SUMMARY
We consider the viscoelastic rheology of the solid Earth under the Antarctic Peninsula due to ice mass loss that commenced after the breakup of the Larsen-B ice shelf. We extend the previous analysis of nearby continuous GPS time-series to include five additional years and the additional consideration of the horizontal components of deformation. They show strong uplift from ∼2002 to 2011 followed by reduced uplift rates to 2018. Modelling the GPS-derived uplift as a viscoelastic response to ongoing regional ice unloading from a new ice model confirms earlier estimates of low upper-mantle viscosities of ∼0.3–3 × 1018 Pa s in this region but allows a wide range of elastic lithosphere thickness. The observed and modelled north coordinate component shows little nonlinear variation due to the location of ice mass change to the east of the GPS sites. However, comparison of the observed and modelled east coordinate component constrains the upper-mantle viscosity to be less than ∼9 × 1018 Pa s, consistent with the viscosity range suggested by the uplift rates alone and providing important, largely independent, confirmation of that result. Our horizontal analysis showed only marginal sensitivity to modelled lithospheric thickness. The results for the horizontal components are sensitive to the adopted plate rotation model, with the estimate based on ITRF2014 suggesting that the sum of residual plate motion and pre-2002 glacial isostatic adjustment is likely less than ∼±0.5 mm yr−1 in the east component.
ABSTRACT:Airborne LiDAR data has become an important tool for both the scientific and industry based investigation of forest structure. The uses of discrete return observations have now reached a maturity level such that the operational use of this data is becoming increasingly common. However, due to the cost of data collection, temporal studies into forest change are often not feasible or completed at infrequent and at uneven intervals. To achieve high resolution temporal LiDAR surveys, this study has developed a micro-Unmanned Aerial Vehicle (UAV) equipped with a discrete return 4-layer LiDAR device and miniaturised positioning sensors. This UAV has been designed to be low-cost and to achieve maximum flying time. In order to achieve these objectives and overcome the accuracy restrictions presented by miniaturised sensors a novel processing strategy based on a Kalman smoother algorithm has been developed. This strategy includes the use of the structure from motion algorithm in estimating camera orientation, which is then used to restrain IMU drift. The feasibility of such a platform for monitoring forest change is shown by demonstrating that the pointing accuracy of this UAV LiDAR device is within the accuracy requirements set out by the Australian Intergovernmental Committee on Surveying and Mapping (ICSM) standards.
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