Geology & soil science


Remote sensing and use of optical and radar satellite data is an essential part of the present-day geology. Soil science applications are closely related to our agricultural activities and projects.


Soil map reconstruction

There exist many original soil cartographic maps in paper version. The information collected in previous soil surveys still keep valuable information. Conversion of such a paper maps to GIS brings new possibilities of the usage.
The procedure of digital reconstruction of original cartographic maps includes steps like scanning, georeferencing, mosaicking, vectorisation and building thematic attribute database in GIS. Such procedures can easily be made in production lines to process large amounts of data.

Thematic services:
  • paper map scanning
  • georeferencing a reprojection of scanned maps
  • thematic maps digitizing


Soil mapping

There is an increasing demand of digital soil maps on different scales. The existing soil spatial databases are either not available or not exhaustive and precise enough for use within number of environmental applications. The reason for the lack of the spatial information is that convential soil survey methods are relatively slow and largely expensive.
Remote sensing data have an important advantage; the data provide spatially exhaustive sampling of the area of interest. Vegetation cover is, however, one of the application constraints in the soil science. Remotely sensed images (either multispectral or hyperspectral) can be used to map spatial patterns of bare soil. Spectral signatures provide indirect information on the top of bare soil layer. As an example, visible boundaries of soil types (groups of soil types) can be mapped.
Four main factors influence the soil reflectance in remote sensing images: mineral composition, soil moisture, organic matter content and soil texture (surface). Size and shape of the soil aggregate also influence the reflectance in the images. Soil moisture is often determined by radar technology. The soil moisture content generally refers to water content in the upper part (several centimetres) of the top soil. Radar backscatter response is affected by soil moisture, in addition to topography, surface roughness and vegetative cover. When the latter elements are static, multitemporal radar images can be used in determination of soil moisture. The radar is actually sensitive to the soil’s dielectric constant, a property that changes in response to the amount of water in the soil.
Remote sensing can also be used in mapping a number of environmental variables that are used in predictive soil mapping, e.g. vegetation/rock cover, landforms, surface materials, drainage, colour of topsoil, conditions of soil formation and other topographic data.

Thematic services:
  • map of top soil colour
  • map of soil type indicators
  • map of soil moisture
  • map of surface drainage
  • supplementary maps of environmental variables (organisms – vegetation, land cover, landforms, surface materials, etc.)


Soil erosion mapping

Mapping of soil erossion, ex post, is often done by remote sensing technology. Very high resolution images are a pre-requisite of such an application. Soil erosion intensity of different geomorphological locations in terrain can be also determined. This provides the basis of designing soil erosion control planning for different situations.

Thematic services:
  • map of soil eroded areas
  • map of soil erosion intensity
  • map of soil erosion risk areas


Soil water modelling

Modelling of water flow and pollutant transport is an important part of many applications, e.g. in water management, agricultural management, soil and ground water pollution. Maps of soil moisture spatial distribution together with time development is for example used to monitor limitations of crop growth. Remotely sensed images are often included to provide e.g. land cover maps for runoff predictions. Also top-soil moisture measurements can be assimilated in the simulation models.
Different approaches may be used for detail description of processes in small scale and short-term compare to description of processes in large scale and long term. Numerical simulation of the water regime is the major process simulation. Varying number of models with different complexity and degrees of simplifications may be used according to application requests. In general, there are two major approaches for water flow simulation. The simplest types of the soil water flow models are based on water storage routing. Such models act as tipping buckets. Examples are WOFOST and EPIC. Those models are usually used for particular problem solution like irrigation scheduling, prediction of crop production, climate modelling or eco-hydrological modelling in larger scale and longer term. The physically based approach uses the Richards’ equation that is based on the Darcy’s law and continuity equation. Those models are generally applicable and can be used for precise description of water regime in unsaturated and saturated soil profile and may be applied in fundamental research as well as in water management. Examples are HYDRUS-2D, HYDRUS-1D, and SWAP.

Thematic services:
  • map of soil moisture distribution
  • map of drought affected areas
  • water limited yield predictions


Relevant projects

Acronym Name / Duration Customer
PALORTHO Orthorectification of Palsar radar data
2008 - 2010 Aquatest (Czech Republic)
ASEMARS Actions in Support of the Enlargement of the MARS Crop Yield Forecasting System
2005 - 2008 Joint Research Centre (DG JRC) / Alterra (Netherlands)
GMES SAGE SAGE (Service for the Provision of Advanced Geoinformation on Environmental Pressure and State)
2005 - 2006 European Space Agency (ESA) / Infoterra Germany
ERDENET Land Cover/Use Changes in ERDENET (Mongolia)
2004 - 2005 GEOMIN (Czech Republic)
GeoBariéra Implementation of geological and geophysical surveys for assessment and scale down of study sites for next steps of DGR sitting
2003 - 2004 SÚRAO / Aquatest a.s. (Czech Republic)
ERSTEC Use of ERS interferometry for tectonic movement detection
2002 Czech Academy of Science
EUROSION EUROSION (LaCoast DB extension to candidate countires)
2002 DG Environment / IGN International (France)
CAMSAT Satellite image maps of Cameroon
2001 Czech Ministry of Environment / Geofyzika a.s. Brno (Czech Republic)
UAMAP ERS Radar Map of the Upper Austria
1997 - 1998 Loeben University (Austria)
BT GIS Black Triangle GIS
1995 - 1996 PHARE Regional Environmental Program
MERA Soil degradation MARS Environment Related Applications (MERA) - Soil degradation
1995 - 1996 PHARE, Czech Ministry of Environment
INGOMAP Radar image map for oil line planning
1995 Czech Geological Institute