Earth Observation Data-Driven Cropland Soil Monitoring: A Review

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Tziolas, N.; Tsakiridis, N.; Chabrillat, S.; Demattê, J.A.M.; Ben-Dor, E. et al.: Earth Observation Data-Driven Cropland Soil Monitoring: A Review. In: Remote Sensing 13 (2021), Nr. 21, 4439. DOI: https://doi.org/10.3390/rs13214439

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Sum total of downloads: 24




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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.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2021
Appears in Collections:Naturwissenschaftliche Fakultät

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pos. country downloads
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1 image of flag of Germany Germany 12 50.00%
2 image of flag of United States United States 4 16.67%
3 image of flag of Ireland Ireland 2 8.33%
4 image of flag of Indonesia Indonesia 2 8.33%
5 image of flag of Hungary Hungary 1 4.17%
6 image of flag of France France 1 4.17%
7 image of flag of Egypt Egypt 1 4.17%
8 image of flag of China China 1 4.17%

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