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بررسی اثر اصلاح چگالی و کوواریانس بهبودیافته در مدل‌سازی محلی میدان گرانی به‌روش کالوکیشن کمترین‌مربعات در ایران | ||
| فیزیک زمین و فضا | ||
| مقاله 6، دوره 49، شماره 2، شهریور 1402، صفحه 371-388 اصل مقاله (2.9 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/jesphys.2023.348002.1007454 | ||
| نویسندگان | ||
| مهکامه قاسمی* ؛ صباح راموز؛ عبدالرضا صفری | ||
| گروه مهندسی نقشه‌برداری و ژئوماتیک، پردیس دانشکده‌های فنی، دانشگاه تهران، تهران، ایران. | ||
| چکیده | ||
| به‌دلیل عدم‌وجود اطلاعات کافی در مورد چگالی اجرام زیرسطحی، در مدل‌سازی میدان گرانی زمین، معمولاً از میانگین جهانی چگالی به‌صورت عددی ثابت در کل منطقه موردمطالعه استفاده می‌شود. در حالی‌که، افزایش دقت تقریب چگالی در مدل‌سازی اثر گرانش ناشی از جرم توپوگرافی، دقت مدل‌سازی میدان گرانی را بالاتر خواهد برد. برای امکان‌سنجی این موضوع، از یک مدل چگالی توپوگرافی با قدرت تفکیک "30×"30 که از پردازش نقشه‌های لرزه‌نگاری و اطلاعات ماهواره‌ای لایه‌های لیتوسفر تهیه شده، برای افزایش دقت تقریب چگالی ثابت در چهار منطقه مطالعاتی درون ایران با وضعیت توپوگرافی و پراکندگی داده متفاوت استفاده شده است. به این ترتیب که، علاوه‌بر مقدار میانگین جهانی، مقدار میانگین چگالی در ایران و منطقه نیز در مدل‌سازی اثر گرانش ناشی از جرم توپوگرافی لحاظ شد. در مدل‌سازی میدان گرانی، روش کالوکیشن کمترین‌مربعات و به‌تبع، تکنیک RTM در مدل‌سازی اثر گرانش ناشی از جرم توپوگرافی به‌کار گرفته شد. همچنین، افزون بر اصلاح چگالی، استفاده از رویکرد کوواریانس بهبودیافته در مدل‌سازی میدان گرانی نیز مورد ارزیابی واقع شد. نتایج مقایسه با نقاط کنترلی این پژوهش نشان می‌دهد، به‌کارگیری اصلاح چگالی و رویکرد کوواریانس بهبودیافته در مناطق با توپوگرافی خشن و فاقد داده گرانی‌سنجی کافی و پراکندگی مناسب، به‌شکل قابل‌اعتنایی (88/1 میلیگال معادل %6/15 در منطقه مطالعاتی این پژوهش) باعث افزایش دقت مدل‌سازی میدان گرانی می‌شود. | ||
| کلیدواژه‌ها | ||
| توپوگرافی؛ تکنیک حذف و محاسبه؛ زمین باقی‌مانده؛ انحراف‌معیار؛ تراکم داده | ||
| عنوان مقاله [English] | ||
| On investigation of density correction and improved covariance effect on local modeling of gravity field by least squares collocation method in Iran | ||
| نویسندگان [English] | ||
| Mahkameh Ghasemi؛ Sabah Ramouz؛ Abdolreza Safari | ||
| Department of Surveying and Geomatics Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran. | ||
| چکیده [English] | ||
| Due to the lack of sufficient information about the density of subsurface masses, in the modeling of the earth gravity field, usually a constant global average density value is used for the entire studied area. However, any accuracy improvement of the mass density used in the modeling of topographic gravitation will increase the accuracy of gravity field modeling. To approve this quantitatively, a topographic density model with a resolution of 30×30 arc second is prepared from the processing of seismographic maps and satellite data of the layers of the lithosphere and used instead of a constant mass density in four study regions inside Iran with diverse topographic and data distribution. These four regions have the dimension of 2.5×3 degrees. The point intervals in the first and third regions (R1 and R3) are approximately 5 minutes, while in the second and fourth regions (R2 and R4) the intervals are approximately 13 minutes. In areas with the same point distribution, R1 has a relatively smoother topography than R3. The topography in R2 is relatively rougher than R4. In addition to the global average density value, the average value for Iran and the region is also included in modeling the gravity topographic masses. Owe to topography diversity, these areas seem to be suitable for an investigation of the RTM technique performance. In modeling the gravity field, the least squares collocation method and, consequently, the RTM technique are used in modeling the effect of topographic mass gravitation. In order to evaluate the effect of lateral density variations when using the RTM technique for gravity field modeling of the earth, the least squares collocation method is used in this research. The RCR technique is used for gravity field modeling by least squares collocation method and the effect of the global topography is removed. To remove the global gravitational effect from the observations, the EIGEN6C4 model degree and order 360 is used. To remove the effect of topography by RTM method, a digital elevation model with a point density of 1 second arc is used. In addition to density correction, the use of improved covariance algorithm in gravity field modeling is also evaluated in this research. The results show that in the areas with more topography, and hence more density variations, the effect of density modification in removing the effect of topography from the gravity anomalies signal of the region is more significant. Furthermore, comparison to the control points of this study shows that application of density correction and the improved covariance algorithm in areas with rough topography and lack of sufficient gravimetric data and proper distribution, the accuracy of gravity field modeling can be improved by 15.6%. Using the IC approach in four regions leads to an increase in modeling accuracy. Among these regions, the highest increase in accuracy is related to region 2 (with a decrease of 1 mGal of standard deviation) and relatively related to region 3 (with a decrease of 11.5% in standard deviation). These two areas have rougher topography than areas 1 and 4. | ||
| کلیدواژه‌ها [English] | ||
| Topography, remove calculate restore (RCR) technique, residual terrain, standard deviation, data density | ||
| مراجع | ||
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Foroughi, I., Afrasteh, Y., Ramouz, S., & Safari, A. (2017). Local evaluation of earth gravitational models, case study: Iran. Geodesy, 43, 1-13. Forsberg, R. (1984). A study of terrain reductions, density anomalies and geophysical inversion methods in gravity field modelling. In.: Ohio State Univ Columbus Dept Of Geodetic Science and Surveying. Forsberg, R., & Tscherning, C. C. (1981). The use of height data in gravity field approximation by collocation. Journal of Geophysical Research: Solid Earth, 86, 7843-54. Förste, C., Bruinsma, S., Abrikosov, O., Marty, J., Flechtner, F., Balmino, G., Barthelmes, F., & Biancale, R. (2014). EIGEN-6C4 The latest combined global gravity field model including GOCE data up to degree and order 2190 of GFZ Potsdam and GRGS Toulouse. Goli, M., & Moosavi Alkazemi, H. (2018). The role of topographic-isostatic effects on smoothing of the gravity anomaly. Iranian Journal of Geophysics, 12, 141-153 (in Persian). Heydarizadeh Shali, H., Ramouz, S., Safari, A., & Barzaghi, R. (2020). Assessment of Tscherning-Rapp covariance in Earth gravity modeling using gravity gradient and GPS/leveling observations. In EGU General Assembly Conference Abstracts, 1059. Hirt, C., & Flury, J. (2008). Astronomical-topographic levelling using high-precision astrogeodetic vertical deflections and digital terrain model data. Journal of Geodesy, 82, 231-48. Hirt, C., Yang, M., Kuhn, M., Bucha, B., Kurzmann, A., & Pail, R. (2019). SRTM2gravity: an ultrahigh resolution global model of gravimetric terrain corrections. Geophysical Research Letters, 46, 4618-27. Kuhn, M. (2000). GeoidBestimmung unter verwendung verschiedener dichtehypothesen. Deutsche Geodatische Kommission', Dissertationen, Munchen. Laske, G., Masters, G., Ma, Z., & Pasyanos, M. (2012). CRUST1. 0: An updated global model of Earth’s crust. Geophys Res Abs, 14, 743. Martinec, Z. (1993). Effect of lateral density variations of topographical masses in view of improving geoid model accuracy over Canada. Contract report for Geodetic Survey of Canada. Moritz, H. (1980). Advanced Physical Geodesy'Herbert Wichmann Verlag. Karlsruhe, 500. Nasa, J. (2013). NASA shuttle radar topography mission global 1 arc second. NASA EOSDIS Land Processes DAAC, 10. Omang, O., & Forsberg, R. (2000). How to handle topography in practical geoid determination: three examples. Journal of Geodesy, 74, 458-66. Ramouz, S., & Safari, A. (2020). Assessment of the Improved Covariance in Local Geoid Modeling Using Least Squares Collocation-Case study: Tehran Province. Journal of the Earth Space Physics, 46, 517-35. Ramouz, S., Afrasteh, Y., Reguzzoni, M., & Safari, A. (2020). Assessment of local covariance estimation through Least Squares Collocation over Iran. Advances in Geosciences, 50, 65-75. Rexer, M., Hirt, C., Bucha, B., & Holmes, S. (2018). Solution to the spectral filter problem of residual terrain modelling (RTM). Journal of Geodesy, 92, 675-90. Safari, A., Ramouz, S., & Jomegi, A. (2014). Improvement in gravity field modeling using collocation by means of crust density, global geopotential models and combination of heterogeneous observations. Journal of the Earth Space Physics, 40(4), 83-98. Sanso, F. (1986). Statistical methods in physical geodesy. in, Mathematical and numerical techniques in physical geodesy (Springer). Sheng, M., Shaw, C., Vaníček, P., Kingdon, R., Santos, M., & Foroughi, I. (2019). Formulation and validation of a global laterally varying topographical density model. Tectonophysics, 762, 45-60. Tenzer, R., & Vaníček, P. (2003). Correction to Helmert’s orthometric height due to actual lateral variation of topographical density. Brazilian Journal of Cartography-Revista Brasileira de Cartografia, 55, 44-47. Vergos, G. S., Erol, B., Natsi, D. A., Grigoriadis, V. N., Işık, M. S., & Ilias, T. N. (2018). Preliminary results of GOCE-based height system unification between Greece and Turkey over marine and land areas. Acta Geodaetica Et Geophysica, 53, 61-79. Yang, M., Hirt, C., Robert, T., & Pail, R. (2018). Experiences with the use of mass-density maps in residual gravity forward modelling. Studia Geophysica et Geodaetica, 62, 596-623. Yildiz, H., Forsberg, R., Ågren, J., Tscherning, C., & Sjöberg, L. (2012). Comparison of remove-compute-restore and least squares modification of Stokes' formula techniques to quasi-geoid determination over the Auvergne test area. Journal of Geodetic Science, 2, 53-64. | ||
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