Use cases soil data
A selection of use cases, combined with dedicated guidance on how to increase FAIR aspect of a data or knowledge publication.
The cases are clustered in three topics:
- Soil observation data
- Soil Maps, predicted distribution of soil properties or soil classifications.
- Soil data related resources
Soil Observation data
Common aspects in describing observation data
While SoilWise supports an array of different encodings for observation data, each tailored for different usage areas, these models are united through the underlying conceptual OGC/ISO Observations, Measurements and Samples Standard, semantically formalized under W3C SSN/SOSA. This model entails the use of generic Observation concepts.
Tabular Soil Observation Data
Tabular formats such as Excel, CSV, Shapefile are a common approach to share Soil data. Locations as rows, observed properties as columns. Improving the metadata at column level offers an opportunity to describe these datasets more interoperable.
Soilwise prepared a tutorial which considers various aspects on existing practices and suggest minor optimisations and potential to this approach.
INSPIRE Soil data in a GeoPackage format
The GeoPackage format for sharing INSPIRE SOIL data is an approach to store data in a relational database while conforming to the INSPIRE Soil conceptual model. Traditionally INSPIRE Soil Observation data and maps require to be shared using a dedicated GML encoding, which was quite a challenge for both data procucers and consumers. The INSPIRE Good Practice using GeoPackage specifically for Soil data has been prepared by the EJP Soil H2020 programme and is further developed in the SoilWise project.
Earth imagery
Earth imagery such as satelite and drone data are increasingly used to better understand soils and their interaction with climate, landscape and crops. Imagery data is often used as a predictor of soil property distribution. Due to their size and origin imagery data is usually not deposited in formal repositories, but available from mass storage such as Google Earth Engine, Copernicus or Amazon Cloud, which can be a challenge for citation of the material.
Soil maps
Traditional Soil maps
Soil maps visualize the distribution of soil properties in space. Properties visualised in maps are: Soil Classification, Soil thickness and Groundwater level. The maps are generated in field studies where experts analyse soil profiles at optimal locations based on landscape characteristics and then deliniate areas with similar charateristics.
For a given deliniated area a reference is made to (one or more) selected reference profiles, which best represent the soil in that area.
The relation between delineated areas and reference profiles is, amongst others, modelled in the INSPIRE Soil Data Model.
Digital Soil Maps
Digital Soil Maps, such as soil property distribution predictions, agricultural decision support and soil health indicator changes are increasingly produced using digital techniques.
An important factor to facilitate reuse is extensive description of lineage. Which source data and procedures have been used to derive the resulting product.