{"title":"Evaluation of terrestrial and airborne gravity data over Antarctica – a generic approach","authors":"P. Zingerle, R. Pail, M. Scheinert, T. Schaller","doi":"10.1515/jogs-2019-0004","DOIUrl":null,"url":null,"abstract":"Abstract The AntGrav project, funded by the German Research Foundation (DFG) has the main objective to homogenize and optimize Antarctic gravity field information. Within this project an evaluation procedure is needed to inspect all different kind of gravity field surveys available in Antarctica. In this paper a suitable methodology is proposed. We present an approach for fast 3D gravity point data reduction in different spectral bands. This is achieved through pre-calculating a fine 3D mesh of synthesized gravity functionals over the entirety of the Antarctic continent, for which two different global models are used: the combined satellite model GOCO05s for the long-wavelength part, and the topographic model Earth2014 for the shorter wavelengths. To maximize the applicability separate meshes are calculated for different spectral bands in order to specifically reduce a certain band or a selected combination. All meshes are calculated for gravity anomalies as well as gravity disturbances. Utilizing these meshes, synthesized gravity data at arbitrary positions is computed by conventional 3D interpolation methods (e.g. linear, cubic or spline). It is shown that the applied approach can reach a worst-case interpolation error of less than 1 mGal. Evaluation results are presented for the AntGG grid and exemplary for the in-situ measurements of the AGAP and BAS-LAND campaigns. While general properties, large-scale errors and systematic effects can usually be detected, small-scale errors (e.g. of single points) are mostly untraceable due to the uncertainties within the topographic model.","PeriodicalId":44569,"journal":{"name":"Journal of Geodetic Science","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Geodetic Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/jogs-2019-0004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 3
Abstract
Abstract The AntGrav project, funded by the German Research Foundation (DFG) has the main objective to homogenize and optimize Antarctic gravity field information. Within this project an evaluation procedure is needed to inspect all different kind of gravity field surveys available in Antarctica. In this paper a suitable methodology is proposed. We present an approach for fast 3D gravity point data reduction in different spectral bands. This is achieved through pre-calculating a fine 3D mesh of synthesized gravity functionals over the entirety of the Antarctic continent, for which two different global models are used: the combined satellite model GOCO05s for the long-wavelength part, and the topographic model Earth2014 for the shorter wavelengths. To maximize the applicability separate meshes are calculated for different spectral bands in order to specifically reduce a certain band or a selected combination. All meshes are calculated for gravity anomalies as well as gravity disturbances. Utilizing these meshes, synthesized gravity data at arbitrary positions is computed by conventional 3D interpolation methods (e.g. linear, cubic or spline). It is shown that the applied approach can reach a worst-case interpolation error of less than 1 mGal. Evaluation results are presented for the AntGG grid and exemplary for the in-situ measurements of the AGAP and BAS-LAND campaigns. While general properties, large-scale errors and systematic effects can usually be detected, small-scale errors (e.g. of single points) are mostly untraceable due to the uncertainties within the topographic model.