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Designing an effective and efficient survey network is one of the essential aspects in the implement of field surveys. In contrast, the design of a survey network is a complicated and sophisticated task because a survey network needs to meet or exceed specified criteria for precision, reliability, sensitivity, and cost. Other pivotal factors must be taken into account in a feasible design, such as geological criteria, suitability for equipment measurement, long term safety, field time and access costs (Talaya, et al., 1999). Therefore, it is vital to implement the techniques and instruments of the design of the survey network to deal with a variety of current problems.
For instance, deformation monitoring network of dam (Gökalp and Taşçı, 2009), precise levelling of the network (Shahrum and Azhari, 2009), and control the network of construction, have drawn intensive attention for surveyors. The aim of survey network design is understood as creating an optimal network configuration and observation plan that satisfies the postulated network quality criteria (e.g., error ellipses and redundancy numbers) with minimum cost (Amiri-Simkooei and Sharifi, 2004).
In other words, survey network design has two aspects: using the current equipment and condition to imbue the layout of the survey network with a higher accuracy, sensitivity and reliability; the cost of the survey network is the lowest when the network meets the precision, sensitivity and reliability.. Increasing amounts of researchers have considered the very pivotal role feedback loops play in the overall progress of network design technology (Mishima 2009; Anderson, and Mikhail, 2003). With the growing need for increased feedback mechanisms to ensure accuracy and reliability, software such as Geolab has emerged to attempt to account for these measures through trial-and-error procedural least square adjustment.
Still, the complete potential of such a system remains to be understood. This research advances with a context consideration of this theoretical understanding. 1.2 Classification of survey network design In accordance with Grafarend’s suggestions (Grafarend, 1974), survey network design can be decomposed into four smaller problems. 1) Zero order design (ZOD) The free network that is a known configuration and observation plan will select an optimal coordinate system for the coordinate of control points and their variance.
In other words, to determine the coordinates of vector X and the co-factor matrix when the design matrix and weight matrix of observation P is known, so that X is an objective function to extremes. Therefore, ZOD is an adjustment problem. 2) First order design (FOD) Design matrix A will be determined when the observation matrix P is known, so that some elements of the survey network reach a predetermined value or the highest accuracy, or the best approximation to the Coordinate of a given matrix. 3) Second order design (SOD) To determine the weight matrix of observation P when the design matrix P is known, so that some elements can achieve the desired accuracy or the highest accuracy, or coordinate the best approximation of a co-factor matrix given matrix. 4) Third order design
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