Fourier geoid determination with irregular data

1995 ◽  
Vol 70 (1-2) ◽  
pp. 2-12 ◽  
Author(s):  
Michael G. Sideris
Keyword(s):  
Geoid Determination ◽  
Irregular Data

scholarly journals Comparison of remove-compute-restore and least squares modification of Stokes' formula techniques to quasi-geoid determination over the Auvergne test area

2012 ◽  
Vol 2 (1) ◽  
pp. 53-64 ◽  
Author(s):  
H. Yildiz ◽  
R. Forsberg ◽  
J. Ågren ◽  
C. Tscherning ◽  
L. Sjöberg
Keyword(s):  
Least Squares ◽  
Gravity Data ◽  
Test Area ◽  
Geoid Determination ◽  
Geopotential Model ◽  
Low Degree ◽  
Residual Terrain Modelling ◽  
The Alps ◽  
Stokes Formula ◽  
Regional Geoid Determination

Comparison of remove-compute-restore and least squares modification of Stokes' formula techniques to quasi-geoid determination over the Auvergne test areaThe remove-compute-restore (RCR) technique for regional geoid determination implies that both topography and low-degree global geopotential model signals are removed before computation and restored after Stokes' integration or Least Squares Collocation (LSC) solution. The Least Squares Modification of Stokes' Formula (LSMS) technique not requiring gravity reductions is implemented here with a Residual Terrain Modelling based interpolation of gravity data. The 2-D Spherical Fast Fourier Transform (FFT) and the LSC methods applying the RCR technique and the LSMS method are tested over the Auvergne test area. All methods showed a reasonable agreement with GPS-levelling data, in the order of a 3-3.5 cm in the central region having relatively smooth topography, which is consistent with the accuracies of GPS and levelling. When a 1-parameter fit is used, the FFT method using kernel modification performs best with 3.0 cm r.m.s difference with GPS-levelling while the LSMS method gives the best agreement with GPS-levelling with 2.4 cm r.m.s after a 4-parameter fit is used. However, the quasi-geoid models derived using two techniques differed from each other up to 33 cm in the high mountains near the Alps. Comparison of quasi-geoid models with EGM2008 showed that the LSMS method agreed best in term of r.m.s.

scholarly journals Traversal Caches: A Framework for FPGA Acceleration of Pointer Data Structures

2010 ◽  
Vol 2010 ◽  
pp. 1-16 ◽  
Author(s):  
James Coole ◽  
Greg Stitt
Keyword(s):  
Data Structures ◽  
Reconfigurable Computing ◽  
Application Development ◽  
Sequential Memory ◽  
Generalized Framework ◽  
Field Programmable ◽  
Order Of Magnitude ◽  
Programmable Gate Arrays ◽  
Irregular Data ◽  
Access Patterns

Field-programmable gate arrays (FPGAs) and other reconfigurable computing (RC) devices have been widely shown to have numerous advantages including order of magnitude performance and power improvements compared to microprocessors for some applications. Unfortunately, FPGA usage has largely been limited to applications exhibiting sequential memory access patterns, thereby prohibiting acceleration of important applications with irregular patterns (e.g., pointer-based data structures). In this paper, we present a design pattern for RC application development that serializes irregular data structure traversals online into a traversal cache, which allows the corresponding data to be efficiently streamed to the FPGA. The paper presents a generalized framework that benefits applications with repeated traversals, which we show can achieve between 7x and 29x speedup over pointer-based software. For applications without strictly repeated traversals, we present application-specialized extensions that benefit applications with highly similar traversals by exploiting similarity to improve memory bandwidth and execute multiple traversals in parallel. We show that these extensions can achieve a speedup between 11x and 70x on a Virtex4 LX100 for Barnes-Hut n-body simulation.

scholarly journals A method of generative model design based on irregular data in application to heat transfer problems

2021 ◽  
Vol 1959 (1) ◽  
pp. 012012
Author(s):  
Nikolay Bykov ◽  
Alexander Hvatov ◽  
Anna Kalyuzhnaya ◽  
Alexander Boukhanovsky
Keyword(s):  
Heat Transfer ◽  
Generative Model ◽  
Model Design ◽  
Irregular Data ◽  
Transfer Problems

Irregular Data

1999 ◽  
pp. 597-622
Author(s):  
John Kauffman ◽  
Kevin Spencer ◽  
Thearon Willis
Keyword(s):  
Irregular Data

scholarly journals Time Series Analysis of Land Cover Change in Dry Mountains: Insights from the Tajik Pamirs

2021 ◽  
Vol 13 (19) ◽  
pp. 3951
Author(s):  
Kim André Vanselow ◽  
Harald Zandler ◽  
Cyrus Samimi
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Land Cover ◽  
Land Cover Change ◽  
Vegetation Index ◽  
Demographic Data ◽  
Mountainous Areas ◽  
Generalized Additive Mixed Models ◽  
Additive Mixed Models ◽  
Irregular Data

Greening and browning trends in vegetation have been observed in many regions of the world in recent decades. However, few studies focused on dry mountains. Here, we analyze trends of land cover change in the Western Pamirs, Tajikistan. We aim to gain a deeper understanding of these changes and thus improve remote sensing studies in dry mountainous areas. The study area is characterized by a complex set of attributes, making it a prime example for this purpose. We used generalized additive mixed models for the trend estimation of a 32-year Landsat time series (1988–2020) of the modified soil adjusted vegetation index, vegetation data, and environmental and socio-demographic data. With this approach, we were able to cope with the typical challenges that occur in the remote sensing analysis of dry and mountainous areas, including background noise and irregular data. We found that greening and browning trends coexist and that they vary according to the land cover class, topography, and geographical distribution. Greening was detected predominantly in agricultural and forestry areas, indicating direct anthropogenic drivers of change. At other sites, greening corresponds well with increasing temperature. Browning was frequently linked to disastrous events, which are promoted by increasing temperatures.

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