Cart (Loading....) | Create Account
Close category search window
 

Biomass Estimation of a Temperate Deciduous Forest Using Wavelet Analysis

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Ghasemi, N. ; Photogrammetry & Remote Sensing Dept., K.N. Toosi Univ. of Technol., Tehran, Iran ; Sahebi, M.R. ; Mohammadzadeh, A.

The increasing concentration of greenhouse gases in the atmosphere has been identified as contributing to the increase in global mean temperature. Carbon sequestration into trees and forests is an effective and inexpensive method for decreasing the CO2 level in the atmosphere. Hence, accurate measurements of biomass levels will be important to the global carbon cycle and climate change. This study used a wavelet-based forest aboveground biomass (AGB) estimation approach in a temperate deciduous forest. Two-dimensional discrete wavelet transformations was applied to ALOS AVNIR and PALSAR to obtain wavelet coefficients, which were correlated with AGB estimates using multiple linear regression analysis. Different wavelets were tested using this approach. Moreover, vegetation indices and texture parameters were calculated and correlated with AGB estimates. The results indicated that wavelet-based modeling could improve the accuracy of biomass estimation to 75% or even higher in comparison with the accuracy of 30%-40% resulting from past studies using vegetation indices and texture measures. This study demonstrates that wavelet-based biomass estimation could be a promising approach for solving the uncertainty between reflectance or backscatter values from satellite images and forest biomass and therefore provide better biomass estimations.

Published in:

Geoscience and Remote Sensing, IEEE Transactions on  (Volume:51 ,  Issue: 2 )

Date of Publication:

Feb. 2013

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.