The Colorado geoid experiment was initiated and organized as a joint study by the Joint Working Group (JWG) 2.2.2 (1-cm geoid experiment) of the International Association of Geodesy (IAG) in 2017, and different institutions and research groups contributed to this study. The aim of this experiment was to clarify the repeatability of gravity potential values as International Height Reference System (IHRS) coordinates from different geoid determination approaches carried out with the same input dataset. The dataset included the terrestrial and airborne gravity observations, a digital terrain model, the XGM2016 global geopotential model and GPS/leveling data for model validations belonging to a mountainous area of approximately 550 km × 730 km in Colorado, US. The dataset was provided by National Geodetic Survey (NGS) department. In this frame, this article aims providing a discussion on Colorado geoid modeling through individual experimental results obtained by Istanbul Technical University-Gravity Research Group (ITU-GRG). This contribution mainly focused on modeling the Colorado geoid using the least squares modifications of Stokes and Hotine integral formulas with additive corrections. The computations using each formula were carried out using ITU-GRG software, including the solution variants based on terrestrial-only, airborne-only and combined gravity datasets. Then, the calculated experimental geoid models were validated using historical and recently measured profile-based GPS/leveling datasets, and they were also compared with the official solutions submitted by different institutions for the “1-cm geoid experiment” of IAG JWG 2.2.2. For all validation results, the Hotine and Stokes integral formulas yielded similar performances in terms of geoid accuracy; however, the models computed using the combined data had better accuracy than those using the terrestrial-only and airborne-only solutions. The geoid model solutions using the combined data had an accuracy of 2.69 cm for the Hotine method and 2.87 cm for the Stokes method in the test results using GPS/leveling data of the GSVS17 (Geoid Slope Validation Survey 2017) profile. Airborne data from the Gravity for the Redefinition of the American Vertical Datum (GRAV-D) project contributed significantly towards improving the geoid model, especially in the mountainous parts of the area.

2017年，国际大地测量学协会（IAG）的联合工作组（JWG）2.2.2（1厘米大地水准面实验）发起并组织了科罗拉多大地水准面实验，不同的机构和研究小组为该活动做出了贡献这项研究。本实验的目的是阐明重力势值的可重复性，即使用同一输入数据集执行的不同大地水准面确定方法的国际高度参考系统（IHRS）坐标。数据集包括地面和空中重力观测，数字地形模型，XGM2016全球地势模型以及用于模型验证的GPS /水平数据，这些数据属于美国科罗拉多州约550 km×730 km的山区。该数据集由美国国家大地测量局（NGS）部门提供。在这个框架中 本文旨在通过伊斯坦布尔技术大学重力研究小组（ITU-GRG）获得的单独实验结果，对科罗拉多大地水准面建模进行讨论。该贡献主要集中在使用Stokes和Hotine积分公式的最小二乘修正以及附加校正来对Colorado大地水准面进行建模。使用每个公式的计算是使用ITU-GRG软件进行的，包括基于地面，仅机载和组合重力数据集的解决方案变体。然后，使用历史数据和最近测量的基于轮廓的GPS /水准数据集验证计算出的实验大地水准面模型，并将它们与不同机构针对IAG JWG 2.2.2的“ 1-cm大地水准面实验”提交的官方解决方案进行比较。 。对于所有验证结果，在大地水准面精度方面，Hotine和Stokes积分公式产生了相似的性能。但是，与仅使用地面和仅使用机载解决方案的模型相比，使用组合数据计算出的模型具有更好的准确性。使用GSVS17（大地坡度验证调查2017）剖面的GPS /水准测量数据，使用合并数据的大地水准面模型解决方案在Hotine方法中的精度为2.69 cm，在Stokes方法中的精度为2.87 cm。重定义美国垂直基准重力项目（GRAV-D）的机载数据对改善大地水准面模型做出了重要贡献，特别是在该地区的山区。与仅使用地面和仅使用机载解决方案的模型相比，使用组合数据计算出的模型具有更高的准确性。使用GSVS17（大地坡度验证调查2017）剖面的GPS /水准测量数据，使用合并数据的大地水准面模型解决方案在Hotine方法中的精度为2.69 cm，在Stokes方法中的精度为2.87 cm。重定义美国垂直基准重力项目（GRAV-D）的机载数据对改善大地水准面模型做出了重要贡献，特别是在该地区的山区。与仅使用地面解决方案和仅使用机载解决方案的模型相比，使用合并数据计算出的模型具有更高的准确性。使用GSVS17（大地坡度验证调查2017）剖面的GPS /水准测量数据，使用合并数据的大地水准面模型解决方案在Hotine方法中的精度为2.69 cm，在Stokes方法中的精度为2.87 cm。重定义美国垂直基准重力项目（GRAV-D）的机载数据对改善大地水准面模型做出了重要贡献，特别是在该地区的山区。