Next Article in Journal
Using Satellite Data to Represent Tropical Instability Waves (TIWs)-Induced Wind for Ocean Modeling: A Negative Feedback onto TIW Activity in the Pacific
Previous Article in Journal
Estimation of Herbaceous Fuel Moisture Content Using Vegetation Indices and Land Surface Temperature from MODIS Data
Remote Sens. 2013, 5(6), 2639-2659; doi:10.3390/rs5062639
Article

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

1,* , 2
, 2
, 3
, 1
, 4
 and 3
Received: 15 March 2013; in revised form: 10 May 2013 / Accepted: 15 May 2013 / Published: 24 May 2013
View Full-Text   |   Download PDF [1737 KB, uploaded 19 June 2014]   |   Browse Figures
Abstract: 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.
Keywords: leaf area index; hyperspectral; imaging spectrometer; radiative transfer; DART; LUT; inversion; discrete wavelet transform leaf area index; hyperspectral; imaging spectrometer; radiative transfer; DART; LUT; inversion; discrete wavelet transform
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Export to BibTeX |
EndNote


MDPI and ACS Style

Banskota, A.; Wynne, R.H.; Thomas, V.A.; Serbin, S.P.; Kayastha, N.; Gastellu-Etchegorry, J.P.; Townsend, P.A. Investigating the Utility of Wavelet Transforms for Inverting a 3-D Radiative Transfer Model Using Hyperspectral Data to Retrieve Forest LAI. Remote Sens. 2013, 5, 2639-2659.

AMA Style

Banskota A, Wynne RH, Thomas VA, Serbin SP, Kayastha N, Gastellu-Etchegorry JP, Townsend PA. Investigating the Utility of Wavelet Transforms for Inverting a 3-D Radiative Transfer Model Using Hyperspectral Data to Retrieve Forest LAI. Remote Sensing. 2013; 5(6):2639-2659.

Chicago/Turabian Style

Banskota, Asim; Wynne, Randolph H.; Thomas, Valerie A.; Serbin, Shawn P.; Kayastha, Nilam; Gastellu-Etchegorry, Jean P.; Townsend, Philip A. 2013. "Investigating the Utility of Wavelet Transforms for Inverting a 3-D Radiative Transfer Model Using Hyperspectral Data to Retrieve Forest LAI." Remote Sens. 5, no. 6: 2639-2659.


Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert