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Africa Soil Properties for iSDA Mapping
Data Science and Analytics
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About
Detailed soil analysis data powering iSDAsoil maps across Africa. This dataset is meticulously prepared in an analysis-ready format and serves as the foundation for training advanced models used to generate cutting-edge iSDAsoil maps. The purpose of this product is to provide high-quality, in-depth measurements of chemical and physical soil properties for research and development focused on the African continent.
Columns
The dataset contains 24 fields, providing locational, temporal, and chemical details about soil samples. Key fields include:
- longitude, latitude: Geographical coordinates (decimal degrees) of the soil sampling location.
- start_date, end_date: Fields used in combination to indicate the timespan over which the data were collected.
- horizon_lower, horizon_upper: The depth (in cm) of the bottom and top boundaries of the sampled soil layer, respectively.
- carbon_organic: Measurement of Organic Carbon by combustion after acidification (g/kg).
- nitrogen_total: Measurement of Total Nitrogen by combustion (g/kg).
- ph: Soil acidity measurement, taken in a 1:1 soil-water suspension.
- electrical_conductivity: Measurement of electrical conductivity using the Saturation Extract method (dS/m).
- aluminium_extractable, boron_extractable, calcium_extractable, copper_extractable, iron_extractable, magnesium_extractable, manganese_extractable, phosphorus_extractable, potassium_extractable, sodium_extractable, sulphur_extractable, zn_mehlich3: Various elemental measurements resulting from Mehlich3 extraction (mg/kg).
Distribution
The data is structured as a CSV file, labelled iSDA-Africa-soil-analysis.csv, with a total file size of 10.19 MB. The structure includes 24 fields. The recorded total number of values or records in the sample is approximately 49,225. Further detail on the distribution of valid values for each field is available upon request, as many sampled columns show a high percentage of missing values in the preliminary analysis.
Usage
Ideal applications for this dataset include:
- Training machine learning and regression models for high-resolution soil mapping.
- Advanced environmental and earth science research concerning African ecosystems.
- Developing precision agriculture tools and solutions based on soil nutrient profiles.
- Geospatial analysis and classification tasks related to land use and soil health.
- Time series analysis if the data is augmented with additional temporal context.
Coverage
The geographic scope focuses exclusively on soil analysis across the African continent. Temporal coverage is indicated by the start_date and end_date fields, which define the collection timespan for the data. The demographic scope is focused entirely on environmental attributes (soil chemical and physical properties) rather than human populations.
License
Attribution 4.0 International (CC BY 4.0)
Who Can Use It
- Geospatial Data Scientists: For developing predictive models of soil properties.
- Agricultural Technology Developers: For creating farm management tools requiring precise nutrient information.
- Academic Researchers: For studies in earth science, pedology, and environmental sustainability.
- Non-Governmental Organizations (NGOs): For informed decision-making regarding land reclamation and resource management in Africa.
Dataset Name Suggestions
- Africa Soil Properties for iSDA Mapping
- African Soil Geochemical Analysis Data
- Analysis-Ready Soil Samples of Africa
- iSDA Soil Nutrient Dataset
Attributes
Original Data Source: Africa Soil Properties for iSDA Mapping
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