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Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates
Joint Authors
Zhang, Maozhen
Chen, Qi
Batistella, Mateus
Moran, Emilio
Lu, Dengsheng
Vaglio Laurin, Gaia
Wang, Guangxing
Saah, David
Source
International Journal of Forestry Research
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-04-04
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Landsat Thematic mapper (TM) image has long been the dominate data source, and recently LiDAR has offered an important new structural data stream for forest biomass estimations.
On the other hand, forest biomass uncertainty analysis research has only recently obtained sufficient attention due to the difficulty in collecting reference data.
This paper provides a brief overview of current forest biomass estimation methods using both TM and LiDAR data.
A case study is then presented that demonstrates the forest biomass estimation methods and uncertainty analysis.
Results indicate that Landsat TM data can provide adequate biomass estimates for secondary succession but are not suitable for mature forest biomass estimates due to data saturation problems.
LiDAR can overcome TM’s shortcoming providing better biomass estimation performance but has not been extensively applied in practice due to data availability constraints.
The uncertainty analysis indicates that various sources affect the performance of forest biomass/carbon estimation.
With that said, the clear dominate sources of uncertainty are the variation of input sample plot data and data saturation problem related to optical sensors.
A possible solution to increasing the confidence in forest biomass estimates is to integrate the strengths of multisensor data.
American Psychological Association (APA)
Lu, Dengsheng& Chen, Qi& Wang, Guangxing& Moran, Emilio& Batistella, Mateus& Zhang, Maozhen…[et al.]. 2012. Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates. International Journal of Forestry Research،Vol. 2012, no. 2012, pp.1-16.
https://search.emarefa.net/detail/BIM-472157
Modern Language Association (MLA)
Lu, Dengsheng…[et al.]. Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates. International Journal of Forestry Research No. 2012 (2012), pp.1-16.
https://search.emarefa.net/detail/BIM-472157
American Medical Association (AMA)
Lu, Dengsheng& Chen, Qi& Wang, Guangxing& Moran, Emilio& Batistella, Mateus& Zhang, Maozhen…[et al.]. Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates. International Journal of Forestry Research. 2012. Vol. 2012, no. 2012, pp.1-16.
https://search.emarefa.net/detail/BIM-472157
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-472157