The presentation demonstrates a technical case study of the image processing by ILWIS GIS. Study area is located in the southwestern, agricultural part of Hungary (Mecsek Hills foothill area). The landscapes of the Mecsek region represent a unique part of the Hungarian environment belonging to the Carpathian basin. However, changes in the land cover types were detected recently caused by various environmental reasons. Study aim was to compare changes in the land cover types and landscape dynamics. 3 Landsat TM images have a temporary gap of 14 years (1992-2006). The gap aimed to assess vegetation changes in the summer months (June). The study includes following methodological steps: 1) Data collection: 3 Landsat TM images; 2) Data import and conversion. 3) Data preprocessing: scenes of 1992, 1999 and 2006. 4) Making color composites from 3 Landsat TM spectral channels (multi-band layers). 5) Image segmentation and classification (clustering). 6) GIS mapping and spatial analysis. 7) Google Earth snapshot verification. 8) Results interpretation. Results analysis shown changes in the selected area detected by ILWIS GIS image classification.
Polina Lemenkova (2015). Mapping Agricultural Lands by Means of GIS for Monitoring Use of Natural Resources (a Case Study of Landscapes in the South-Western Hungary).
Mapping Agricultural Lands by Means of GIS for Monitoring Use of Natural Resources (a Case Study of Landscapes in the South-Western Hungary)
Polina Lemenkova
Primo
2015
Abstract
The presentation demonstrates a technical case study of the image processing by ILWIS GIS. Study area is located in the southwestern, agricultural part of Hungary (Mecsek Hills foothill area). The landscapes of the Mecsek region represent a unique part of the Hungarian environment belonging to the Carpathian basin. However, changes in the land cover types were detected recently caused by various environmental reasons. Study aim was to compare changes in the land cover types and landscape dynamics. 3 Landsat TM images have a temporary gap of 14 years (1992-2006). The gap aimed to assess vegetation changes in the summer months (June). The study includes following methodological steps: 1) Data collection: 3 Landsat TM images; 2) Data import and conversion. 3) Data preprocessing: scenes of 1992, 1999 and 2006. 4) Making color composites from 3 Landsat TM spectral channels (multi-band layers). 5) Image segmentation and classification (clustering). 6) GIS mapping and spatial analysis. 7) Google Earth snapshot verification. 8) Results interpretation. Results analysis shown changes in the selected area detected by ILWIS GIS image classification.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


