DOI: 10.5281/zenodo.14039385
title: Maps of topsoil (0-30 cm) properties of Tuscany (Italy)

description: The internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.

The topsoil (0-30 cm) properties maps are prepared to evaluate soil ecosystem services in SERENA/EJP-Soil and for applying SOC loss Cookbook and SOIL Loss Cookbook. In particular Soil Organic Carbon content map was directly considered as an application of SOC loss Cookbook (DOI: 10.5281/zenodo.13951265 Version 3).

They are based on Tuscany Region soil database available at Geoscopio (https://www502.regione.toscana.it/geoscopio/pedologia.html) and on point soil data not freely available (Lamma Consortium). More information and requests to: info@lamma.toscana.it.

In accordance with the methodology reported in the Soil Organic Carbon Mapping Cookbook (Yigini et al., 2018), the following soil properties were mapped for all Tuscany Region:



soil organic carbon content (dag/kg),

soil organic carbon stock (t/ha),

textural fractions (sand, silt and clay, USDA limits, dag/kg),

rock fragments (vol/vol),

pH in water,

bulk density (g/cm3).


They were obtained through Digital Soil Mapping (DSM) approach, based on correlations with numerous environmental factors and using Random Forest algorithm.

All the maps have a 100 m spatial resolution.
description: Several spatial covariates, both categorical and numerical, were prepared for data processing: morphometric indices elaborated from DEM; meteorological indices; thematic data such as lithology, soil map and land use; vegetation indices from remote sensing (NDVI, SWIR). The Random Forest algorithm was used to explore the quantitative relationship between environmental variables and target soil properties and to predict the results with multivariate forecasting techniques.

The data are derived from the calculation of indicators based on a standard methodology established as part of the EJP Soil SERENA programme. Please keep in mind that:

·         It is the result of a modelling exercise and does not necessarily reflect reality.

·         Despite the efforts made to provide reliable data, the results may contain inconsistencies, depending in particular on the raw data available and level of accuracy of the techniques chosen and their prior knowledge.

·         It is necessary to consider how the results have been obtained in order to decide on their relevance in relation to the intended purpose of reuse.

·         These results are interesting from a scientific point of view, but their use for environmental management and policy issues should be done keeping the previous aspects in mind and complementing, when necessary, the provided results with the best available data.

Finally, it is the responsibility of the users of this information to decide whether it is appropriate to use these data and whether the data meet their needs. The authors of this resource can in no way be held responsible for the results obtained from the use of this data.