The Department of GIS and Remote Sensing  deals with applications of Geographical Information Systems (GIS) and Remote sensing (RS) methods in vegetation ecology. Although formally established in June 2007, geoinformatic technologies have been employed at the Institute of Botany under the Department of Geobotany since 1998.

Microclimate measurements

The Department of GIS and RS focuses on application of spatio-temporal data, such as:

  1. Spatio-temporal changes in plant populations and communities and their spatial structure on different spatial scales using GIS, RS and spatially explicit models
  2. Detection of invasive species using remote sensing (including UAV)
  3. Plant spatial patterns and underlying biological processes
  4. Role of history in shaping temperate forests

    Hemispheric photo

    Hemispheric photo

RS data and field measurements are processed in a GIS environment and by spatially explicit modeling.

Besides its own research, the Department provides support for other research teams and projects of the Institute.


Microclimate station in extreme conditions

The Laboratory is equipped with complete software for vector and raster data processing and analyses (ArcGIS with selected extensions; PCI Geomatica 2012 with Orthoengine module; eCognition Developer 9.2, ENVI, Agisoft Photoscan), as well as with equipment for position measurements (GNSS Trimble PathFinder Pro XRS, Geoexplorer 2008 XH both with sub-meter accuracy and Geoexplorer GeoXH 6000 with decimeter accuracy; and field mapping tool FieldMap). We also have Spectral Evolution Full Range Portable Spectroradiometer for remote sensing purposes.


UAV use for monitoring of giant hogweed invasion

Research topics

  1. mapping both vegetation and particular species
  2. study of relationships between flora, vegetation and environmental factors
  3. analyses of spatial pattern and spatial relationships of studied objects
  4. analyses of spatio-temporal changes
  5. forest microclimate
  6. forest fires
  7. detection of invasive species using remote sensing

Forest microclimate modelling (combined image from thermal and visible spectra)


Departmental presentation from 2017 (PDF)