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.