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TOOLS

Our team developed geospatial tools to enhance your geospatial analysis, streamlining processes for greater speed, accuracy, and automation.

1. Optimal scaling of predictors for digital mapping of soil properties

This R script enhances soil property mapping accuracy by optimizing terrain attribute scaling using Random Forests (RF). It demonstrated the effectiveness of optimized scaling for nine soil properties.

    The script resamples a digital elevation model (DEM) at multiple resolutions and finds the optimal scales for each terrain attribute specific to each soil property.

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    For more information about the script, please refer to our published paper:

    Reference: Dornik A, Cheţan MA, Drăguţ L, Dicu DD, Iliuţă A, 2022, Optimal scaling of predictors for digital mapping of soil properties, Geoderma (IF 6.1; AIS 1.221; Q1), 405:115453, DOI: 10.1016/j.geoderma.2021.115453

    DATASETS

    1. Land suitability in temperate Europe

    This dataset includes land suitability maps for several crops and land uses (14 crops, 7 fruit trees, 3 land-use types) in the temperate continental climate of Europe. To model the land suitability we used geospatial data depicting seventeen eco-pedological indicators (e.g. soil texture, pH, porosity, temperature, precipitation, slope).

    https://esdac.jrc.ec.europa.eu/content/land-suitability-temperate-europe

    Reference: Dornik, A., Cheţan, M.A., Crişan, T.E., Heciko, R., Gora, A., Drăguţ, L. and Panagos, P., 2024. Geospatial evaluation of the agricultural suitability and land use compatibility in Europe’s temperate continental climate region. International Soil and Water Conservation Research. DOI: 10.1016/j.iswcr.2024.01.002