Earth observation data-driven cropland soil monitoring: A review

Research output: Contribution to journalBook/Film/Article review in journalResearchpeer review

Authors

  • Nikolaos Tziolas
  • Nikolaos Tsakiridis
  • Sabine Chabrillat
  • José A.M. Demattê
  • Eyal Ben-Dor
  • Asa Gholizadeh
  • George Zalidis
  • Bas van Wesemael

Research Organisations

External Research Organisations

  • Aristotle University of Thessaloniki (A.U.Th.)
  • Universidade de Sao Paulo
  • Tel Aviv University
  • Czech University of Life Sciences Prague
  • Université catholique de Louvain (UCL)
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Details

Original languageEnglish
Article number4439
JournalRemote sensing
Volume13
Issue number21
Publication statusPublished - 4 Nov 2021

Abstract

We conducted a systematic review and inventory of recent research achievements related to spaceborne and aerial Earth Observation (EO) data-driven monitoring in support of soil-related strategic goals for a three-year period (2019–2021). Scaling, resolution, data characteristics, and modelling approaches were summarized, after reviewing 46 peer-reviewed articles in international journals. Inherent limitations associated with an EO-based soil mapping approach that hinder its wider adoption were recognized and divided into four categories: (i) area covered and data to be shared; (ii) thresholds for bare soil detection; (iii) soil surface conditions; and (iv) infrastructure capabilities. Accordingly, we tried to redefine the meaning of what is expected in the next years for EO data-driven topsoil monitoring by performing a thorough analysis driven by the upcoming technological waves. The review concludes that the best practices for the advancement of an EO data-driven soil mapping include: (i) a further leverage of recent artificial intelligence techniques to achieve the desired representativeness and reliability; (ii) a continued effort to share harmonized labelled datasets; (iii) data fusion with in situ sensing systems; (iv) a continued effort to overcome the current limitations in terms of sensor resolution and processing limitations of this wealth of EO data; and (v) political and administrative issues (e.g., funding, sustainability). This paper may help to pave the way for further interdisciplinary research and multi-actor coordination activities and to generate EO-based benefits for policy and economy.

Keywords

    Carbon farming, Common agricultural policy, Deep learning, Earth observation, Food security, Hyperspectral, Soil organic carbon, Spectral signatures

ASJC Scopus subject areas

Sustainable Development Goals

Cite this

Earth observation data-driven cropland soil monitoring: A review. / Tziolas, Nikolaos; Tsakiridis, Nikolaos; Chabrillat, Sabine et al.
In: Remote sensing, Vol. 13, No. 21, 4439, 04.11.2021.

Research output: Contribution to journalBook/Film/Article review in journalResearchpeer review

Tziolas, N, Tsakiridis, N, Chabrillat, S, Demattê, JAM, Ben-Dor, E, Gholizadeh, A, Zalidis, G & van Wesemael, B 2021, 'Earth observation data-driven cropland soil monitoring: A review', Remote sensing, vol. 13, no. 21, 4439. https://doi.org/10.3390/rs13214439
Tziolas, N., Tsakiridis, N., Chabrillat, S., Demattê, J. A. M., Ben-Dor, E., Gholizadeh, A., Zalidis, G., & van Wesemael, B. (2021). Earth observation data-driven cropland soil monitoring: A review. Remote sensing, 13(21), Article 4439. https://doi.org/10.3390/rs13214439
Tziolas N, Tsakiridis N, Chabrillat S, Demattê JAM, Ben-Dor E, Gholizadeh A et al. Earth observation data-driven cropland soil monitoring: A review. Remote sensing. 2021 Nov 4;13(21):4439. doi: 10.3390/rs13214439
Tziolas, Nikolaos ; Tsakiridis, Nikolaos ; Chabrillat, Sabine et al. / Earth observation data-driven cropland soil monitoring : A review. In: Remote sensing. 2021 ; Vol. 13, No. 21.
Download
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abstract = "We conducted a systematic review and inventory of recent research achievements related to spaceborne and aerial Earth Observation (EO) data-driven monitoring in support of soil-related strategic goals for a three-year period (2019–2021). Scaling, resolution, data characteristics, and modelling approaches were summarized, after reviewing 46 peer-reviewed articles in international journals. Inherent limitations associated with an EO-based soil mapping approach that hinder its wider adoption were recognized and divided into four categories: (i) area covered and data to be shared; (ii) thresholds for bare soil detection; (iii) soil surface conditions; and (iv) infrastructure capabilities. Accordingly, we tried to redefine the meaning of what is expected in the next years for EO data-driven topsoil monitoring by performing a thorough analysis driven by the upcoming technological waves. The review concludes that the best practices for the advancement of an EO data-driven soil mapping include: (i) a further leverage of recent artificial intelligence techniques to achieve the desired representativeness and reliability; (ii) a continued effort to share harmonized labelled datasets; (iii) data fusion with in situ sensing systems; (iv) a continued effort to overcome the current limitations in terms of sensor resolution and processing limitations of this wealth of EO data; and (v) political and administrative issues (e.g., funding, sustainability). This paper may help to pave the way for further interdisciplinary research and multi-actor coordination activities and to generate EO-based benefits for policy and economy.",
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T1 - Earth observation data-driven cropland soil monitoring

T2 - A review

AU - Tziolas, Nikolaos

AU - Tsakiridis, Nikolaos

AU - Chabrillat, Sabine

AU - Demattê, José A.M.

AU - Ben-Dor, Eyal

AU - Gholizadeh, Asa

AU - Zalidis, George

AU - van Wesemael, Bas

N1 - Funding Information: Funding: This research was performed within the framework of the WORLDSOILS application project funded by the European Space Agency developed within the EO Science for Society slice of the 5th Earth Observation Envelope Program. This research was co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship, and Innovation, under the call RESEARCH–CREATE– INNOVATE (project code: T2EDK-00866).

PY - 2021/11/4

Y1 - 2021/11/4

N2 - We conducted a systematic review and inventory of recent research achievements related to spaceborne and aerial Earth Observation (EO) data-driven monitoring in support of soil-related strategic goals for a three-year period (2019–2021). Scaling, resolution, data characteristics, and modelling approaches were summarized, after reviewing 46 peer-reviewed articles in international journals. Inherent limitations associated with an EO-based soil mapping approach that hinder its wider adoption were recognized and divided into four categories: (i) area covered and data to be shared; (ii) thresholds for bare soil detection; (iii) soil surface conditions; and (iv) infrastructure capabilities. Accordingly, we tried to redefine the meaning of what is expected in the next years for EO data-driven topsoil monitoring by performing a thorough analysis driven by the upcoming technological waves. The review concludes that the best practices for the advancement of an EO data-driven soil mapping include: (i) a further leverage of recent artificial intelligence techniques to achieve the desired representativeness and reliability; (ii) a continued effort to share harmonized labelled datasets; (iii) data fusion with in situ sensing systems; (iv) a continued effort to overcome the current limitations in terms of sensor resolution and processing limitations of this wealth of EO data; and (v) political and administrative issues (e.g., funding, sustainability). This paper may help to pave the way for further interdisciplinary research and multi-actor coordination activities and to generate EO-based benefits for policy and economy.

AB - We conducted a systematic review and inventory of recent research achievements related to spaceborne and aerial Earth Observation (EO) data-driven monitoring in support of soil-related strategic goals for a three-year period (2019–2021). Scaling, resolution, data characteristics, and modelling approaches were summarized, after reviewing 46 peer-reviewed articles in international journals. Inherent limitations associated with an EO-based soil mapping approach that hinder its wider adoption were recognized and divided into four categories: (i) area covered and data to be shared; (ii) thresholds for bare soil detection; (iii) soil surface conditions; and (iv) infrastructure capabilities. Accordingly, we tried to redefine the meaning of what is expected in the next years for EO data-driven topsoil monitoring by performing a thorough analysis driven by the upcoming technological waves. The review concludes that the best practices for the advancement of an EO data-driven soil mapping include: (i) a further leverage of recent artificial intelligence techniques to achieve the desired representativeness and reliability; (ii) a continued effort to share harmonized labelled datasets; (iii) data fusion with in situ sensing systems; (iv) a continued effort to overcome the current limitations in terms of sensor resolution and processing limitations of this wealth of EO data; and (v) political and administrative issues (e.g., funding, sustainability). This paper may help to pave the way for further interdisciplinary research and multi-actor coordination activities and to generate EO-based benefits for policy and economy.

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KW - Common agricultural policy

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KW - Earth observation

KW - Food security

KW - Hyperspectral

KW - Soil organic carbon

KW - Spectral signatures

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