Beaudoin, André: (Co-Investigator)
Naesset, Erik: Norwegian University of Life Sciences (Co-Investigator)
Ståhl, Göran: SLU (Co-Investigator)
Ung, Chhun-Huor: (Co-Investigator)
Project Funding:
2005 - 2007
NRA: 2004 NASA: Carbon Cycle Science
Funded by NASA
Abstract:
This proposal responds to the NASA Carbon Cycle Science call (NRA-04-OES-01) to reduce major uncertainties in the boreal forest carbon budget. Driving down these errors is critical to the North American Carbon Program. The overarching objective of the study is to develop a realistic estimate of the variability of regional carbon estimates developed using space-based lidar measurements of forest structure. Unlike the vast majority of remote sensing studies, this investigation will quantify major sources of variability in the regional C estimates, sources which are commonly ignored in most studies. To this end, three sub-objectives are identified. First, the investigators will develop the rigorous statistical and procedural framework to accurately estimate regional forest biomass and carbon estimates using an existing ground measurement network, an airborne lidar (PALS), and space lidar data (ICESat/GLAS). Second, this experimental design will be employed to develop forest biomass and carbon estimates for the entire province of Quebec. The selection of Quebec as the study area is based on five factors: (1) the expectation that, over the next century, the Province will undergo significant phyto-structural alteration as climate changes (2) the presence of multiple ecosystems, including a significant portion of the circumpolar boreal forest (3) the availability of ground plot information collected by the Quebec Ministry of Natural Resources, Parks and Wildlife (MNRQ, Ministère des Ressources Naturelles Quebec) (4) the availability of systematically-sampled GLAS data across the entire province and (5) the existence of complementary, boreal studies in Canada, Norway, Sweden, and Siberia. Third, C errors will be assessed to determine which phases of the multi-phase sampling procedure drive C variability. The following sources of variation are considered: – tree-level allometry, - plot-level sampling variability, - airborne lidar regression error and sampling variability, and - space-lidar regression error and sampling variation. The error analysis is key, for the results from this portion of the study will be used 1) to determine where efforts should be optimally allocated to minimize regional C-variability, and 2) to report those levels of C variability that, realistically, might be expected using airborne and space lidar as sampling tools. The study will employ a number of NASA assets to estimate aboveground forest carbon throughout all of Quebec. NASA data sets and instruments include standard MODIS land cover products, a Landsat-based land cover disturbance product, ICESat/GLAS data, airborne lidar data (PALS), and SRTM topographic data. GLAS is not an operational instrument and, in fact, may fail shortly. But the subcontinental C-measurement procedure developed and optimized in this study will be applicable in future studies which utilize airborne lidar profilers, scanners, and/or space lidars for natural resource assessment.
Publications:
Nelson, R., E. Næsset, T. Gobakken, G. Ståhl, and T. Gregoire. 2007. Regional Forest Inventory Using an Airborne Profiling LiDAR. Journal of Forest Planning 13: 287-294.
Gregoire, T.G., Q.-F. Lin, J. Boudreau, and R. Nelson. 2007. Regression estimation following the square root transformation of the response. Forest Science 54(6): 597-606.
BOUDREAU, J., NELSON, R., MARGOLIS, H., BEAUDOIN, A., GUINDON, L., KIMES, D. 2008. Regional aboveground forest biomass using airborne and spaceborne LiDAR in Quebec. Remote Sensing of Environment. 112(10), 3876-3890. DOI: 10.1016/j.rse.2008.06.003
Nelson, R., Boudreau, J., Gregoire, T. G., Margolis, H., Naesset, E., Gobakken, T., Stahl, G. 2009. Estimating Quebec provincial forest resources using ICESat/GLAS. Canadian Journal of Forest Research. 39(4), 862-881. DOI: 10.1139/X09-002
Nelson, R. 2010. Model effects on GLAS-based regional estimates of forest biomass and carbon. International Journal of Remote Sensing. 31(5), 1359-1372. DOI: 10.1080/01431160903380557
2008 NASA Carbon Cycle & Ecosystems Joint Science Workshop Posters
- GLAS-based Estimates of Biomass and Carbon in Siberia and Quebec
-- (Ross F. Nelson)
[abstract]
[poster]
More details may be found in the following project profile(s):
