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Comparison of estimators of variance for forest inventories with systematic sampling-results from artificial populations

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Forest Ecosystems 2020年第2期7卷 215-233页

作者： Steen Magnussen Ronald EMcRoberts Johannes Breidenbach Thomas Nord-Larsen Göran Ståhl Lutz Fehrmann Sebastian Schnell 506 West Burnside Road VictoriaBC V8Z 1M5Canada raspberry ridge analytics 15111 Elmcrest Avenue NorthHugoMN 55038USA Norwegian Institute of Bioeconomy Research Høgskolevegen 81431ÅsNorway Department of Geosciences and Natural Resource Management University of CopenhagenRolighedsvej 23DK-1958 Frederiksberg CDenmark Department of Forest Resource Management Swedish University of Agricultural SciencesUmeåSweden Forest Inventory and Remote Sensing Faculty of Forest SciencesUniversity of GöttingenBüsgenweg 5D37077GöttingenGermany Alfred-Möller-Straße 1 Haus 41-4216225 EberswaldeGermany.

Background:Large area forest inventories often use regular grids(with a single random start)of sample locations to ensure a uniform sampling intensity across the space of the surveyed populations.A design-unbiased estimator of variance does not exist for this ***,a quasi-default estimator applicable to simple random sampling(SRS)is used,even if it carries with it the likely risk of overestimating the variance by a practically important *** better exploit the precision of systematic sampling we assess the performance of five estimators of variance,including the quasi *** this study,simulated systematic sampling was applied to artificial populations with contrasting covariance structures and with or without linear *** compared the results obtained with the SRS,Matern’s,successive difference replication,Ripley’s,and D’Orazio’s variance ***:The variances obtained with the four alternatives to the SRS estimator of variance were strongly correlated,and in all study settings consistently closer to the target design variance than the estimator for *** latter always produced the greatest *** populations with a near zero spatial autocorrelation,all estimators,performed equally,and delivered estimates close to the actual design ***:Without a linear trend,the SDR and DOR estimators were best with variance estimates more narrowly distributed around the benchmark;yet in terms of the least average absolute deviation,Matern’s estimator held a narrow *** a strong or moderate linear trend,Matern’s estimator is *** large populations,and a low sampling intensity,the performance of the investigated estimators becomes more similar.

关键词： Spatial autocorrelation Linear trend Model based Design biased Matern variance Successive difference replication variance Geary contiguity coefficient Random site effects

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Ethernet based time synchronization for raspberry Pi network improving network model verification for distributed active turbulent flow control

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Control Theory and Technology 2015年第2期13卷 204-210页

作者： Marcel DUECK Mario SCHLOESSER Stefan van WAASEN Michael SCHIEK Central Institute of Engineering Electronics and Analytics ZEA-2: Electronic SystemsForschungszentrum Juelich Gmb H ZEA-2 Wilhelm-Johnen-Straβe University of Duisburg-Essen Faculty of Engineering

Friction drag primarily determines the total drag of transport systems. A promising approach to reduce drag at high Reynolds numbers(> 104) are active transversal surface waves in combination with passive methods like a riblet surface. For the application in transportation systems with large surfaces such as airplanes, ships or trains, a large scale distributed real-time actuator and sensor network is required. This network is responsible for providing connections between a global flow control and distributed actuators and sensors. For the development of this network we established at first a small scale network model based on Simulink and True Time. To determine timescales for network events on different package sizes we set up a raspberry Pi based testbed as a physical representation of our first model. These timescales are reduced to time differences between the deterministic network events to verify the behavior of our model. Experimental results were improved by synchronizing the testbed with sufficient precision. With this approach we assure a link between the large scale model and the later constructed microcontroller based real-time actuator and sensor network for distributed active turbulent flow control.

关键词： raspberry Pi True Time distributed actuator and sensor network network model

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