Analysis of coarse resolution (∼1 km) satellite imagery has provided evidence of vegetation changes in arctic regions since the mid-1980s that may be attributable to climate warming. Here we investigate finer-scale changes to northern vegetation over the same period using stacks of 30 m resolution Landsat TM and ETM+ satellite images. Linear trends in the normalized difference vegetation index (NDVI) and tasseled cap indices are derived for four widely spaced national parks in northern Canada. The trends are related to predicted changes in fractional shrub and other vegetation covers using regression tree classifiers trained with plot measurements and high resolution imagery. We find a consistent pattern of greening (6.1-25.5% of areas increasing) and predicted increases in vascular vegetation in all four parks that is associated with positive temperature trends. Coarse resolution (3 km) NDVI trends were not detected in two of the parks that had less intense greening. A range of independent studies and observations corroborate many of the major changes observed.
Remote sensing has provided evidence of vegetation changes in Arctic tundra that may be attributable to recent climate warming. These changes are evident from local scales as expanding shrub cover observed in aerial photos, to continental scales as greening trends based on satellite vegetation indices. One challenge in applying conventional two date, satellite change detection in tundra environments is the short growing season observation window, combined with high inter-annual variability in vegetation conditions. We present an alternative approach for investigating tundra vegetation and surface cover changes based on trend analysis of long-term (1985-present) Landsat TM/ETM+ image stacks. The Tasseled Cap brightness, greenness, and wetness indices, representing linear transformations of the optical channels, are analysed for per-pixel trends using robust linear regression. The index trends are then related to changes in fractional shrub and other vegetation covers using a regression tree classifier trained with high resolution land cover. Fractional trends can be summarised by vegetation or ecosystem type to reveal any consistent patterns. Example results are shown for a 3 000 km 2 study area in northern Yukon, Canada where index and fractional changes are related to growth of vascular plants and coastal erosion.
During the past decade, significant research has been carried out on the strengthening of reinforced concrete (RC) slabs, beams, and columns using externally bonded carbon fibre reinforced polymer (CFRP) sheets. Steel reinforced polymer (SRP) sheets have recently been proposed as an alternative to CFRP to strengthen reinforced concrete beams. This paper reports experimental and numerical results of RC beams and beam-columns transversely wrapped with SRP and tested under blast load. A total of 10 scaled RC members were tested at a variety of blast wave intensities. Detailed observations are reported and validated against numerical models created in AUTODYN for the unstrengthened RC members. The SRP wraps were resilient in the near-field blast range and enhanced the ductility of the concrete likely through enhanced confinement. Member capacity could be increased by the wraps in failure modes dominated by concrete crushing. AUTODYN appears able to reasonably predict the behaviour of the RC members when loaded by blast.
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