Clustering Algorithm in ILWIS GIS for Classification of Landsat TM Scenes (Mecsek Hills Region, Hungary)

Current research has been performed at Eötvös Loránd University (Hungary, Budapest), Institute of Cartography. It focuses on the land cover change analysis using Landsat TM images and ILWIS GIS.

• Research Emphasis: application of clustering spatial analysis of the open source ILWIS GIS.
• Research Aim: agricultural mapping of land cover types: south-west Hungary, Mecsek Hills.
• Research Process: Landsat TM scenes were classified into different land use types: natural vegetation coverage, anthropogenic areas and agricultural fields, subdivided to various crop types.
• Research Output: three independent agricultural thematic maps of land cover types for years 1992, 1999 and 2006, created in ILWIS GIS.

The research methodology is based on cluster classification algorithm available in ILWIS GIS. The work is organized in several research steps summarized in the research workflow: The research area was classified into a set of land cover categories, labeled to following land units: 1) winter wheat 2) spring barley, 3) maize 4) sugar beet 5) maize for ensilage 6) oak and beech forests 7) potato 8) other crops 9) shrubland 10) water 11) not agricult. areas 12) grassland 13) other land cover types Field crops (e.g. maize, winter wheat) were detected on the images. The species with unclear nature of crop or not easily recognized were defined as ’other crops’. A Google Earth aerial imagery was used for visual control inspection. Once all clusters are grouped, the layout was created using representation palette defined in the domain ’Land Cover Types. The research results in 3 maps of land cover types for 1992, 1999 and 2006. Clustering method can be applied for other agri- cultural areas, since it enables objective classification in regions with high land heterogeneity and complex landscape structure. The research method is based on the cluster classification of Landsat scenes in ILWIS GIS.

The results show classified satellite images showing land cover types for the years 1992, 1999 and 2006, respectively.