Extracting and identifying vegetation from satellite images is a major topic in Remote Sensing and GIS. Several techniques have been developed by scientists worldwide. This study aims to evaluate the approaches to the extraction of vegetation from satellite images and to examine each approach within the GIS environment. Three different approaches were used: The first is Normalized Difference Vegetation Index (NDVI), the second is Supervised Classification and the third is Unsupervised Classification. These three methods were examined using two Landsat scenes for Dhofar Governorate which lies in the Southern part of Oman. The two Landsat scenes were acquired on 4th May 2001. The preliminary results show that there are variations in the total areas of vegetation between the three approaches. For example, the total vegetation area using NDVI approach is just above 900 Km2, but it increases to more than 1700 Km2 when using upervised classification, and then it increases again to more than 3300 Km2 when using the unsupervised classification approach.
|Published - 2011
|34th International Symposium on Remote Sensing of Environment - The GEOSS Era: Towards Operational Environmental Monitoring - Sydney, NSW, Australia
المدة: أبريل ١٠ ٢٠١١ → أبريل ١٥ ٢٠١١
|34th International Symposium on Remote Sensing of Environment - The GEOSS Era: Towards Operational Environmental Monitoring
|٤/١٠/١١ → ٤/١٥/١١
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