Geology, soil and seismic risk

Soil maps and derived thematic maps

Soil maps

Many maps are available in WMS format at the link https://servizigis.regione.emilia-romagna.it/wms/suoli

  • 1:250k Regional Soil Map - 1994
    Google Earth web site | Data downloadWMS
    This map describes soils and their geographical distribution in the Emilia-Romagna region at 1:250k scale.
  •  1:50k Soil map - 2021
    Google Earth web site | MinERva site | Data download WMS
    This map describes soils and their geographical distribution in the alluvial plain and in some parts of the Appennines at 1:50k scale. The map covers 78% of the regional territory: the whole plain, 93% of the hills and 23% of the mountains.
    Each polygon (delineation) of the soil map is identified by a numerical ID and it has a specific and unique soil component (soil type, percentage, distribution).
    The average area of the polygons is 467 ha in the plain, 71 ha in the hills and 31 ha in the mountains. Polygons with similar soil distribution form a Soil Mapping Unit (820 SMUs are described). N. 466 soil types (210 in the plain, 162 in the hills and 94 in the mountains) are identified and they are classified according to Soil Taxonomy (2010, 2014) and WRB (2007,2014).

  •  Local benchmark sites of the soils in the plain and in the hills - 2021 
    Google Earth web site | MinERva site  | Data download
    A  local benchmark site is linked to every soil type in every polygon of the 1:50k soil map: users can view and download chemical and physical analyses (sand, silt, clay, pH, organic carbon, total carbonate, bulk density and Ksat).

  • 1:10k Experimental farm soil map - 2005
    Google Earth web site
    This layer contains 1:10k soil maps of some experimental public farms in Emilia-Romagna region.

Maps of chemical and physical properties of soils

  • Extension Service soil analyses - 2021 
    MinERva site WMS
    These data are about 40.000 routine chemical-physical analyses (sand, silt, clay, pH, total carbonate, active carbonate, organic matter, available K, available P, total N) of soil samples (mostly on superficial horizons). Their use is for extension service in Agriculture and to improve the description of the soil polygons.

  •  Heavy metal data inventory - 2018
    MinERva site WMS
    This map is a point layer and it groups 1906 analyzed soil samples (heavy metals content with ICP-MS method) at depth 20-30 cm. This data have been used with a geo-statistical approach to make background maps of 8 heavy metals.

  •  Shallow Water Table Measurement Sites - 2021
    MinERva site | Data download WMS
    This map is a point layer and it groups 179 measurement sites of the shallow water table (0-3 m) in the whole plain of Emilia-Romagna region. Data of the water depth are collected about every 10 days.

  • Soil Organic Carbon: % content  in the 0-30 cm layer (1:50k). 3nd edition - 2023
    Google Earth web site | MinERva site | Data download WMS
    This map provides the estimated medium percentage content of Organic Carbon at the depth 0-30 cm in the soils of Emilia-Romagna region. It is a raster layer, with cells 100 m x 100 m wide. Each cell contains a classified value and a medium content (weight %) of Organic Carbon at the depth 0-30 cm. This value derives from geo-statistical analysis on point data, on the base of 1:50.000 Emilia- Romagna plain Soil Map and other covariates.

  • Soil Organic Carbon: % content in the 0-100 cm layer (1:50k) - 2016
    Google Earth web site | Data download WMS
    This map provides the estimated medium percentage content of Organic Carbon at the depth 0-100 cm in the alluvial plain of Emilia-Romagna region. It is a vector tiles layer, with cells 500m x 500m wide. Each cell contains a classified value and a medium content (weight %) of Organic Carbon at the depth 0-100 cm. This value derives from geo-statistical analysis on point data, on the base of 1:50,000 Emilia- Romagna plain Soil Map.

  • Soil texture in the 0-30 cm layer (1:50k) - 2023
    Google Earth web site | MinERva site | Data download WMS
    This map provides a valuation of the medium percentage content of sand, silt and clay at the depth 0-30 cm in the soils of Emilia-Romagna region. It is a raster layer, with cells 100m x 100m wide. Each cell contains a classified value and a medium content (weight %) of sand, silt, clay and skeleton percentage at the depth 0-30 cm. These values derive from geo-statistical analysis on point data, on the base of Emilia-Romagna Soil Map at 1:50,000 scale and other covariates.

  • Soil pH value in the 0-30 cm layer (1:50k) - 2023
    Google Earth web site | MinERva site | Data download WMS
    This map provides the estimated pH value at the depth 0-30 cm in the soils of Emilia-Romagna region. It is a rasters layer, with cells 100 m x 100 m wide. Each cell contains a classified value and a medium value of pH at the depth 0-30 cm. This value derives from geo-statistical analysis on point data, on the base of Emilia- Romagna Soil Map at 1:50,000 scale and other covariates.
  •  Pedo-geochemical map of 6 heavy metals of the soils of the plain (1:250k). 2nd edition - 2016
    Google Earth web site MinERva site Data download WMS
    The map represents the areal distribution of Cr, Cu, Ni, Pb, V, Zn concentration in the subsoil of agricultural soils (90-140 cm depth). This depth is assumed to be representative of the natural (pedo-geochemical) content according to ISO/DIS 19258, 2005.The geographical extension of geochemical data is based on 1:50.000 scale soil map. X-ray Fluorescence Spectrometry (XRF) has been used to determine the total content.

  • Chromium pedo-geochemical map of the soils of the plain (1:250k). 2nd edition - 2016
    Google Earth web site | MinERva site | Data download WMS
    The map represents the areal distribution of Chromium (Cr) concentration in the subsoil of agricultural soils (90-140 cm depth). This depth is assumed to be representative of the natural (pedo-geochemical) content according to ISO/DIS 19258, 2005.The geographical extension of geochemical data is based on 1:50.000 scale soil map. The prevailing factor that controls the natural content of Chromium in soil is the sediment provenance. X-ray Fluorescence Spectrometry (XRF) has been used to determine the total content. In the case of Chromium, aqua regia soluble content and ICP Mass Spectrometry determinations on the same samples usually provide lower values than XRF analyses (around 35% less on average value).

  • Nickel pedo-geochemical map of the soils of the plain (1:250k). 2nd edition - 2016
    Google Earth web site | MinERva site | Data download WMS
    The map represents the areal distribution of Nickel (Ni) concentration in the subsoil of agricultural soils (90-140 cm depth). This depth is assumed to be representative of the natural (pedo-geochemical) content, according to ISO/DIS 19258, 2005. The geographical extension of geochemical data is based on 1:50,000 scale soil map. The prevailing factor that controls the natural content of Nickel in soil is the sediment provenance. X-ray Fluorescence Spectrometry (XRF) has been used to determine the total content. In the case of Nickel, aqua regia soluble content and ICP Mass Spectometry determinations on the same samples usually provide lower values than XRF analyses (around 23 % less on average value).

  • Lead pedo-geochemical map of the soils of the plain (1:250k). 2nd edition - 2016
    Google Earth web site | MinERva site | Data download WMS
    The map represents the areal distribution of Lead (Pb) concentration in the subsoil of agricultural soils (90-140 cm depth). This depth is assumed to be representative of the natural (pedo-geochemical) content, according to ISO/DIS 19258, 2005. The geographical extension of geochemical data is based on 1:50,000 scale soil map. The prevailing factor that controls the natural content of Lead in soil is the sediment provenance but in Emilia-Romagna region there aren't igneous rocks so the Lead concentration is quite low. X-ray Fluorescence Spectrometry (XRF) has been used to determine the total content. In case of Lead, aqua regia soluble content and ICP Mass Spectrometry determinations on the same samples usually provide lower values than XRF analyses (around 7 % less on average value).

  • Copper pedo-geochemical map of the soils of the plain (1:250k). 2nd edition - 2016
    Google Earth web site | MinERva site | Data download WMS
    The map represents the areal distribution of Copper (Cu) concentration in the subsoil of agricultural soils (90-140 cm depth). This depth is assumed to be representative of the natural (pedo-geochemical) content, according to ISO/DIS 19258, 2005. The geographical extension of geochemical data is based on 1:50,000 scale soil map. There isn't a prevailing factor that controls natural content of Copper in soil: only the degree of weathering seems to have a little influence. X-ray Fluorescence Spectrometry (XRF) has been used to determine the total content. In the case of Copper, aqua regia soluble content and ICP Mass Spectrometry determinations on the same samples usually provide lower values than XRF analyses (around 17 % less on average value).

  • Vanadium pedo-geochemical map of the soils of the plain (1:250k). - 2016
    Google Earth web site | MinERva site | Data download WMS
    The map represents the areal distribution of Vanadium (V) concentration in the subsoil of agricultural soils (90-140 cm depth). This depth is assumed to be representative of the natural (pedo-geochemical) content, according to ISO/DIS 19258, 2005. The geographical extension of geochemical data is based on 1:50,000 scale soil map. The prevailing factor that controls natural content of Vanadium in soil is texture. X-ray Fluorescence Spectrometry (XRF) has been used to determine the total content. In the case of Vanadium, aqua regia soluble content and ICP Mass Spectrometry determinations on the same samples usually provide lower values than XRF analyses (around 37 % less on average value).

  • Zinc pedo-geochemical map of the soils of the plain (1:250k). 2nd edition - 2016
    Google Earth web site | MinERva site | Data download WMS
    The map represents the areal distribution of Zinc (Zn) concentration in the subsoil of agricultural soils (90-140 cm depth). This depth is assumed to be representative of the natural (pedo-geochemical) content, according to ISO/DIS 19258, 2005. The geographical extension of geochemical data is based on 1:50,000 scale soil map. The prevailing factor that controls natural content of Zinc in soil is texture. X-ray Fluorescence Spectrometry (XRF) has been used to determine the total content. In the case of Zinc, aqua regia soluble content and ICP Mass Spectrometry determinations on the same samples usually provide lower values than XRF analyses (around 15 % less on average value).

  • Salinity in the 0-50 cm layer in the soils of the plain (1:250k). 2nd edition - 2015
    Google Earth web site | MinERva site | Data download WMS
    This map shows the salinity of the soils at depth 0-50 cm in the plain area. It’s a representation derived by geo-statistical analysis on point data. It is a vector tiles layer, with cells 500 m x 500 m wide.Each cell contains salinity class according to USDA Soil Survey Manual (Richards, 1954), soil electrical conductivity (ECe in dSm-1) estimated value and a classified confidence value.

  • Salinity in the 50-100 cm layer in the soils of the plain (1:250k)
    Google Earth web site | MinERva site | Data download WMS
    This map shows the salinity of the soils at depth 50-100 cm in the plain area. It’s an early representation derived by geo-statistical analysis on point data. It is a vector tiles layer, with cells 1 km x 1 km wide. Each cell contains salinity class according to USDA Soil Survey Manual (Richards, 1954), a soil electrical conductivity (ECe in dSm-1) estimated value and a classified confidence value.

Special purpose maps

  • Land Capability (1: 50k) - 2021
    Google Earth web site | MinERva site | Data download WMS
    Land capability classification is a system of grouping soils primarily on the basis of their capability to produce common cultivated crops and pasture plants without deteriorating over a long period of time (U.S. Department of Agriculture, Natural Resources Conservation Service. National soil survey handbook). Land capability map is based on 1:50k Soil map (2021 edition). For each delineation, according to the specific proportion of major soil components, the assessment table SINA 2000 provides general guidance for assignments of the class and subclass and for describing limiting factors for the use of the soil.

  • Impermeable areas of the Emilia-Romagna plain - 2016
    Google Earth web site | Data download
    The map shows the different degrees of waterproofing of the Emilia-Romagna plain. Base data have been extrapolated from the topographic database (2008-2011 update). It is a raster layer, with cells 10 m x 10 m wide.

  • Soil Organic Carbon stock in the 0-30 cm layer in the soils of the plain (1:50k) - 2008
    Google Earth web site | MinERva site | Data download WMS
    This map shows the Organic Carbon stock (Mg/ha) in soils of the alluvial plain at 0-100 cm depth. It is a vector tiles layer, with cells 1 km x 1 km wide. The evaluated value considers different soil types distribution and the effect of the “not-soils bodies ” (e.g. deep water, buildings and infrastructures land cover). The stock of Organic Carbon of each cell is evaluated by geo-statistical analysis on point data, on the base of 1:50,000 Emilia-Romagna plain Soil Map; the selection between soil and no soil surfaces derives from 1:25k Land Use Map (2003 edition).

  • Soil Organic Carbon stock at depth 0-100 cm in the plain (1:50k) - 2008
    Google Earth web site | Data download WMS
    This map shows Organic Carbon stock (Mg/ha) in soils of hills and mountains at 0-30 cm depth. It is a vector tiles layer, with cells 1 km x 1 km wide. The evaluated value considers different soil types distribution and the effect of the “not-soils bodies” (e.g. deep water, buildings and infrastructures land cover). The stock of Organic Carbon of each cell is evaluated by geo-statistical analysis on point data, on the base of 1:50,000 Emilia-Romagna plain Soil Map; the selection between soil and no soil surfaces derives from 1:25k Land Use Map (2003 edition).

  • Soil Organic Carbon stock at depth 0-30 cm in the mountain (1:250k) - 2008
    Google Earth web site | MinERva site | Data download WMS
    This map shows Organic Carbon stock (Mg/ha) in soils of hills and mountains at 0-300 cm depth. It is a vector tiles layer, with cells 1 km x 1 km wide. The evaluated value considers different soil types distribution and the effect of the “not-soils bodies ” (e.g. deep water, buildings and infrastructures land cover). The stock of Organic Carbon of each cell is evaluated by geo-statistical analysis on point data, on the base of 1:250k Emilia-Romagna Soil Map; the selection between soil and no soil surfaces derives from 1:25k Land Use Map (2003 edition).

  • Soil Organic Carbon stock at depth 0-100 cm in the mountain (1:250k) - 2008
    Google Earth web site | Data download WMS
    This map shows Organic Carbon stock (Mg/ha) in soils of hills and mountains at 0-100 cm depth. It is a vector tiles layer, with cells 1 km x 1 km wide. The evaluated value considers different soil types distribution and the effect of the “not-soils bodies” (e.g. deep water, buildings and infrastructures land cover). The stock of Organic Carbon of each cell is evaluated by geo-statistical analysis on point data, on the base of 1:250k Emilia-Romagna Soil Map; the selection between soil and no soil surfaces derives from 1:25k Land Use Map (2003 edition).

  • Evaluation of Soil Organic Matter content in the 0-30 cm layer (1:50k). 3nd edition - 2023
    Google Earth web site | Data download WMS
    This map shows the classes of the organic matter content in the soils, having different agricultural potential. Evaluation schema refers to Disciplinari di Produzione Integrata (D.P.I. 2015) of Emilia-Romagna Region Extension Service. The classes are based on the relationship between clay content and organic matter accumulation and stabilization. It is a raster layer, with cells 100m x 100m wide.

  • Soil erosion (1:50k) - 2019
    Google Earth web site

    For the evaluation of water erosion, the Universal Soil Loss Equation by Wischmeier and Smith (USLE) was applied in the version by Renard et al. 1997. RUSLE provides an estimate of the soil loss due to water erosion expressed in Mg * ha-1 * year-1 as a long-term annual average. The estimated value is relative to specific combinations of slope, land use and management practices in a given climatic and environmental context.

  •  Map of background concentration of 9 heavy metals in soils of the plain (1:250k) - 2nd edition (2019)  
    Google Earth web site | Data downloadWMS
    This map represents the background concentration of As, Cd, Cr, Ni, Pb, Sn, V and Zn in the topsoil of cultivated soils. The upper limit of the “usual” background value defined for topsoil samples follows the ISO international standards (ISO/DIS 19528). It’s a vector tiles layer, with cells 1 km x 1 km wide. Each cell contains estimated values of 50° and 95° percentile (mg/kg). These values derive from a Scorpan Kriging approach that combines the trend of metal concentrations, as derived from the 1:50,000 soil map, with geostatistical modeling of the stochastic, locally varying but spatially correlated component. The background map is available only in the alluvial plain area.

  •  Ksat map in the plain. (1:50k). 2nd edition - 2018
    Google Earth web site | MinERva site | Data download WMS
    The map describes the areal distribution of Ksat soil classes according to the Soil Survey Manual scheme, 1993 through the polygons of the soil map at 1:50,000 scale. For each polygon the weighted average value of Ksat has been calculated on the basis of the percentage diffusion of the soils present in it.

  • Hydrologic Soil Group Map (1:50k) - 2014
    Google Earth web site | MinERva site | Data download WMS
    The map represents the distribution of Hydrologic Soil Groups (USDA-NRCS methodology, 2009.) Each plygon represents the main HSG.

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last modified 2023-11-17T14:31:45+01:00
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