Influencing factors on the accuracy of local geoid model

Different modification methods and software programs were developed to obtain accurate local geoid models in the past two decades. The quantitative effect of the main factors on the accuracy of local geoid modeling is still ambiguous and has not been clearly diagnosed yet. This study presents effort...

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Bibliographic Details
Published in:Geodesy and Geodynamics
Main Author: Jalal S.J.; Musa T.A.; Md Din A.H.; Wan Aris W.A.; Shen W.; Pa'suya M.F.
Format: Review
Language:English
Published: KeAi Communications Co. 2019
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070930634&doi=10.1016%2fj.geog.2019.07.003&partnerID=40&md5=e602f8b7487cedd6d1b301c4fffcbfa8
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Summary:Different modification methods and software programs were developed to obtain accurate local geoid models in the past two decades. The quantitative effect of the main factors on the accuracy of local geoid modeling is still ambiguous and has not been clearly diagnosed yet. This study presents efforts to find the most influential factors on the accuracy of the local geoid model, as well as the amount of each factor's effect quantitatively. The methodology covers extracting the quantitative characteristics of 16 articles regarding local geoid models of different countries. The Statistical Package of Social Sciences (SPSS) software formulated a strong multiple regression model of correlation coefficient r = 0.999 with a high significance coefficient of determination R2 = 0.997 and adjusted R2 = 0.98 for the required effective factors. Then, factor analysis is utilized to extract the dominant factors which include: accuracy of gravity data (40%), the density of gravity data (25%) (total gravity factors is 65%), the Digital Elevation Model (DEM) resolution (16%), the accuracy of GPS/leveling points (10%) and the area of the terrain of the country/state under the study (9%). These results of this study will assist in developing more accurate local geoid models. © 2019 The Authors
ISSN:16749847
DOI:10.1016/j.geog.2019.07.003