The EURECA telecommanding chain: Experience with packet telecommand and telemetry systems

The European Retrieval Carrier (EURECA) was launched on its first flight on the 31st July 1992 by the Space Shuttle Atlantis. EURECA is characterized by several new on-board features, most notable Packet Telemetry and a partial implementation of Packet Telecommanding using an early version of the Command Operation Procedure (COP-1) protocol. EURECA has also very low contact time with its Ground Station, with a consequent high number of out-of-visibility onboard operations. This paper concentrates on the implementation and operational experience with the COP-1 Protocol and the effect the short ground contact time has on the design of the Commanding System. Another interesting feature is that the COP-1 is implemented at the control center rather than at the ground station. The COP-1 protocol also successfully supported the mission during the launch where commands were sent via NASCOM and the Shuttle

Using digital time-lapse cameras to monitor species-specific understorey and overstorey phenology in support of wildlife habitat assessment

Critical to habitat management is the understanding of not only the location of animal food resources, but also the timing of their availability. Grizzly bear (Ursus arctos) diets, for example, shift seasonally as different vegetation species enter key phenological phases. In this paper, we describe the use of a network of seven ground-based digital camera systems to monitor understorey and overstorey vegetation within species-specific regions of interest. Established across an elevation gradient in western Alberta, Canada, the cameras collected true-colour (RGB) images daily from 13 April 2009 to 27 October 2009. Fourth-order polynomials were fit to an RGB-derived index, which was then compared to field-based observations of phenological phases. Using linear regression to statistically relate the camera and field data, results indicated that 61% (r 2?= 0.61, df = 1, F?= 14.3, p?= 0.0043) of the variance observed in the field phenological phase data is captured by the cameras for the start of the growing season and 72% (r 2?= 0.72, df = 1, F?= 23.09, p?= 0.0009) of the variance in length of growing season. Based on the linear regression models, the mean absolute differences in residuals between predicted and observed start of growing season and length of growing season were 4 and 6 days, respectively. This work extends upon previous research by demonstrating that specific understorey and overstorey species can be targeted for phenological monitoring in a forested environment, using readily available digital camera technology and RGB-based vegetation indices

Lidar sampling for large-area forest characterization: A review

The ability to use digital remotely sensed data for forest inventory is often limited by the nature of the measures, which, with the exception of multi-angular or stereo observations, are largely insensitive to vertically distributed attributes. As a result, empirical estimates are typically made to characterize attributes such as height, volume, or biomass, with known asymptotic relationships as signal saturation occurs. Lidar (light detection and ranging) has emerged as a robust means to collect and subsequently characterize vertically distributed attributes. Lidar has been established as an appropriate data source for forest inventory purposes; however, large area monitoring and mapping activities with lidar remain challenging due to the logistics, costs, and data volumes involved.The use of lidar as a sampling tool for large-area estimation may mitigate some or all of these problems. A number of factors drive, and are common to, the use of airborne profiling, airborne scanning, and spaceborne lidar systems as sampling tools for measuring and monitoring forest resources across areas that range in size from tens of thousands to millions of square kilometers. In this communication, we present the case for lidar sampling as a means to enable timely and robust large-area characterizations. We briefly outline the nature of different lidar systems and data, followed by the theoretical and statistical underpinnings for lidar sampling. Current applications are presented and the future potential of using lidar in an integrated sampling framework for large area ecosystem characterization and monitoring is presented. We also include recommendations regarding statistics, lidar sampling schemes, applications (including data integration and stratification), and subsequent information generation. © 2012

Global wealth disparities drive adherence to COVID-safe pathways in head and neck cancer surgery

Peer reviewe

Digital Terrestrial Photogrammetry to Enhance Field-Based Forest Inventory across Stand Conditions

Forest inventories in uncertain future economic and environmental conditions require the development of cost-effective measurement techniques to provide robust and accurate information on forests across regional and global scales. Digital terrestrial photogrammetry (DTP) can be used to detect and measure trees on sample plots. In this study, a method was developed which used spherical images taken strategically within plots, and under varying acquisition conditions, to derive forest inventory attributes. Using a set of 102 photos on 400 m2 circular plots achieved a mean detection rate of 72.3% and estimated diameter to an RMSE of 19.0%. This study also explored the sensitivity of detection and estimation accuracy to different field and acquisition conditions. Detection of individual trees was significantly influenced by the tree size and species (p < 0.05 in a regression analysis), while plot-level detection was influenced by size and stem density. Tree size and the distance to the camera significantly influenced the accuracy of estimated attributes. These results are comparable to those of other DTP and terrestrial laser scanning studies in similar forest types while using fewer photos and less time, demonstrating the value of cost-effective methods for DTP estimation of forest attributes