This study aims at identify vegetation using three approaches; Supervised, Unsupervised and Normalized Difference Vegetation Index methods of classification and also to examine and compare the final results to an image of higher resolution in other to determine which of the approaches best identifies vegetation. This study used Akinyele Local Government as a case study. These three methods were examined using one Landsat scene for Akinyele Local Government area Ibadan, Oyo state, Nigeria. The Landsat scene was acquired on 30th January, 2019. All operations involved in the three approaches were carried out using the ArcGIS 10.5 software and the results were also produced on the ArcGIS software. The results obtained shows that there are variations in the total vegetation areas covered when using the three approaches. The results from the three approaches were analyzed and compared to a standard image of higher resolution (Google Earth Image) in other to determine which method is best for identifying vegetation. Finally, from these observations, the Normalized Difference Vegetation Index result represents a compromise between the supervised and unsupervised results.
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In-Text Citation: (Kehinde et al., 2020)
To Cite this Article: Kehinde, A. G., Adediran, A. S., & Timilehin, F. (2020). Identification of Vegetation with Supervised, Unsupervised, Normalized Difference Vegetation Index Methods and Comparison with Standard Google Earth Image using Remote Sensing and Geographic Information System Techniques. International Journal of Academic Research in Enviornment & Geography, 7(1), 56–69.
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