ASSESMENT OF THE TVI VEGETATION INDEX WITH THE AID OF PROBABILITY THEORY
In the present paper the statistical behaviour of the Transformed Vegetation Index TVI is studied. TVI is defined by: (equation No1) - or, alternatively, by: (equation No2) u is the numerical value of the vegetation index, χ and y are the brightness values of the near infrared and red zones, respectively. Relation (1) defines the vegetation index TVI. Relation (2) defines the vegetation index TVI'. Using appropriate distributions to describe the histograms of χ and y channels, and taking into account certain theorems from probability theory, the expressions for the distributions of TVI and TVI' values are deduced. According to these expressions, the standard deviation of TVI image is larger than that of TVI', as well as NDVI (Normalized Difference Vegetation Index). The prevailing value of the TVI' histogram is located at the right part of the tonality range. Therefore, according to the mathematical analysis, the TVI image has a better contrast than that of the NDVI and TVI' images. The TVI' has a diffuse luminance. The theoretical predictions were tested with a Landsat 7 ETM image of Zakynthos Island (western Greece) and they were found to be in accordance with the satellite data. It was also observed that lineaments with a dark tonality are expressed more clearly in the TVI image than in the TVI' image. The general conclusion is that the TVI vegetation index is preferable from TVI', since the former produces images with a larger standard deviation and a better contrast than the latter. The results and conclusions of this paper may be useful in geological and environmental research , for mapping regions with a different vegetation cover.
- How to Cite
Σκιάνης Γ. Α., Βαϊόπουλος Δ., & Νικολακόπουλος Κ. (2004). ASSESMENT OF THE TVI VEGETATION INDEX WITH THE AID OF PROBABILITY THEORY. Bulletin of the Geological Society of Greece, 36(3), 1338–1346. https://doi.org/10.12681/bgsg.16478
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors who publish with this journal agree to the following terms:
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution Non-Commercial License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g. post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal. Authors are permitted and encouraged to post their work online (preferably in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.