Investigating the Utility of Wavelet Transforms for Inverting a 3-D Radiative Transfer Model Using Hyperspectral Data to Retrieve Forest LAI

The need for an efficient and standard technique for optimal spectral sampling of hyperspectral data during the inversion of canopy reflectance models has been the subject of many studies. The objective of this study was to investigate the utility of the discrete wavelet transform (DWT) for extracti...

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Main Authors: Jean P. Gastellu-Etchegorry, Nilam Kayastha, Shawn P. Serbin, Valerie A. Thomas, Randolph H. Wynne, Asim Banskota, Philip A. Townsend
Format: Article
Language:English
Published: MDPI AG 2013-05-01
Series:Remote Sensing
Subjects:
Online Access:http://www.mdpi.com/2072-4292/5/6/2639
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author Jean P. Gastellu-Etchegorry
Nilam Kayastha
Shawn P. Serbin
Valerie A. Thomas
Randolph H. Wynne
Asim Banskota
Philip A. Townsend
author_facet Jean P. Gastellu-Etchegorry
Nilam Kayastha
Shawn P. Serbin
Valerie A. Thomas
Randolph H. Wynne
Asim Banskota
Philip A. Townsend
author_sort Jean P. Gastellu-Etchegorry
collection DOAJ
description The need for an efficient and standard technique for optimal spectral sampling of hyperspectral data during the inversion of canopy reflectance models has been the subject of many studies. The objective of this study was to investigate the utility of the discrete wavelet transform (DWT) for extracting useful features from hyperspectral data with which forest LAI can be estimated through inversion of a three dimensional radiative transfer model, the Discrete Anisotropy Radiative Transfer (DART) model. DART, coupled with the leaf optical properties model PROSPECT, was inverted with AVIRIS data using a look-up-table (LUT)-based inversion approach. We used AVIRIS data and in situ LAI measurements from two different hardwood forested sites in Wisconsin, USA. Prior to inversion, model-simulated and AVIRIS hyperspectral data were transformed into discrete wavelet coefficients using Haar wavelets. The LUT inversion was performed with three different datasets, the original reflectance bands, the full set of wavelet extracted features, and two wavelet subsets containing 99.99% and 99.0% of the cumulative energy of the original signal. The energy subset containing 99.99% of the cumulative signal energy provided better estimates of LAI (RMSE = 0.46, R2 = 0.77) than the original spectral bands (RMSE = 0.60, R2 = 0.47). The results indicate that the discrete wavelet transform can increase the accuracy of LAI estimates by improving the LUT-based inversion of DART (and, potentially, by implication, other terrestrial radiative transfer models) using hyperspectral data. The improvement in accuracy of LAI estimates is potentially due to different properties of wavelet analysis such as multi-scale representation, dimensionality reduction, and noise removal.
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spelling doaj.art-1227751b88bb42a9bc8ad7a26b7f24f12022-12-22T04:14:57ZengMDPI AGRemote Sensing2072-42922013-05-01562639265910.3390/rs5062639Investigating the Utility of Wavelet Transforms for Inverting a 3-D Radiative Transfer Model Using Hyperspectral Data to Retrieve Forest LAIJean P. Gastellu-EtchegorryNilam KayasthaShawn P. SerbinValerie A. ThomasRandolph H. WynneAsim BanskotaPhilip A. TownsendThe need for an efficient and standard technique for optimal spectral sampling of hyperspectral data during the inversion of canopy reflectance models has been the subject of many studies. The objective of this study was to investigate the utility of the discrete wavelet transform (DWT) for extracting useful features from hyperspectral data with which forest LAI can be estimated through inversion of a three dimensional radiative transfer model, the Discrete Anisotropy Radiative Transfer (DART) model. DART, coupled with the leaf optical properties model PROSPECT, was inverted with AVIRIS data using a look-up-table (LUT)-based inversion approach. We used AVIRIS data and in situ LAI measurements from two different hardwood forested sites in Wisconsin, USA. Prior to inversion, model-simulated and AVIRIS hyperspectral data were transformed into discrete wavelet coefficients using Haar wavelets. The LUT inversion was performed with three different datasets, the original reflectance bands, the full set of wavelet extracted features, and two wavelet subsets containing 99.99% and 99.0% of the cumulative energy of the original signal. The energy subset containing 99.99% of the cumulative signal energy provided better estimates of LAI (RMSE = 0.46, R2 = 0.77) than the original spectral bands (RMSE = 0.60, R2 = 0.47). The results indicate that the discrete wavelet transform can increase the accuracy of LAI estimates by improving the LUT-based inversion of DART (and, potentially, by implication, other terrestrial radiative transfer models) using hyperspectral data. The improvement in accuracy of LAI estimates is potentially due to different properties of wavelet analysis such as multi-scale representation, dimensionality reduction, and noise removal.http://www.mdpi.com/2072-4292/5/6/2639leaf area indexhyperspectralimaging spectrometerradiative transferDARTLUTinversiondiscrete wavelet transform
spellingShingle Jean P. Gastellu-Etchegorry
Nilam Kayastha
Shawn P. Serbin
Valerie A. Thomas
Randolph H. Wynne
Asim Banskota
Philip A. Townsend
Investigating the Utility of Wavelet Transforms for Inverting a 3-D Radiative Transfer Model Using Hyperspectral Data to Retrieve Forest LAI
Remote Sensing
leaf area index
hyperspectral
imaging spectrometer
radiative transfer
DART
LUT
inversion
discrete wavelet transform
title Investigating the Utility of Wavelet Transforms for Inverting a 3-D Radiative Transfer Model Using Hyperspectral Data to Retrieve Forest LAI
title_full Investigating the Utility of Wavelet Transforms for Inverting a 3-D Radiative Transfer Model Using Hyperspectral Data to Retrieve Forest LAI
title_fullStr Investigating the Utility of Wavelet Transforms for Inverting a 3-D Radiative Transfer Model Using Hyperspectral Data to Retrieve Forest LAI
title_full_unstemmed Investigating the Utility of Wavelet Transforms for Inverting a 3-D Radiative Transfer Model Using Hyperspectral Data to Retrieve Forest LAI
title_short Investigating the Utility of Wavelet Transforms for Inverting a 3-D Radiative Transfer Model Using Hyperspectral Data to Retrieve Forest LAI
title_sort investigating the utility of wavelet transforms for inverting a 3 d radiative transfer model using hyperspectral data to retrieve forest lai
topic leaf area index
hyperspectral
imaging spectrometer
radiative transfer
DART
LUT
inversion
discrete wavelet transform
url http://www.mdpi.com/2072-4292/5/6/2639
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