Improved geoid modeling using observed and modeled gravity gradients in Taiwan

Yu Shen Hsiao*, Chein-way Hwang, Meng Ling Wu, Jung Chieh Chang


研究成果: Article同行評審

2 引文 斯高帕斯(Scopus)


The authors present a new geoid modeling procedure that can greatly improve relative geoid accuracy in mountainous areas, leading to improved applications for modern geodetic techniques, such as light detection and ranging (LIDAR), in mapping orthometric heights over steep terrain on which precise slopes are needed to assess the risk of landslides and the suitability of industrial development. The new procedure (1) measures gravity gradients or computing modeled gravity gradients from a regular grid of gravity anomalies, (2) uses these gradients to refine gravity anomalies, and (3) uses the gravity anomalies to compute geoidal undulations. This new procedure was tested in Taiwan. In situ gravity gradients were measured at approximately 4,000 gravity sites to compare the modeled gravity gradients. In the test, ground gravity observations are reduced to gravity anomalies at mean sea surface using three types of gravity gradients: normal, modeled, and observed. The researchers' geoid modeling uses the method of least-squares collocation (LSC) with the remove-compute-restore (RCR) procedure. Free-air gravity anomalies, as reduced using the observed and modeled gravity gradients, deviate from those using normal gradients by up to 100 mgal in high mountains. Using free-air gravity anomalies derived from observed and modeled gravity gradients, the authors can improve the relative geoid accuracies by up to 17 and 18 cm, respectively, for Route 3 (an area with high mountains) in Taiwan.

期刊Journal of Surveying Engineering
出版狀態Published - 1 5月 2017


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