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Proceedings/Recueil Des Communications Année : 2019

Investigating the harmonization of highly noisy heterogeneous datasets hand-collected over the same study domain

Résumé

The objective of this paper is to propose an approach to harmonise noisy spatial data acquired by different operators using (low-cost) hand-held sensors over the same spatial domain. In such cases, datasets need to be harmonised first to be comparable before decision making. This work proposes a methodology to address this issue in the case of nested and noisy spatial data. First, it proposes the implementation of a non-parametric test of Kolmogorov-Smirnov to determine if harmonisation is needed. Then, it proposes an aspatial harmonization method based on standardization. The method was applied on grape sugar content datasets collected by 2 hand-held spectrometers. Results showed that harmonizing a less confident dataset is interesting solely if the size of the trusted one is too small.
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Dates et versions

hal-02609783 , version 1 (16-05-2020)

Identifiants

Citer

L. Pichon, C. Leroux, V. Geraudie, J. Taylor, Bruno Tisseyre. Investigating the harmonization of highly noisy heterogeneous datasets hand-collected over the same study domain. 12th European Conference on Precision Agriculture, ECPA 2019, Jul 2019, Montpellier, France. Wageningen Academic Publishers, pp.735-741, 2019, 978-90-8686-337-2. ⟨10.3920/978-90-8686-888-9_91⟩. ⟨hal-02609783⟩
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