研究生: |
陳勇福 Chen, Yun-fu |
---|---|
論文名稱: |
利用絕對重力測量與GPS觀測台灣衛星追蹤站高程變化之比較分析 Comparisons of geocentric height changes derived from absolute gravimetry and GPS at continuous tracking stations in Taiwan |
指導教授: |
楊名
Yang, Ming |
學位類別: |
碩士 Master |
系所名稱: |
工學院 - 測量及空間資訊學系 Department of Geomatics |
論文出版年: | 2007 |
畢業學年度: | 95 |
語文別: | 中文 |
論文頁數: | 91 |
中文關鍵詞: | 全球衛星定位 、絕對重力 |
外文關鍵詞: | GPS, Absolute Gravity |
相關次數: | 點閱:82 下載:5 |
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全球至今已有超過100個衛星連續追蹤站使用於監測地殼變動,以獲得測站定義於國際參考框架(ITRF)下之三維坐標及速度場資訊。本研究分析了台灣衛星追蹤站2003至2006年的全球衛星定位(GPS)資料,採用兩種不同的策略估計測站的ITRF坐標變化速度量;並且於2006至2007年使用絕對重力儀FG5於其中的三個追蹤站進行絕對重力(AG)觀測作業,並在經過嚴謹的重力改正計算後,將重力變化值轉換為測站高程變化速度量。本研究比較由兩種不同觀測技術求得之測站高程變化速度量,得到以下的初步結論:(1)地下水位變化對於AG資料的正確性具有非常重要的影響,若未能有效改正則所推導之高程變化速度量將很可能會具有顯著的偏差量;(2)由GPS與由AG所得到的高程變化速度量之間的吻合度可達到1-2 cm/yr;(3)以1年的AG觀測資料與4年的GPS觀測資料作為比較基礎仍嫌不足,應累積長期的觀測資料,尤其是AG資料,以得到更為可靠的分析成果。
To date, at least hundreds of Global Positioning System (GPS) continuous tracking stations have been used worldwide to measure tectonic motions. The derived 3-D station coordinates and velocities are defined in the International Terrestrial Reference Frame (ITRF). We analyzed GPS data collected at the Taiwanese continuous tracking stations from 2003 to 2006, and adopted two strategies to compute high-precision time series of ITRF coordinates of the stations. From 2006 to 2007, we have started to measure absolute gravity (AG) readings at three of the stations with an FG5 gravimeter. After careful modeling of various gravity corrections, we then converted the time series of AG readings to geocentric height changes of the stations. This study compares the geocentric height changes derived from AG readings and GPS. Initial comparison results suggest that (1) accurate correction for ground water table variation is vital to the correct interpretation of AG readings as large biases in AG-derived vertical velocities are likely to emerge if the effect of ground water is not modeled properly; and (2) the level of agreement of vertical velocities obtained from GPS and AG is 1-2 cm/yr; and (3) longer time series of field observations, particularly the AG data, are needed for a more reliable comparison analysis.
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