A Log-Ratio Vegetation Index (LRVI) for Discrimination and Classification of Remote Sensing Data
| Autor: | Francisco C. Rego, Irene S.P. Cadima, Eva K. Strand |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
010504 meteorology & atmospheric sciences
Electromagnetic spectrum Near-infrared spectroscopy 0211 other engineering and technologies Spectral space 02 engineering and technology 01 natural sciences Reflectivity Discriminant Environmental science Vegetation Index 021101 geological & geomatics engineering 0105 earth and related environmental sciences Log ratio Remote sensing |
| Zdroj: | Silva Lusitana. 28:45-70 |
| ISSN: | 0870-6352 |
| DOI: | 10.1051/silu/20202801045 |
| Popis: | Discrimination and classification are integral processes for interpreting remotely sensed data. Many spectral vegetation indices have been proposed for discriminating between vegetation, soil, and other ground cover categories. Classical remote sensing show that reflectance in the red (R) and near infrared (NIR) bands of the electromagnetic spectrum have been successful in differentiating between vegetation and other ground cover classes and they are commonly used for this purpose. Here we demonstrate how Fisher’s classical statistics can be applied to develop discriminant functions for commonly used vegetation indices simply using the R and NIR bands. We derive a new vegetation index, the Log-Ratio Vegetation Index (LRVI) and demonstrate its utility in discriminating between cork oak trees and surrounding background in woodlands in Portugal. The LRVI performed better than seven previously developed vegetation indices, likely because of its linear properties in the reflectance density spectral space. The robustness and simplicity of LRVI suggests that it deserves further exploration and should be included for comparison with other vegetation indices and functions in discrimination, classification, and modelling studies. We suggest that the demonstrated approach is widely applicable to development of indices composed of other bands than R and NIR for systems or processes that correlate better with reflectance in other regions of the electromagnetic spectrum. |
| Databáze: | OpenAIRE |
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