Douglas K. Bolton
University of British Columbia
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Publication
Featured researches published by Douglas K. Bolton.
Canadian Journal of Remote Sensing | 2013
Douglas K. Bolton; Michael A. Wulder
Carbon storage in forest aboveground biomass is a critical, yet difficult, component of the global carbon cycle to estimate. Canopy height, a key indicator of carbon storage, can be estimated from Light Detection and Ranging (Lidar) waveforms collected by the Geoscience Laser Altimeter System (GLAS) aboard the Ice, Cloud, and land Elevation Satellite (ICESat). Although globally distributed, GLAS does not provide spatially exhaustive coverage. Therefore, accurate methods of extrapolation are necessary to produce wall-to-wall global canopy height maps from these data. In this analysis, we compare two of these global GLAS-derived height products to canopy height estimates derived from 25000 km of discrete return airborne Lidar data over Canadas boreal forests. We selected the 95th percentile of first return height from airborne Lidar as a measure of canopy height to relate against estimates from the global GLAS-derived products. The agreement between the global GLAS-derived products and airborne Lidar-derived height estimates varied between the two products (average ecozone RMSE = 3.9 and 7.4 m), demonstrating that differences in data selection, processing, and extrapolation can influence height estimates derived from GLAS data. Where large differences existed between the global GLAS-derived products and the airborne Lidar-derived height estimates, the GLAS-derived products tended to predict taller canopies. Removing GLAS waveforms on steep terrain appeared to be a superior approach to reducing errors in height estimates, as the global GLAS-derived product that filtered these waveforms was in closer agreement with airborne Lidar-derived height estimates in regions of rough terrain (RMSE = 3.2–8.5 m compared with 8.1–13.8 m). Differences in the spatial resolution of canopy height estimates, coupled with varying definitions of canopy height within each product, should be considered when interpreting the results of this analysis. Investigating the relationship between small-footprint Lidar data and published canopy height products can identify the approaches that lead to the most accurate estimates of aboveground biomass and can help determine why discrepancies in height estimates exist between various model approaches, data and underlying environmental conditions.
PLOS ONE | 2018
Txomin Hermosilla; Michael A. Wulder; Joanne C. White; Douglas K. Bolton
Fire as a dominant disturbance has profound implications on the terrestrial carbon cycle. We present the first ever multi-decadal, spatially-explicit, 30 meter assessment of fire regimes across the forested ecoregions of Canada at an annual time-step. From 1985 to 2015, 51 Mha burned, impacting over 6.5% of forested ecosystems. Mean annual area burned was 1,651,818 ha and varied markedly (σ = 1,116,119), with 25% of the total area burned occurring in three years: 1989, 1995, and 2015. Boreal forest types contained 98% of the total area burned, with the conifer-dominated Boreal Shield containing one-third of all burned area. While results confirm no significant national trend in burned area for the period of 1985 to 2015, a significant national increasing trend (α = 0.05) of 11% per year was evident for the past decade (2006 to 2015). Regionally, a significant increasing trend in total burned area from 1985 to 2015 was observed in the Montane Cordillera (2.4% increase per year), while the Taiga Plains and Taiga Shield West displayed significant increasing trends from 2006 to 2015 (26.1% and 12.7% increases per year, respectively). The Atlantic Maritime, which had the lowest burned area of all ecozones (0.01% burned per year), was the only ecozone to display a significant negative trend (2.4% decrease per year) from 1985 to 2015. Given the century-long fire return intervals in many of these ecozones, and large annual variability in burned area, short-term trends need to be interpreted with caution. Additional interpretive cautions are related to year used for trend initiation and the nature and extents of spatial regionalizations used for summarizing findings. The results of our analysis provide a baseline for monitoring future national and regional trends in burned area and offer spatially and temporally detailed insights to inform science, policy, and management.
Ecography | 2018
Gregory J. M. Rickbeil; Douglas K. Bolton; Margaret E. Andrew; N.C. Brouwers
Determining drivers of species richness is recognised as highly complex, involving many synergies and interactions. We examine the utility of newly available remote sensing representations of vegetation productivity and vegetation structure to examine drivers of species richness at continental and regional scales. We related richness estimates derived from stacked species distribution models for birds, mammals, amphibians, and reptiles to estimates of actual and potential evapotranspiration (AET and PET), forest structure, and forest productivity across Australia as a whole as well as by bioclimatic zones. We used structural equation modeling to partition correlations between climate energy and vegetation attributes and their subsequent associations with species richness. Continentally, vertebrate richness patterns were strongly related to patterns of energy availability. Richness of amphibians, mammals, and birds were positively associated with AET. However, reptile richness was most strongly associated with PET. Regionally, forest structure and productivity associations with bird, mammal, and amphibian richness were strongest. Again, reptile richness associated most strongly with PET. Our results suggest that a hierarchy of drivers of broad‐scale vertebrate richness patterns exist (reptiles excluded): 1) climate energy is most important at the continental scale; next, 2) vegetation productivity and vegetation structure are most important at the regional scale; except 3) at low extremes of climate energy when energy becomes limiting.
Remote Sensing of Environment | 2015
Douglas K. Bolton; Michael A. Wulder
Environmental Monitoring and Assessment | 2013
Douglas K. Bolton; Michael A. Wulder
Remote Sensing of Environment | 2016
Wiebe Nijland; Douglas K. Bolton; Gordon Stenhouse
Journal of Biogeography | 2017
Douglas K. Bolton; Txomin Hermosilla; Michael A. Wulder; Joanne C. White
Diversity and Distributions | 2014
Gregory J. M. Rickbeil; Margaret E. Andrew; Douglas K. Bolton; Nancy A. Mahony; Trisalyn A. Nelson
Isprs Journal of Photogrammetry and Remote Sensing | 2018
Melissa Fedrigo; Glenn Newnham; Darius S. Culvenor; Douglas K. Bolton; Craig R. Nitschke
Forest Science | 2015
Yuhao Lu; Douglas K. Bolton; Tongli Wang; Guangyu Wang