Spatial Accuracy Evaluation of Population Density Grid Disaggregations with Corine Landcover

Author(s):  
Johannes Scholz ◽  
Michael Andorfer ◽  
Manfred Mittlboeck
IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 221176-221190
Author(s):  
Xiaoqing Song ◽  
Yi Long ◽  
Ling Zhang ◽  
David G. Rossiter ◽  
Fengyuan Liu ◽  
...  

Author(s):  
A. J. Sturm ◽  
M.-Y. Lee

Abstract This paper presents a stochastic model and a Monte Carlo computer simulation algorithm to combine all measurable non-linear kinematic and misalignment error components to predict the overall tooltip quasi-static robot spatial position accuracy for a gantry robot. These errors include joint position accuracies, joint misalignments, joint zero position offsets, axis directional straightness, squareness errors and kinematic coupling errors. All of these errors can be independently measured using a laser interferometer and/or other precision measuring instruments. The interation between robot joints and coupling between these error components are very complex making the determination of the overall robot spatial position accuracy difficult. In this paper a Monte Carlo computer simulation program for predicting overall robot spatial position accuracy based on a stochastic error model was developed. Finally, simulation results are compared with direct spatial accuracy test results using a computerized Theodolite system. This robot spatial accuracy qualification methodology has been accepted and recommended by RIA as part of American National Standard for robot accuracy evaluation.


2013 ◽  
Vol 58 (9) ◽  
pp. 2861-2877 ◽  
Author(s):  
Richard Castillo ◽  
Edward Castillo ◽  
David Fuentes ◽  
Moiz Ahmad ◽  
Abbie M Wood ◽  
...  

2020 ◽  
pp. 133-158
Author(s):  
K. A. Kholodilin ◽  
Y. I. Yanzhimaeva

A relative uniformity of population distribution on the territory of the country is of importance from socio-economic and strategic perspectives. It is especially important in the case of Russia with its densely populated West and underpopulated East. This paper considers changes in population density in Russian regions, which occurred between 1897 and 2017. It explores whether there was convergence in population density and what factors influenced it. For this purpose, it uses the data both at county and regional levels, which are brought to common borders for comparability purposes. Further, the models of unconditional and conditional β-convergence are estimated, taking into account the spatial dependence. The paper concludes that the population density equalization took place in 1897-2017 at the county level and in 1926—1970 at the regional level. In addition, the population density increase is shown to be influenced not only by spatial effects, but also by political and geographical factors such as climate, number of GULAG camps, and the distance from the capital city.


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