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Technical note A new technique for interpolating the reflectance red edge position

Terence P. Dawson, Paul J. Curran

Open publisher page 417 citations

Abstract

The point of maximum slope on the reflectance spectrum of vegetation between red and near-infrared wavelengths, termed the red edge position (REP), is correlated strongly with foliar chlorophyll content and provides a very sensitive indicator of, among other things, vegetation stress. The high spectral resolution of airborne imaging spectrometers now offers the potential for determining the REP of vegetation canopies at regional scales. However, the accurate estimation of the REP is dependent upon sensor band positions and widths. Various techniques have been developed to minimize the error in estimating the REP, such as linear interpolation or inverted Gaussian curve fitting in the region of the red edge which requires an a priori knowledge of the spectrum under investigation. This technical note presents a simple technique known as Lagrangian interpolation which is applied to the first-derivative transformation of the reflectance spectrum. The technique fits a second-order polynomial curve to three bands, which need not be equally spaced, centred around the maximum slope position. A second derivative is then performed on the Lagrangian equation to determine the maximum slope position.

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What this paper is about

The point of maximum slope on the reflectance spectrum of vegetation between red and near-infrared wavelengths, termed the red edge position (REP), is correlated strongly with foliar chlorophyll content and provides a very sensitive indicator of, among other things, vegetation stress. The high spectral resolution of airborne imaging spectrometers now offers the potential for determining the REP of vegetation canopies at regional scales. However, the accurate estimation of the REP is dependent upon sensor band positions and widths. Various techniques have been developed to minimize the error in estimating the REP, such as linear interpolation or inverted Gaussian curve fitting in the region of the red edge which requires an a priori knowledge of the spectrum under investigation. This technical note presents a simple technique known as Lagrangian interpolation which is applied to the first-derivative transformation of the reflectance spectrum. The technique fits a second-order polynomial curve to three bands, which need not be equally spaced, centred around the maximum slope position. A second derivative is then performed on the Lagrangian equation to determine the maximum slope position.

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Available abstract

The point of maximum slope on the reflectance spectrum of vegetation between red and near-infrared wavelengths, termed the red edge position (REP), is correlated strongly with foliar chlorophyll content and provides a very sensitive indicator of, among other things, vegetation stress. The high spectral resolution of airborne imaging spectrometers now offers the potential for determining the REP of vegetation canopies at regional scales. However, the accurate estimation of the REP is dependent upon sensor band positions and widths. Various techniques have been developed to minimize the error in estimating the REP, such as linear interpolation or inverted Gaussian curve fitting in the region of the red edge which requires an a priori knowledge of the spectrum under investigation. This technical note presents a simple technique known as Lagrangian interpolation which is applied to the first-derivative transformation of the reflectance spectrum. The technique fits a second-order polynomial curve to three bands, which need not be equally spaced, centred around the maximum slope position. A second derivative is then performed on the Lagrangian equation to determine the maximum slope position.

Key concepts: Red edge, Interpolation (computer graphics), Position (finance), Gaussian, Remote sensing, A priori and a posteriori, Linear interpolation, Vegetation (pathology)

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