The increasingly urbanized world has created various problems of environment, climate, consumption of resources, and public health, which are closely linked to the side-effects of urbanization such as sprawl, congestion, housing affordability and loss of open space. Fundamental to the urban problems are two separate yet related issues: urban structure and urban dynamics. The chapters collected in this book present an excellent profile of the current state of geospatial analysis and modelling, and demonstrate how these approaches can contribute to the study of various urban issues. The book addresses key themes including new ways of capturing data digitally at the individual level, the development of systems based around networks, the notion of linking hierarchy to networks to morphology as in complexity theory, and the development of new ways of integrating diverse urban processes through simulation paying careful attention to the basic econometric and statistical principles of spatial analysis.

Research interests in the studies of complex systems have been booming in many disciplines for the last decade. As the nature of geographic environment is a complex system, researches in this field are anticipated. In particular, the urban street networks in the Geographic Information System (GIS) as complex networks are brought forth for the thesis study. Meanwhile, identifying the scale-free property, which is represented as the power law distribution from a mathematical perspective, is a hot topic in the studies of complex systems. Many previous studies estimated the power law distributions with graphic method, which used linear regression method to identify the exponent value and estimate the quality that the power law fits to the empirical data. However, such strategy is considered to cause inaccurate results and lead to biased judgments. Whereas, the Maximum Likelihood Estimation (MLE) and the Goodness of fit test based on Kolmogorov-Smironv (KS) statistics will provide more solid and trustable results for the estimations. Therefore, this thesis addresses these updated methods exploring the topological patterns of urban street networks from an analytical perspective, which is estimating the power law distributions for the connectivity degree and length of the urban streets. Simultaneously, this thesis explores the street networks from a visual perspective as well. The visual perspective adopts the large network visualization tool (LaNet-vi), which is developed based on the k-core decomposition algorithm, to analyze the cores of the urban street networks. By retrieving the spatial information of the networks from GIS, it actually enables us to see how the urban street networks decomposed topologically and spatially. In particular, the 40 US urban street networks are reformed as natural street networks by using three "natural street" models.

The results from analytical perspective show that the 80/20 principle still exists for both the street connectivity degree and length qualitatively, which means around 20% natural streets in each network have a connectivity degree or length value above the average level, while the 80% ones are below the average. Moreover, the quantitative analysis revealed the fact that most of the distributions from the street connectivity degree or length of the 40 natural street networks follow a power law distribution with an exponential cut-off. Some of the rest cases are verified to have power law distributions and some extreme cases are still unclear for identifying which distribution form to fit. The comparisons are made to the power law statement from previous study which used the linear regression method. Moreover, the visual perspective not only provides us the chance to see the inner structures about the hierarchies and cores of the natural street networks topologically and spatially, but also serves as a reflection for the analytical perspective. Such relationships are discussed and the possibility of combining these two aspects are pointed out. In addition, the future work is also proposed for making better studies in this field.

The emerging techniques of mobile GIS applications, its abilities and its implied limitations ofinternet connections is the main subject in this study. Many of the operations that mobile devicesuse are dependent on mobile internet connectivity. Therefore the potential for it in well connectedareas is great but how would they function in less connected areas? Mobile GIS, which is todaymostly used in devices as smart phones and tablets, has internet connectivity for uploading anddownloading files and other data. Mobile GIS is also dependent on location-based services thatenable the device to get information or take action from the current location of the device. Thisresearch examines the potential usage of mobile GIS in conjunction with the bandwidth of wirelesstechnologies. It is important to study this issue to see if mobile applications can perform upload anddownload tasks within reasonable time in poor mobile coverage. To test the possibilities of mobileGIS in rural areas a test environment is set up in a mobile GIS application for septic tanks. Thetesting is performed by uploading and downloading data with real GIS actions from pre-selectedlocations that have low mobile coverage. The study is comparing the measurements with a scale ofacceptable time for download and upload. The result for registering (uploading) a new point inmobile GIS with three small images is that it requires at least 330 Kbit/s connection to transfer thedata within acceptable time. The results for uploading data without images and downloading giveseven better results and are not as dependent on a good connection for transferring within acceptabletime. The conclusion is that mobile gis applications are able to run within acceptable time measuresin rural areas. The results and other sources were used to make general guidelines for mobile GISapplications for use in rural areas.

Many surveying engineering applications require the knowledge of the orientation parameters of instruments. One can use inertial measurement units (IMUs) to determine that. IMUs are combinations of several inertial sensors and comprise at least an accelerometer and a gyroscope. Therefore, they can detect accelerations and angular rates in a three-dimensional space. As micro-electro-mechanical systems, the sensors are increasingly getting smaller and lighter, but without being reduced in their accuracy. The smaller size facilitates diverse placing of the sensors, which allows a variety of uses. Moreover, several low-cost IMUs have been devised since the development of single-board computers.

The main objectives of this work are to determine tilts using a low-cost IMU, and the accuracy of the sensor. Furthermore, it studies general IMU applications in surveying engineering, and examines whether low-cost versions are applicable.

To fulfil the objectives, the study was based on a selected low-cost IMU. Two programs were developed as part of this work. One was to control the sensor and the other, to calculate the tilts and analyse the data. The IMU was mounted in front of the objective of the total station and aligned in different reference orientations. All measurements were performed under controlled thermal conditions. Thereby, it was ensured that no falsifications could appear due to ambient temperature influences. As a first step, the sensor calibration process was completed. It helped determine the signal offset parameter and their time-dependent change. The calibration was done using two present methods, the six-position and the multi-position methods. The calibrated IMU helped determine the tilts. This was done in the case of the accelerometer via trigonometric functions, which allowed an absolute orientation statement. In contrast, the gyroscope provided relative orientation with the multiplication of the detected angular variance and the time that passed. After that, a target-actual comparison with the reference information of the total station helped determine the external accuracy of the tilt from the IMU. Moreover, multiple measurements could give a statement of the internal accuracy. Finally, the Kalman Filter was added to smooth out the sensor data and combine it in real-time.

The calibration methods showed similar results, and it was striking that the sensors did not show the expected drifts. The reason could be related to a pre-calibration by the manufacturer. On the one hand, the used IMU showed differences in the total station alignments in the order of 0.798° for the accelerometer and up to 4.3° for the gyroscope with the calibrated data. On the other, the differences in repeated measurements were at 0.024° for the accelerometer and 0.5° for the gyroscope.

It was figured out different possible applications of IMUs in surveying engineering. Among other things, these included orientation monitoring of sensor platforms or the determination of the external orientation of unmanned aerial systems. For these applications, the usability depends on the achievable accuracy. In the case of the IMU chosen in this study, the proven accuracy is too inaccurate for these applications.

There is a need for further investigation because the use of another sensor type may rectify the insufficient accuracy problem. Moreover, to achieve better accuracies and to make it possible to use the IMU in different ambient temperatures, the temperature influence must be determined.

Recently, there has been an increasing interest in looking at urban environment as a complex system. More and more researchers are paying attention to the study of the configuration of urban space as well as human social activities within it. It has been found that correlation exists between the morphological properties of urban street network and observed human social movement patterns. This correlation implies that the influence of urban configurations on human social movements is no longer only revealed from the sense of metric distance, but also revealed from topological and geometrical perspectives. Metric distances, topological relationships and angular changes between streets should be considered when applying space syntax analysis to an urban street network. This thesis is mainly focused on the comparison among metric, topological and angular analyses based on three kinds of urban street representation models: natural streets, axial lines and axial segments. Four study areas (London, Paris, Manhattan and San Francisco) were picked up for empirical study. In the study, space syntax measures were calculated for different combinations of analytical methods and street models. These theoretical space syntax accessibility measures (connectivity, integration and choice) were correlated to the corresponding practical human movement to evaluate the correlations. Then the correlation results were compared in terms of analytical methods and street representation models respectively. In the end, the comparison of results show that (1) natural-street based model is the optimal street model for carrying out space syntax analysis followed by axial lines and axial segments; (2) angular analysis and topological analysis are more advanced than metric analysis; and (3) connectivity, integration and local integration (two-step) are more suitable for predicting human movements in space syntax. Furthermore, it can be hypothesized that topological analysis method with natural-street based model is the best combination for the prediction of human movements in space syntax, for the integration of topological and geometrical thinking.

During the urbanization process, vehicles quantity increase with expansion in population. Under this situation, bus transportation system also suffers from bus delay. Bus delay could be caused by a series of factors, for instance, overload passengers, traffic jam, traffic accident and other unpredictable situations. Therefore, choosing crucial elements to efficiently evaluate bus delay is a complex problem in bus delay researches and operation management. The thesis propose an approach to evaluate and explain bus delay by two elements: traffic congestion and passengers’ waiting time. Those two elements would represent the action of external and internal factors on bus operation. This approach could be adaptive to explain the reasons for bus delays, thus to help the optimization of bus lines and give useful information for decision making of transportation company. To achieve the research aim, a GIS-T database was created by combining the GIS database and TIS database. Spatial data as well as attribute data are combined in the database to represent the crucial information for bus delay. Based on GIS-T the database, the impact of traffic congestion and passengers’ waiting time was calculated using the bus line simulation. By implementing the above steps, the main cause of bus delay was studied. A case study application of this method is narrated; focusing on optimize the bus system of Guiyang city, South China. Different methods are used to find out the problem of system and the reason for delay. Moreover, optimization suggestion is proposed according to result. Compared with other methods, the two-factor method has the advantage of locating the reason of delay for each station. The time performance is not superior to other methods. By comparing the situation of adjacent station, the proportion of traffic congestion and overload passenger in bus delay was determined. The two-factor method is applicable for other transit system in different cities which has similar structure as Guiyang. However, for cities with other structure, a feasibility should be made to select an appropriate model.