{"title":"A SPECIFIC APPROACH TO LEAST SQUARES ADJUSTMENT OF THE STATE LEVELLING NETWORK","authors":"S. Gospodinov, E. Peneva, Penio S. Penev","doi":"10.5593/sgem2022/2.1/s09.20","DOIUrl":null,"url":null,"abstract":"In addition to its main purpose: establishing and maintaining the parameters of the height system for the territory of a given state (country), state levelling networks also serve to establish (register) the contemporary (recent) vertical movements of the Earth's crust. The detection of such movements, besides in a purely research sense, is of great practical importance. The displacement of the benchmarks over time plays an essential role in seismic forecasting in the short and long term. \nSometimes, not very often, it happens that the duration of the measurements in a single cycle of State levelling network measurement is commensurate or nearly commensurate with the period between the different cycles. Such a fact raises serious issues to be addressed, both in the process of preliminary accuracy estimation of the measurements and in the formation of the adjustment model. A period of ten years or more is long enough for displacements on the order of a few mm (millimeters) to become apparent and to be reliably detected. \nOne possible approach, in such cases, is to apply a modified version of adjustment using the Least Squares Method. It would be appropriate, as additional unknowns, to introduce the velocities of the individual benchmarks of the network into the adjustment model. Thus, taking into account the time of the start of the measurements, preconditions are created for taking into account the dynamic behaviour of the benchmarks during the measurement period. \nThe applied adjustment model is based on the so-called \"dynamic\" or \"kinematic\" adjustment model, which also takes into account some technological features in the overall network measurement process.","PeriodicalId":375880,"journal":{"name":"22nd SGEM International Multidisciplinary Scientific GeoConference Proceedings 2022, Informatics, Geoinformatics and Remote Sensing","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"22nd SGEM International Multidisciplinary Scientific GeoConference Proceedings 2022, Informatics, Geoinformatics and Remote Sensing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5593/sgem2022/2.1/s09.20","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In addition to its main purpose: establishing and maintaining the parameters of the height system for the territory of a given state (country), state levelling networks also serve to establish (register) the contemporary (recent) vertical movements of the Earth's crust. The detection of such movements, besides in a purely research sense, is of great practical importance. The displacement of the benchmarks over time plays an essential role in seismic forecasting in the short and long term.
Sometimes, not very often, it happens that the duration of the measurements in a single cycle of State levelling network measurement is commensurate or nearly commensurate with the period between the different cycles. Such a fact raises serious issues to be addressed, both in the process of preliminary accuracy estimation of the measurements and in the formation of the adjustment model. A period of ten years or more is long enough for displacements on the order of a few mm (millimeters) to become apparent and to be reliably detected.
One possible approach, in such cases, is to apply a modified version of adjustment using the Least Squares Method. It would be appropriate, as additional unknowns, to introduce the velocities of the individual benchmarks of the network into the adjustment model. Thus, taking into account the time of the start of the measurements, preconditions are created for taking into account the dynamic behaviour of the benchmarks during the measurement period.
The applied adjustment model is based on the so-called "dynamic" or "kinematic" adjustment model, which also takes into account some technological features in the overall network measurement process.