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Geodesy
Published in Basudeb Bhatta, Global Navigation Satellite Systems, 2021
The word geodesy comes from Greek, literally meaning ‘dividing the earth’. The first practical objective of geodesy was the provision of an accurate framework for the control of national topographical surveys, and hence it is the foundation of a nation’s maps (Smith 1997). To prepare the map, geodesy must define the basic geometrical and physical properties of the figure of the earth. The scientific objective of geodesy has therefore always been to determine the size, shape, and gravitational field of the earth (Clarke 2001; DMA 1984; Smith 1997; Seeber 1993; Hofmann-Wellenhof and Moritz 2005). Geodesy can be defined as the science which deals with the methods of precise measurements of elements of the surface of the earth and their treatment for the determination of the geographic positions on the surface of the earth including the gravity field of the earth in a three-dimensional time varying space. It also deals with the theory of size and shape of the earth. Satellite geodesy is the measurement of the form and dimensions of the earth, the location of objects on its surface and the figure of the earth’s gravity field by means of satellite technique (Seeber 1993). Traditional astronomical geodesy, that includes astronomical positioning, is not commonly considered a part of satellite geodesy. This chapter will discuss the essentials of geodesy to understand GNSS positioning.
Geodesy Fundamentals
Published in Julio Sanchez, Maria P. Canton, William Perrizo, Space Image Processing, 2018
Julio Sanchez, Maria P. Canton
Geodesy is an applied field of physical geography that relates to the size and shape of the earth and to measurements on its surface. It is usually divided into two parts: geometrical geodesy and physical geodesy. The second one, physical geodesy, relates to the gravity fields of the earth and how these fields affect its shape. In the following discussion we ignore physical geodesy and concentrate on the earth’s shape and measurement.
Strain monitoring of hard rock mine slopes
Published in Vladimir Litvinenko, EUROCK2018: Geomechanics and Geodynamics of Rock Masses, 2018
Iuliia Fedotova, Eduard Kasparian, Ivan Rozanov, Mikhail Kuznetsov, Roman Dostovalov, Roman Dostovalov
Among the main parameters determining the geomechanical state of the rock mass and mining structures, the authors have chosen strains and displacements, as the most physically verified and informative parameters for the state of the hierarchically-blocked rock massif. At present, strains and displacements are most widely measured by the traditional geodetic direct methods, but recently new methods of area surveys such as laser and radar scanning and satellite geodesy methods, including GPS and GLONASS technologies, start to be used.
Application of robust estimation in geodesy using the harmony search algorithm
Published in Journal of Spatial Science, 2018
Geodesy deals with the measurement of the earth and in this sense it uses advanced measurement techniques such as GNSS. There are a number of GNSSs in operation (fully or partly): the United States Global Positioning System (GPS), the Russian GLObal’naya NAvigatsionnaya Sputnikovaya Sistema (GLONASS) and the European Galileo system. Using these techniques the coordinates of the points are determined in a chosen coordinate system. GNSS networks are established for this purpose and measurements are made. Once established, GNSS networks may be used by many professions; for example, geodesy, surveying, geology, forestry, environmental engineering, civil engineering, archaeology, agriculture, urban planning, military and probably many more. The classic parameter estimation method used for geodetic measurements (see section 2) is the LS (least squares) method. Yet, to obtain correct results for estimated parameters, it must be ensured that no outliers (gross errors/blunders) are present in the measurements and only the random errors remain. Otherwise, the LS method might provide very poor results. Unfortunately, errors are generally present in the measurement data-set. On the other hand, many RE (robust estimation) methods which are less sensitive against outliers than the LS method have been developed and they can produce more reliable results even if some measurements contain errors (Rousseeuw 1984, Hampel et al. 1986, Huber and Ronchetti 2009, Yetkin and Inal 2011). Robust estimation techniques are created to offer maximum resistance to the influence of errors in the measurements. Thus, robust estimation not only works as a detection tool but also provides the least-affected solution. There are numerous robust methods in use, including least absolute deviations (Edgeworth Edgeworth 1887, Marshall and Bethel 1996, Marshall 2002, Simkooei 2003), M-estimators (Huber 1964), R-estimators (Jaeckel 1972), least trimmed squares (Rousseeuw 1984, Rousseeuw and Leroy 1987), least median squares (Rousseeuw 1984) and sign-constrained robust least squares (Xu 2005, Yetkin and Berber 2013).