NDLI: Impact of spectrally dependent gain errors in hyperspectral data on the determination of chlorophyll concentrations in vegetation

Content Provider	IEEE Xplore Digital Library
Author	Soffer, R.J. Neville, R.A. Staenz, K. White, H.P.
Copyright Year	2007
Description	Author affiliation: Canada Centre for Remote Sensing, Ottawa (Soffer, R.J.; Neville, R.A.; Staenz, K.; White, H.P.)
Abstract	In support of Phase A work on the proposed Hyperspectral Environment and Resource Observer (HERO) mission, the sensitivity of chlorophyll concentrations derived from vegetation red-edge analysis to a spectrally dependent error in the radiometric calibration of the hyperspectral data is investigated. A typical ground-based reflectance spectrum taken from a boreal forest Aspen leaf is converted to top-of-atmosphere (TOA) radiance using the MODTRAN atmospheric correction model as implemented in the Imaging Spectrometer Data Analysis System (ISDAS). The resulting spectrum is then subjected to a randomly generated Spectral Gain Error (SGE). This process is repeated a statistically significant number of times to produce a simulated data set. By varying the magnitude of the SGE, several simulated data sets are produced representing different levels of relative calibration accuracies in the spectral domain. The simulated TOA data sets are then converted back to ground-based reflectance, once again using MODTRAN. For each pixel in the resulting data sets, red-edge parameters are determine using an Inverted Gaussian (IG) technique (red-edge inflection point - $lambda_{p},$ reflectance minimum - $lambda_{o},$ and sigma = $lambda_{p}-lambda_{o})$ as well as a couple of commonly applied Vegetation Indices $(R_{740}/R_{720}$ and $R_{710}/R_{760})-$ Each of these parameters results in a distribution of results, the width of which is dependent on the magnitude of the SGE applied to the data set providing the relationship between the parameters and the SGE. In order to tie these results to chlorophyll concentration levels, the PROSPECT Vegetation Model is used to invert the original spectrum. The sensitivity of each of the indices to the chlorophyll concentration is determined by varying its value in the PROSPECT model while holding the other three model parameters constant. Using these relationships, the sensitivity of the chlorophyll concentrations to the SGE is determined. A specification of the acceptable error in the chlorophyll concentration levels would then dictate the required level of accuracy in the spectral gain calibration. The relationship between the SGE and the chlorophyll concentration retrieval based upon any of the five investigated red-edge parameters is shown to be directly proportional.
Starting Page	3233
Ending Page	3236
File Size	1481116
Page Count	4
File Format	PDF
ISBN	9781424412112
DOI	10.1109/IGARSS.2007.4423533
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-07-23
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hyperspectral imaging Hyperspectral sensors Vegetation mapping Calibration Reflectivity Analytical models Remote sensing Atmospheric modeling Spectroscopy Data analysis Chlorophyll Concentration. HERO Hyperspectral Spectroradiometric Calibration Simulation Red-edge Analysis
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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