new generation of hyperspectral satellites. However, the very high values in kettle holes in a morainic landscape of Northern Germany are underestimated.

Keywords

    European soil monitoring, LUCAS soil, Sentinel-2, SOC content, Soil parameter modelling, Temporal composite, Validation

ASJC Scopus subject areas

Cite this

A European soil organic carbon monitoring system leveraging Sentinel 2 imagery and the LUCAS soil data base. / van Wesemael, Bas; Abdelbaki, Asmaa; Ben-Dor, Eyal et al.
In: GEODERMA, Vol. 452, 117113, 12.2024.

Research output: Contribution to journalArticleResearchpeer review

van Wesemael, B, Abdelbaki, A, Ben-Dor, E, Chabrillat, S, d'Angelo, P, Demattê, JAM, Genova, G, Gholizadeh, A, Heiden, U, Karlshoefer, P, Milewski, R, Poggio, L, Sabetizade, M, Sanz, A, Schwind, P, Tsakiridis, N, Tziolas, N, Yagüe, J & Žížala, D 2024, 'A European soil organic carbon monitoring system leveraging Sentinel 2 imagery and the LUCAS soil data base', GEODERMA, vol. 452, 117113. https://doi.org/10.1016/j.geoderma.2024.117113
van Wesemael, B., Abdelbaki, A., Ben-Dor, E., Chabrillat, S., d'Angelo, P., Demattê, J. A. M., Genova, G., Gholizadeh, A., Heiden, U., Karlshoefer, P., Milewski, R., Poggio, L., Sabetizade, M., Sanz, A., Schwind, P., Tsakiridis, N., Tziolas, N., Yagüe, J., & Žížala, D. (2024). A European soil organic carbon monitoring system leveraging Sentinel 2 imagery and the LUCAS soil data base. GEODERMA, 452, Article 117113. https://doi.org/10.1016/j.geoderma.2024.117113
van Wesemael B, Abdelbaki A, Ben-Dor E, Chabrillat S, d'Angelo P, Demattê JAM et al. A European soil organic carbon monitoring system leveraging Sentinel 2 imagery and the LUCAS soil data base. GEODERMA. 2024 Dec;452:117113. Epub 2024 Nov 26. doi: 10.1016/j.geoderma.2024.117113
van Wesemael, Bas ; Abdelbaki, Asmaa ; Ben-Dor, Eyal et al. / A European soil organic carbon monitoring system leveraging Sentinel 2 imagery and the LUCAS soil data base. In: GEODERMA. 2024 ; Vol. 452.
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abstract = "The Worldsoils project has developed a pre-operational Soil Organic Carbon (SOC) monitoring system in a cloud environment. The system predicts topsoil organic carbon content at regional and continental scales from Earth Observation (EO) satellite data with a continuous cover over Europe. The system utilizes spectral models for croplands and a digital soil mapping approach for permanently vegetated areas such as grasslands and forests. Models strongly rely on soil reflectance composites from the Sentinel 2 multispectral instrument providing the median reflectance for all valid pixels over a period of three years. The bare soil frequency, a proxy for the degree of crop cover, is clearly lower in a Mediterranean pilot region compared to croplands in temperate regions. This is due to the extensive crop cover in the Mediterranean with winter cereals and fodder crops. The graphical user interface provides SOC content and the prediction interval ratio (i.e. 90 % uncertainty interval divided by the median) for 50 m pixels in three pilot regions and 100 m pixels for the rest of Europe. The SOC prediction algorithms are reasonable compared to others at the continental scale (R2: 0.41 for croplands and 0.28 for permanently vegetated areas). Apart from tree crops in Macedonia (Greece) the soil reflectance composite attributes the correct model to validation sets of cropland and grassland in the pilot regions. The SOC prediction is satisfactory in Wallonia (Belgium; R2 0.51) but is less accurate in Greece and the Czech Republic. In particular in Greece, the poor performance is linked to the low bare soil frequency due to the abundance of tree crops, cereals and fodder crops. The monitoring system can reproduce spatial patterns in SOC content similar to the ones obtained from a detailed regional algorithm using the new generation of hyperspectral satellites. However, the very high values in kettle holes in a morainic landscape of Northern Germany are underestimated.",
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AU - van Wesemael, Bas

AU - Abdelbaki, Asmaa

AU - Ben-Dor, Eyal

AU - Chabrillat, Sabine

AU - d'Angelo, Pablo

AU - Demattê, José A.M.

AU - Genova, Giulio

AU - Gholizadeh, Asa

AU - Heiden, Uta

AU - Karlshoefer, Paul

AU - Milewski, Robert

AU - Poggio, Laura

AU - Sabetizade, Marmar

AU - Sanz, Adrián

AU - Schwind, Peter

AU - Tsakiridis, Nikolaos

AU - Tziolas, Nikolaos

AU - Yagüe, Julia

AU - Žížala, Daniel

N1 - Publisher Copyright: © 2024 The Author(s)

PY - 2024/12

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N2 - The Worldsoils project has developed a pre-operational Soil Organic Carbon (SOC) monitoring system in a cloud environment. The system predicts topsoil organic carbon content at regional and continental scales from Earth Observation (EO) satellite data with a continuous cover over Europe. The system utilizes spectral models for croplands and a digital soil mapping approach for permanently vegetated areas such as grasslands and forests. Models strongly rely on soil reflectance composites from the Sentinel 2 multispectral instrument providing the median reflectance for all valid pixels over a period of three years. The bare soil frequency, a proxy for the degree of crop cover, is clearly lower in a Mediterranean pilot region compared to croplands in temperate regions. This is due to the extensive crop cover in the Mediterranean with winter cereals and fodder crops. The graphical user interface provides SOC content and the prediction interval ratio (i.e. 90 % uncertainty interval divided by the median) for 50 m pixels in three pilot regions and 100 m pixels for the rest of Europe. The SOC prediction algorithms are reasonable compared to others at the continental scale (R2: 0.41 for croplands and 0.28 for permanently vegetated areas). Apart from tree crops in Macedonia (Greece) the soil reflectance composite attributes the correct model to validation sets of cropland and grassland in the pilot regions. The SOC prediction is satisfactory in Wallonia (Belgium; R2 0.51) but is less accurate in Greece and the Czech Republic. In particular in Greece, the poor performance is linked to the low bare soil frequency due to the abundance of tree crops, cereals and fodder crops. The monitoring system can reproduce spatial patterns in SOC content similar to the ones obtained from a detailed regional algorithm using the new generation of hyperspectral satellites. However, the very high values in kettle holes in a morainic landscape of Northern Germany are underestimated.

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