TY - JOUR

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.

KW - Carbon farming

KW - Common agricultural policy

KW - Deep learning

KW - Earth observation

KW - Food security

KW - Hyperspectral

KW - Soil organic carbon

KW - Spectral signatures

UR - http://www.scopus.com/inward/record.url?scp=85118704392&partnerID=8YFLogxK

U2 - 10.3390/rs13214439

DO - 10.3390/rs13214439

M3 - Book/Film/Article review in journal

AN - SCOPUS:85118704392

VL - 13

JO - Remote sensing

JF - Remote sensing

SN - 2072-4292

IS - 21

M1 - 4439

ER -