Workshops held in Norway, France, Poland and the Czech Republic identified gaps and proposed measures to remedy them. The most important 3 gaps and measures to cope with them were:
- A lack of information on existing data, theoretical and practical knowledge on processing, and know-how for end-users other than researchers.
Suggestions: (i) provide training; (ii) strengthen collaborations between remote sensing experts and soil experts on the one hand, and between scientists and other end-users on the other; (iii) provide access to data via a single, well-documented web interface;
- Most sensors do not penetrate the soil, can only characterize bare soil, and have signal affected by clouds and the atmosphere.
Suggestions: (i) Couple in situ data and available covariates (accessible imaging proxies) with models; (ii) Use airborne gamma-ray spectrometry; (iii) Use process-based model inversion.
- Lack of harmonization (i.e. heterogeneity of methods and products).
Suggestions: (i) Clearly inform the user of what has been done to obtain the products; (ii) Ensure interoperability between different products, standardized methods and procedures; (iii) Request access to a confidence interval to assess product quality.
Do you agree with these shortcomings? Would you like to add other gaps and/or suggest other ways of dealing with those identified? Please feel free to respond in your local language if that's easier for you. Thank you very much for your constructive input. 😉
