TWO-EPOCH OPTIMAL DESIGN OF DISPLACEMENT MONITORING NETWORKS

In the traditional method of optimal design of displacement monitoring networks a higher precision, √2 times better than the desired accuracy of displacements, is considered for the net points in such a way that the accuracy of the detected displacements meets the desired one. However, in this paper, we develop an alternative method by considering the total number of observations in two epochs without such a simple assumption and we call it two-epoch optimisation. This method is developed based on the Gauss-Helmert adjustment model and the variances of the observations are estimated instead of the weights to optimise the observation plan. This method can deliver the same results as the traditional one, but with less required observations in each epoch

Optimal Design in Geodetic GNSS-based Networks

An optimal design of a geodetic network helps the surveying engineers maximise the efficiency of the network. A number of pre-defined quality requirements, i.e. precision, reliability, and cost, of the network are fulfilled by performing an optimisation procedure. Today, this is almost always accomplished by implementing analytical solutions, where the human intervention in the process cycle is limited to defining the requirements. Nevertheless, a trial and error method can be beneficial to some applications. In order to analytically solve an optimisation problem, it can be classified to different orders, where an optimal datum, configuration, and optimal observation weights can be sought such that the precision, reliability and cost criteria are satisfied. In this thesis, which is a compilation of six peer-reviewed papers, we optimised and redesigned a number of GNSS-based monitoring networks in Sweden by developing new methodologies. In addition, optimal design and efficiency of total station establishment with RTK-GNSS is investigated in this research. Sensitivity of a network in detecting displacements is of importance for monitoring purposes. In the first paper, a precision criterion was defined to enable a GNSS-based monitoring network to detect 5 mm displacements at each network point. Developing an optimisation model by considering this precision criterion, reliability and cost yielded a decrease of 17% in the number of observed single baselines implying a reliable and precise network at lower cost. The second paper concerned a case, where the precision of observations could be improved in forthcoming measurements. Thus a new precision criterion was developed to consider this assumption. A significant change was seen in the optimised design of the network for subsequent measurements. As yet, the weight of single baselines was subject to optimisation, while in the third paper, the effect of mathematical correlations between GNSS baselines was considered in the optimisation. Hence, the sessions of observations, including more than two receivers, were optimised. Four out of ten sessions with three simultaneous operating receivers were eliminated in a monitoring network with designed displacement detection of 5 mm. The sixth paper was the last one dealing with optimisation of GNSS networks. The area of interest was divided into a number of three-dimensional elements and the precision of deformation parameters was used in developing a precision criterion. This criterion enabled the network to detect displacements of 3 mm at each point. A total station can be set up in the field by different methods, e.g. free station or setup over a known point. A real-time updated free station method uses RTK-GNSS to determine the coordinates and orientation of a total station. The efficiency of this method in height determination was investigated in the fourth paper. The research produced promising results suggesting using the method as an alternative to traditional levelling under some conditions. Moreover, an optimal location for the total station in free station establishment was studied in the fifth paper. It was numerically shown that the height component has no significant effect on the optimal localisation.QC 2080115</p

Optimal Design in Geodetic GNSS-based Networks

An optimal design of a geodetic network helps the surveying engineers maximise the efficiency of the network. A number of pre-defined quality requirements, i.e. precision, reliability, and cost, of the network are fulfilled by performing an optimisation procedure. Today, this is almost always accomplished by implementing analytical solutions, where the human intervention in the process cycle is limited to defining the requirements. Nevertheless, a trial and error method can be beneficial to some applications. In order to analytically solve an optimisation problem, it can be classified to different orders, where an optimal datum, configuration, and optimal observation weights can be sought such that the precision, reliability and cost criteria are satisfied. In this thesis, which is a compilation of six peer-reviewed papers, we optimised and redesigned a number of GNSS-based monitoring networks in Sweden by developing new methodologies. In addition, optimal design and efficiency of total station establishment with RTK-GNSS is investigated in this research. Sensitivity of a network in detecting displacements is of importance for monitoring purposes. In the first paper, a precision criterion was defined to enable a GNSS-based monitoring network to detect 5 mm displacements at each network point. Developing an optimisation model by considering this precision criterion, reliability and cost yielded a decrease of 17% in the number of observed single baselines implying a reliable and precise network at lower cost. The second paper concerned a case, where the precision of observations could be improved in forthcoming measurements. Thus a new precision criterion was developed to consider this assumption. A significant change was seen in the optimised design of the network for subsequent measurements. As yet, the weight of single baselines was subject to optimisation, while in the third paper, the effect of mathematical correlations between GNSS baselines was considered in the optimisation. Hence, the sessions of observations, including more than two receivers, were optimised. Four out of ten sessions with three simultaneous operating receivers were eliminated in a monitoring network with designed displacement detection of 5 mm. The sixth paper was the last one dealing with optimisation of GNSS networks. The area of interest was divided into a number of three-dimensional elements and the precision of deformation parameters was used in developing a precision criterion. This criterion enabled the network to detect displacements of 3 mm at each point. A total station can be set up in the field by different methods, e.g. free station or setup over a known point. A real-time updated free station method uses RTK-GNSS to determine the coordinates and orientation of a total station. The efficiency of this method in height determination was investigated in the fourth paper. The research produced promising results suggesting using the method as an alternative to traditional levelling under some conditions. Moreover, an optimal location for the total station in free station establishment was studied in the fifth paper. It was numerically shown that the height component has no significant effect on the optimal localisation.QC 2080115</p

Tree Detection and Species Identification using LiDAR Data

The importance of single-tree-based information for forest management and related industries in countries like Sweden, which is covered in approximately 65% by forest, is the motivation for developing algorithms for tree detection and species identification in this study. Most of the previous studies in this field are carried out based on aerial and spectral images and less attention has been paid on detecting trees and identifying their species using laser points and clustering methods. In the first part of this study, two main approaches of clustering (hierarchical and K-means) are compared qualitatively in detecting 3-D ALS points that pertain to individual tree clusters. Further tests are performed on test sites using the supervised k-means algorithm in which the initial clustering points are defined as seed points. These points, which represent the top point of each tree are detected from the cross section analysis of the test area. Comparing those three methods (hierarchical, ordinary K-means and supervised K-means), the supervised K-means approach shows the best result for clustering single tree points. An average accuracy of 90% is achieved in detecting trees. Comparing the result of the thesis algorithms with results from the DPM software, developed by the Visimind Company for analysing LiDAR data, shows more than 85% match in detecting trees. Identification of trees is the second issue of this thesis work. For this analysis, 118 trees are extracted as reference trees with three species of spruce, pine and birch, which are the dominating species in Swedish forests. Totally six methods, including best fitted 3-D shapes (cone, sphere and cylinder) based on least squares method, point density, hull ratio and slope changes of tree outer surface are developed for identifying those species. The methods are applied on all extracted reference trees individually. For aggregating the results of all those methods, a fuzzy logic system is used because of its good reputation in combining fuzzy sets with no distinct boundaries. The best-obtained model from the fuzzy system provides 73%, 87% and 71% accuracies in identifying the birch, spruce and pine trees, respectively. The overall obtained accuracy in species categorization of trees is 77%, and this percentage is increased dealing with only coniferous and deciduous types classification. Classifying spruce and pine as coniferous versus birch as deciduous species, yielded to 84% accuracy

On Optimisation and Design of Geodetic Networks

Optimisation of a geodetic network is performed to provide its pre-set quality requirements. Today, this procedure is almost run with the aid of developed analytical approaches, where the human intervention in the process cycle is limited to defining the criteria. The existing complication of optimisation problem was terminated by classifying it into several stages. By performing these steps, we aim to design a network with the best datum, configuration and the observation weights, which meets the precision, reliability and cost criteria. In this thesis, which is a compilation of four papers in scientific journals, we investigate the optimisation problem by developing some new methods in simulated and real applications. On the first attempt, the impact of different constraints in using a bi-objective optimisation model is investigated in a simulated network. It is particularly prevalent among surveyors to encounter inconsistencies between the controlling constraints, such as precision, reliability and cost. To overcome this issue in optimisation, one can develop bi-objective or multi-objective models, where more criteria are considered in the object function. We found out that despite restricting the bi-objective model with precision and reliability constraints in this study, there is no significant difference in results compared to the unconstrained model. Nevertheless, the constrained models have strict controls on the precision of net points and observation reliabilities. The importance of optimisation techniques in optimal design of displacement monitoring networks leads to the development of a new idea, where all the observations of two epochs are considered in the optimisation procedure. Traditionally, an observation plan is designed for a displacement network and repeated for the second epoch. In the alternative method, by using the Gauss-Helmert method, the variances of all observations are estimated instead of their weights to perform the optimisation. This method delivers two observation plans for the two epochs and provides the same displacement precision as the former approach, while it totally removes more observations from the plan. To optimise a displacement monitoring network by considering a sensitivity criterion as a main factor in defining the capacity of a network in detecting displacements, a real case study is chosen. A GPS displacement monitoring network is established in the Lilla Edet municipality in the southwest of Sweden to investigate possible landslides. We optimised the existing monitoring network by considering all quality criteria, i.e. precision, reliability and cost to enable the network for detecting 5 mm displacement at the net points. The different optimisation models are performed on the network by assuming single baseline observations in each measurement session. A decrease of 17% in the number of observed baselines is yielded by the multi-objective model. The observation plan with fewer baselines saves cost, time and effort on the project, while it provides the demanded quality requirements. The Lilla Edet monitoring network is also used to investigate the idea, where we assume more precise instruments in the second of two sequential epochs. In this study, we use a single-objective model of precision, and constrained it to reliability. The precision criterion is defined such that it provides the sensitivity of the network in detecting displacements and has a better variance-covariance matrix than at the first epoch. As the observations are GPS baselines, we assumed longer observation time in the second epoch to obtain higher precision. The results show that improving the observation precision in the second epoch yields an observation plan with less number of baselines in that epoch. In other words, separate observation plans with different configurations are designed for the monitoring network, considering better observation precision for the latter epoch.QC 20150603Forma

On Optimisation and Design of Geodetic Networks

Optimisation of a geodetic network is performed to provide its pre-set quality requirements. Today, this procedure is almost run with the aid of developed analytical approaches, where the human intervention in the process cycle is limited to defining the criteria. The existing complication of optimisation problem was terminated by classifying it into several stages. By performing these steps, we aim to design a network with the best datum, configuration and the observation weights, which meets the precision, reliability and cost criteria. In this thesis, which is a compilation of four papers in scientific journals, we investigate the optimisation problem by developing some new methods in simulated and real applications. On the first attempt, the impact of different constraints in using a bi-objective optimisation model is investigated in a simulated network. It is particularly prevalent among surveyors to encounter inconsistencies between the controlling constraints, such as precision, reliability and cost. To overcome this issue in optimisation, one can develop bi-objective or multi-objective models, where more criteria are considered in the object function. We found out that despite restricting the bi-objective model with precision and reliability constraints in this study, there is no significant difference in results compared to the unconstrained model. Nevertheless, the constrained models have strict controls on the precision of net points and observation reliabilities. The importance of optimisation techniques in optimal design of displacement monitoring networks leads to the development of a new idea, where all the observations of two epochs are considered in the optimisation procedure. Traditionally, an observation plan is designed for a displacement network and repeated for the second epoch. In the alternative method, by using the Gauss-Helmert method, the variances of all observations are estimated instead of their weights to perform the optimisation. This method delivers two observation plans for the two epochs and provides the same displacement precision as the former approach, while it totally removes more observations from the plan. To optimise a displacement monitoring network by considering a sensitivity criterion as a main factor in defining the capacity of a network in detecting displacements, a real case study is chosen. A GPS displacement monitoring network is established in the Lilla Edet municipality in the southwest of Sweden to investigate possible landslides. We optimised the existing monitoring network by considering all quality criteria, i.e. precision, reliability and cost to enable the network for detecting 5 mm displacement at the net points. The different optimisation models are performed on the network by assuming single baseline observations in each measurement session. A decrease of 17% in the number of observed baselines is yielded by the multi-objective model. The observation plan with fewer baselines saves cost, time and effort on the project, while it provides the demanded quality requirements. The Lilla Edet monitoring network is also used to investigate the idea, where we assume more precise instruments in the second of two sequential epochs. In this study, we use a single-objective model of precision, and constrained it to reliability. The precision criterion is defined such that it provides the sensitivity of the network in detecting displacements and has a better variance-covariance matrix than at the first epoch. As the observations are GPS baselines, we assumed longer observation time in the second epoch to obtain higher precision. The results show that improving the observation precision in the second epoch yields an observation plan with less number of baselines in that epoch. In other words, separate observation plans with different configurations are designed for the monitoring network, considering better observation precision for the latter epoch.QC 20150603Forma

Optimization of Lilla Edet Land Slide GPS Monitoring Network

QC 20180604Project DNR 245-2012-356‎, Forma

Optimal Design in Geodetic GNSS-based Networks

An optimal design of a geodetic network helps the surveying engineers maximise the efficiency of the network. A number of pre-defined quality requirements, i.e. precision, reliability, and cost, of the network are fulfilled by performing an optimisation procedure. Today, this is almost always accomplished by implementing analytical solutions, where the human intervention in the process cycle is limited to defining the requirements. Nevertheless, a trial and error method can be beneficial to some applications. In order to analytically solve an optimisation problem, it can be classified to different orders, where an optimal datum, configuration, and optimal observation weights can be sought such that the precision, reliability and cost criteria are satisfied. In this thesis, which is a compilation of six peer-reviewed papers, we optimised and redesigned a number of GNSS-based monitoring networks in Sweden by developing new methodologies. In addition, optimal design and efficiency of total station establishment with RTK-GNSS is investigated in this research. Sensitivity of a network in detecting displacements is of importance for monitoring purposes. In the first paper, a precision criterion was defined to enable a GNSS-based monitoring network to detect 5 mm displacements at each network point. Developing an optimisation model by considering this precision criterion, reliability and cost yielded a decrease of 17% in the number of observed single baselines implying a reliable and precise network at lower cost. The second paper concerned a case, where the precision of observations could be improved in forthcoming measurements. Thus a new precision criterion was developed to consider this assumption. A significant change was seen in the optimised design of the network for subsequent measurements. As yet, the weight of single baselines was subject to optimisation, while in the third paper, the effect of mathematical correlations between GNSS baselines was considered in the optimisation. Hence, the sessions of observations, including more than two receivers, were optimised. Four out of ten sessions with three simultaneous operating receivers were eliminated in a monitoring network with designed displacement detection of 5 mm. The sixth paper was the last one dealing with optimisation of GNSS networks. The area of interest was divided into a number of three-dimensional elements and the precision of deformation parameters was used in developing a precision criterion. This criterion enabled the network to detect displacements of 3 mm at each point. A total station can be set up in the field by different methods, e.g. free station or setup over a known point. A real-time updated free station method uses RTK-GNSS to determine the coordinates and orientation of a total station. The efficiency of this method in height determination was investigated in the fourth paper. The research produced promising results suggesting using the method as an alternative to traditional levelling under some conditions. Moreover, an optimal location for the total station in free station establishment was studied in the fifth paper. It was numerically shown that the height component has no significant effect on the optimal localisation.QC 2080115</p