Spatial Analysis for Environmental Mapping of Šumava National Park

Polina Lemenkova (1)

1 OUC - Ocean University of China

The study area is Šumava National Park (ŠNP), the largest of the four national parks (68,064 hectares) located in the south-west of Czech Republic, on the border with Germany. Since 1990 it has been the protected Biospherical Reserve of UNESCO. Being a unique mosaic of natural and secondary habitats of exceptional natural value of European-wide significance, the components of the ŠNP represent is the largest terrestrial significant part of the Natura 2000 network in Czech Republic and Germany. For instance, the fauna species of ŠNP include protected important examples, such as e.g. lynx, otter and peregrine The research aim was to analyse how the ecosystem landscapes located within the study area changed since 1991 until 2009 (18-year time span) using remote sensing data and GIS. The data include GIS layers in two forms: raster layers as Landsat TM images with 18-years interval (1991 and 2009), and vector thematic layers in ArcGIS shape-file format. The data were stored in a GIS project. Technically, the GIS project were generated in Quantum GIS (QGIS) software. Methodologically, the applied workflow used in this research included following steps: 1) Data capture, unpacking and storage. 2) Organizing GIS project. 3) Geo- referencing and re-projection. 4) Activating GDAL and GRASS remote sensing plugins. 5) Preliminary data processing. 6) Generating contour layers from DEM. 7) Colour composition from 3 Landsat TM bands. 8) Defining Region of Interest: raster mosaicing and clipping. 9) False colour composites (bands 4-3-2). 10) Setting up parameters for classification. 11) Image classification using K-Means algorithm. 12) Pattern recognition. 13) Spatial analysis. The detailed illustrations of these steps are shown in the proposed presentation. The GIS analysis is used to test the importance of the natural and human-induced land used changes for survival of the important floristic locations in several case studies. Thus, landscape level predictors of commons (their location, size, borders) are evaluated using geospatial data: vector GIS layers and aerial images. The information received from these data includes digital model of the terrain (altitudes), vertical heterogeneity, slope, topographical related moisture index, heat load index and solar radiation index. The information on local geology and soil conditions (based on soil profiles), history of the colonization of the study area, and borders of land cadasters and private properties is taken from the auxiliary data. The land cover structure is calculated using Patch Analyst function embedded into the ArcGIS which is used to describe various aspects of landscape heterogeneity, habitat diversity and fragmentation. The outcomes are illustrated by two maps showing geographic distribution of land cover types within the study area in given time periods of 18-year time span. The results demonstrate visualization of the ecosystems in 1991 and 2009 showing dynamics of land cover types in the given time. The work demonstrated effective application of QGIS software combined with multi-source data (remote sensing and geoinformatics) for the purpose of environmental protection of precious areas of the Šumava National Park.

Mots clés: Spatial analysis; Remote sensing GIS; National Parks; GIS Data Modelling; GIS & Spatial Analyses; GIS Climat Environnement Société; GIS Geographic Information System; GIS MAPPING; GIS MODEL

Domaines: Sciences de la Terre; Géomorphologie; Sciences de l'environnement; Milieux et Changements globaux; Biodiversité et Ecologie; Environnement et Société; Planète et Univers [physics]; Géographie

Polina Lemenkova. Spatial Analysis for Environmental Mapping of Šumava National Park. 6th Annual PostGraduate Students (PGS) Conference, Charles University in Prague, Institute for Environmental Studies, Jan 2015, Prague, Czech Republic. ⟨10.6084/m9.figshare.7211843⟩. ⟨hal-02018179⟩