CONFERENCE PROCEEDINGS
Advanced Search
Home > Journals > J. Appl. Rem. Sens. > Volume 9 > Issue 1 > Article
Open Access
16 June 2015 Review of the use of remote sensing for biomass estimation to support renewable energy generation
Lalit Kumar, Priyakant Sinha, Subhashni Taylor, Abdullah F. Alqurashi
Author Affiliations +
Journal of Applied Remote Sensing, Vol. 9, Issue 1, 097696 (June 2015). https://doi.org/10.1117/1.JRS.9.097696
Abstract
The quantification, mapping and monitoring of biomass are now central issues due to the importance of biomass as a renewable energy source in many countries of the world. The estimation of biomass is a challenging task, especially in areas with complex stands and varying environmental conditions, and requires accurate and consistent measurement methods. To efficiently and effectively use biomass as a renewable energy source, it is important to have detailed knowledge of its distribution, abundance, and quality. Remote sensing offers the technology to enable rapid assessment of biomass over large areas relatively quickly and at a low cost. This paper provides a comprehensive review of biomass assessment techniques using remote sensing in different environments and using different sensing techniques. It covers forests, savannah, and grasslands/rangelands, and for each of these environments, reviews key work that has been undertaken and compares the techniques that have been the most successful.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Citation Download Citation
Lalit Kumar, Priyakant Sinha, Subhashni Taylor, and Abdullah F. Alqurashi "Review of the use of remote sensing for biomass estimation to support renewable energy generation," Journal of Applied Remote Sensing 9(1), 097696 (16 June 2015). https://doi.org/10.1117/1.JRS.9.097696
Published: 16 June 2015
JOURNAL ARTICLE
 28 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Lens.org Logo
CITATIONS
Cited by 129 scholarly publications.
Advertisement
Advertisement
KEYWORDS
Biological research
Remote sensing
Vegetation
LIDAR
Data modeling
Ecosystems
Radar
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top