Skip to Main Content
Evaluating the remote sensing and inventory-based estimation of biomass in the western CarpathiansAuthor(s): Magdalena Main-Knorn; Gretchen G. Moisen; Sean P. Healey; William S. Keeton; Elizabeth A. Freeman; Patrick Hostert
Source: Remote Sensing. 3: 1427-1446.
Publication Series: Miscellaneous Publication
PDF: Download Publication (1004.82 KB)
DescriptionUnderstanding the potential of forest ecosystems as global carbon sinks requires a thorough knowledge of forest carbon dynamics, including both sequestration and fluxes among multiple pools. The accurate quantification of biomass is important to better understand forest productivity and carbon cycling dynamics. Stand-based inventories (SBIs) are widely used for quantifying forest characteristics and for estimating biomass, but information may quickly become outdated in dynamic forest environments. Satellite remote sensing may provide a supplement or substitute. We tested the accuracy of aboveground biomass estimates modeled from a combination of Landsat Thematic Mapper (TM) imagery and topographic data, as well as SBI-derived variables in a Picea abies forest in the Western Carpathian Mountains. We employed Random Forests for non-parametric, regression tree-based modeling. Results indicated a difference in the importance of SBI-based and remote sensing-based predictors when estimating aboveground biomass. The most accurate models for biomass prediction ranged from a correlation coefficient of 0.52 for the TM- and topography-based model, to 0.98 for the inventory-based model. While Landsat-based biomass estimates were measurably less accurate than those derived from SBI, adding tree height or stand-volume as a field-based predictor to TM and topography-based models increased performance to 0.36 and 0.86, respectively. Our results illustrate the potential of spectral data to reveal spatial details in stand structure and ecological complexity.
- You may send email to email@example.com to request a hard copy of this publication.
- (Please specify exactly which publication you are requesting and your mailing address.)
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationMain-Knorn, Magdalena; Moisen, Gretchen G.; Healey, Sean P.; Keeton, William S.; Freeman, Elizabeth A.; Hostert, Patrick. 2011. Evaluating the remote sensing and inventory-based estimation of biomass in the western Carpathians. Remote Sensing. 3: 1427-1446.
Keywordsaboveground biomass, forest carbon, Random Forests, forest inventory, Picea abies, Carpathian Mountains, Landsat
- Using landsat time-series and lidar to inform aboveground carbon baseline estimation in Minnesota
- Combining LIDAR estimates of aboveground biomass and Landsat estimates of stand age for spatially extensive validation of modeled forest productivity.
- Airborne lidar-based estimates of tropical forest structure in complex terrain: opportunities and trade-offs for REDD+
XML: View XML