A comparison tool for different vegetation indices from spaceborne imagery
Gülşah Özdemir, Emre Sümer
Abstract
Gülşah Özdemir, Emre Sümer
Abstract
In this study, we developed a tool in order to compare the performance of different vegetation indices. Among the tens of vegetation indices being developed, three broadband greenness vegetation indices; Normalized Vegetation Index (NDVI), Atmospherically Resistant Vegetation Index (ARVI) and Simple Ratio Index (SRI), were considered in this study. The comparison tool was developed in Matlab programming language, which is composed of three parts: (i) input, (ii) output and (iii) analysis. The vegetation indices were tested on three different scenes, which are selected on a residential area of the Batikent district of Ankara, Turkey. The data used includes the IKONOS pan-sharpened images acquired on August 4, 2002. The spatial resolution is 1-m and the data is composed of 4 spectral bands, which are blue, green, red and near infrared. A comparison between the selected vegetation indices was performed with respect to the obtained error performances.
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In this study, we developed a tool in order to compare the performance of different vegetation indices. Among the tens of vegetation indices being developed, three broadband greenness vegetation indices; Normalized Vegetation Index (NDVI), Atmospherically Resistant Vegetation Index (ARVI) and Simple Ratio Index (SRI), were considered in this study. The comparison tool was developed in Matlab programming language, which is composed of three parts: (i) input, (ii) output and (iii) analysis. The vegetation indices were tested on three different scenes, which are selected on a residential area of the Batikent district of Ankara, Turkey. The data used includes the IKONOS pan-sharpened images acquired on August 4, 2002. The spatial resolution is 1-m and the data is composed of 4 spectral bands, which are blue, green, red and near infrared. A comparison between the selected vegetation indices was performed with respect to the obtained error performances.
Key concepts: Vegetation (pathology), Normalized Difference Vegetation Index, Vegetation Index, Enhanced vegetation index, Remote sensing, Environmental science, Index (typography), Image resolution