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Combining Satellite Lidar, Airborne Lidar and Ground Plots to Estimate the Amount and Distribution of Aboveground Biomass In Page 1 of 59 Combining Satellite Lidar, Airborne Lidar and Ground Plots to Estimate the Amount and Distribution of Aboveground Biomass in the Boreal Forest of North America Hank A. Margolis 1,2 , Ross F. Nelson 2, Paul M. Montesano 2,3 , André Beaudoin 4, Guoqing Sun 2,5 , Hans-Erik Andersen 6, Michael A. Wulder 7 1. Centre d’étude de la forêt; Faculté de foresterie, de géographie et de géomatique; Université Laval; Québec City, QC, G1V 0A6, Canada. Email: [email protected] ; Tel: (418) 656-7120. Corresponding Author 2. Biospheric Sciences Laboratory; NASA Goddard Space Flight Center; Greenbelt, MD, 20771, USA. Email: [email protected] , 3. Science Systems and Applications Inc., NASA Goddard Space Flight Center, Greenbelt, MD 20771 USA. Email: [email protected] 4. Laurentian Forestry Centre; Canadian Forest Service; Natural Resources Canada; 1055 rue du PEPS; Quebec City, QC, G1V 4C7, Canada. E-mail: [email protected] 5. University of Maryland; Department of Geographical Sciences; College Park, MD 20742, USA. Email: [email protected] 4. USDA Forest Service; Pacific Northwest Research Station; P.O. Box 352100; Seattle, WA 98195-2100, USA. Email: [email protected] 5. Pacific Forestry Centre; Canadian Forest Service; Natural Resources Canada; 506 West Burnside Road; Victoria, BC, V8Z 1M5, Canada. Email: [email protected] Can. J. For. Res. Downloaded from www.nrcresearchpress.com by University of St. Andrews - Library on 04/24/15 Revised Version: Submitted to the Canadian Journal of Forest Research For personal use only. This Just-IN manuscript is the accepted prior to copy editing and page composition. It may differ from final official version of record. 1 Page 2 of 59 1 ABSTRACT 2 We report estimates of the amount, distribution, and uncertainty of aboveground biomass 3 (AGB) of the different ecozones and forest land cover classes within the North American boreal 4 forest; analyze the factors driving the error estimates; and compare our estimates to other 5 reported values. A three-phase sampling strategy was used (1) to tie ground plot AGB to 6 airborne profiling lidar metrics, (2) to link the airborne estimates of AGB to ICESat-GLAS lidar 7 measurements such that (3) GLAS could be used as a regional sampling tool. We estimated the 8 AGB of the North American boreal forest at 21.8 Pg with relative error of 1.9% based on 256 9 GLAS orbits (229 086 pulses). The distribution of AGB was 46.6% for Western Canada, 43.7% for 10 Eastern Canada, and 9.7% for Alaska. With a single exception, relative errors were under 4% for 11 the three regions and for the major cover types and under 10% at the ecozone level. 12 The uncertainties of the estimates were calculated using a variance estimator that 13 accounted for only sampling error, i.e., the variability among GLAS orbital estimates, and 14 airborne to spaceborne regression error, i.e., the uncertainty of the model coefficients. Work is 15 on-going to develop robust statistical techniques for integrating other sources of error such as 16 ground to air regression error and allometric error. Small ecozones with limited east-west 17 extents tended to have fewer GLAS orbits and a greater percent sampling error. AGB densities 18 derived from GLAS agreed closely with the estimates derived from both forest inventories 19 (<17%) and a MODIS-based interpolation technique (<26%) for more southern, well-inventoried Can. J. For. Res. Downloaded from www.nrcresearchpress.com by University of St. Andrews - Library on 04/24/15 20 ecozones, whereas differences were much greater for unmanaged northern and/or 21 mountainous ecozones. 22 KEY WORDS : Aboveground biomass, lidar, North American boreal forest, ICESat-GLAS, Landsat, 23 MODIS, forest inventory, kNN. For personal use only. This Just-IN manuscript is the accepted prior to copy editing and page composition. It may differ from final official version of record. 2 Page 3 of 59 24 25 INTRODUCTION 26 Extending east to west across the entire continent, the North American boreal forest 27 encompasses ~3.7 million km 2 of which ~58% is classified as forest and other wooded land 28 (Brandt 2009). The North American boreal forest provides ecosystem services at local, regional, 29 and global scales including the storage of large amounts of carbon in living biomass and soils 30 (Kurz et al. 2013). However, this carbon is vulnerable to climate change and the amounts 31 sequestered vary in response to changes in forest fires (Amiro et al. 2009) and insect epidemics 32 (Kurz et al. 2008). Both on-going and projected increases in temperature have been reported, 33 with mean annual temperatures across the Canadian boreal zone expected to increase 4 to 5° C 34 by 2100 (Price et al. 2013). Climate change has the potential to create positive feedbacks 35 through which decreases in forest carbon sequestration lead to increased atmospheric CO 2 36 concentrations further exacerbating climate warming (Soja et al. 2007). More frequent and 37 larger wildfires, increased insect infestations, and changing vegetation structure due to melting 38 permafrost are likely consequences of increased temperatures in the boreal forest region (Price 39 et al. 2013). Therefore, it is useful to examine different approaches for monitoring boreal 40 carbon and to explore the development of new monitoring capabilities (Wulder et al. 2013a). 41 The primary operational approach for assessing large-scale forest biomass and carbon 42 stocks in the boreal forest of North America involves combining forest inventory ground plots Can. J. For. Res. Downloaded from www.nrcresearchpress.com by University of St. Andrews - Library on 04/24/15 43 with growth and yield curves for different land cover types and disturbance frequencies (Stinson 44 et al. 2011). Laser-ranging airborne lidar has the potential to provide supplemental information 45 on aboveground biomass (AGB) density of forests and has been used increasingly as a sampling For personal use only. This Just-IN manuscript is the accepted prior to copy editing and page composition. It may differ from final official version of record. 3 Page 4 of 59 46 tool at local to regional scales (Wulder et al. 2012a,b). This airborne technology is particularly 47 useful in extending AGB measurements into areas where few, if any, ground plots exist, e.g., 48 unmanaged forest regions. 49 Airborne lidars provide direct measurements of distances between the aircraft and 50 various ground targets. Data processing algorithms calculate both the distance to the ground 51 and the height above the ground of different components of the forest. From these 52 measurements, a number of lidar metrics related to forest height and canopy structure can be 53 derived which can then be converted into AGB (Nelson et al. 1988). Both profiling and scanning 54 lidars have been used as sampling tools (e.g., Nelson et al. 2012, Gobakken et al. 2012) and 55 various statistical approaches have been developed to estimate both AGB and carbon stocks as 56 well as their statistical uncertainties (Gregoire et al. 2012, Ståhl et al. 2011). For example, in 57 lidar-assisted model-based sampling, ground plots representative of the entire area of interest 58 are selected. Models are constructed which predict ground-measured biomass as a function of 59 lidar height and canopy density metrics and then these models are applied to the entire area 60 (Nelson et al. 2012). The error calculations account for the non-random, spatially dependent 61 transect data obtained by the lidar (Ene et al. 2013) which is accomplished partially by using the 62 transect as the sampling unit. 63 Reliable measurements of forest AGB from a space-based lidar would be useful because 64 such an instrument could provide repeated global-scale sampling of variables related to forest Can. J. For. Res. Downloaded from www.nrcresearchpress.com by University of St. Andrews - Library on 04/24/15 65 height from which regional and global biomass could be derived. The first opportunity to 66 explore the utility of a global sample of satellite-based lidar measurements occurred in 2003 67 when ICESat-1 (Ice Cloud and land Elevation SATellite) was launched with the Geosciences Lidar For personal use only. This Just-IN manuscript is the accepted prior to copy editing and page composition. It may differ from final official version of record. 4 Page 5 of 59 68 Altimetry System (GLAS) aboard. Using the GLAS waveform lidar, the ICESat mission’s main 69 objective was to measure changes in the mass balance of the polar ice sheets, and it collected 70 ice elevation data from 2003 to 2009. However, GLAS also offered the scientific community the 71 possibility of estimating forest height and AGB, although the sensor was not explicitly designed 72 for this objective. Global tree height maps have been developed (Simard et al. 2011) and Bolton 73 et al. (2013) compared this information to tree height data in Canada and found that discarding 74 GLAS waveforms from steep terrain reduced errors in height estimates. 75 Boudreau et al. (2008) and Nelson et al. (2009a) applied a sampling approach for 1.3 76 million km 2 of forest in the province of Québec that involved three different sampling phases, 77 i.e., ground, airborne, and satellite. The basic approach involved (1) building an initial statistical 78 model to link PALS height measurements to ground plot biomass, (2) building a second model to 79 relate the estimated biomass from the airborne lidar to the height metrics obtained by GLAS for 80 the 1,325 GLAS pulses that were flown by the aircraft, and (3) use the GLAS height metrics, 81 slope, and land cover for the ~104,000 quality-filtered GLAS pulses available across the province 82 of Quebec to calculate the AGB and carbon stocks for the province by land cover type.
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