Geo-based Information Visualizations (GIV) allow people to analyze data points based on their related geographic locations. This approach is usually adopted where a large scale geo-referenced dataset is present and users are trying to find a way to examine hidden patterns within this data. One of the emerging trends in GIV is to visualize social media data to show how information flows between users of popular social networking sites. Due to its public nature and the large number of users, most of the visualizations in this area rely on conversational data from Twitter (Twitter.com). In this thesis, we design and implement a web-based interactive GIV system, AcademiaMap-GIV, to visualize online conversations among scholars on Twitter. A formal exploratory user study was also conducted on the target users. The study results demonstrated that most of the study respondents found the features of AcademiaMap-GIV effective in regards to visualizing information of their interests.

Geo-data visualization has always been an important tool in the urban planning process. Recent trends in geo-information technology are, however, offering additional opportunities for the development of new visualization tools. In parallel, developments have also taken place in the field of urban planning, which has evolved from the rational planning model towards a more strategic planning process with a greater emphasis on collaboration and inclusiveness. This study investigates how an innovative geo-data visualisation tool can be used to develop more inclusive and participatory planning processes, and it tests this approach by means of a case study in Tripoli, Lebanon. The study compared two geo-data visualization techniques regarding their potential for an increased involvement of different types of stakeholders in the urban planning processes: The first technique employed coloured printed transparency maps of the present land-use and the 2000-2020 Master Plan, both geo-referenced to a mosaic of QuickBird satellite imagery used to assist the participant’s orientation. The second technique was the Lenticular Foil Display (LFD) using the so-called flip effect, also based on the geo-coding of the same three “layers”. By tilting this product the observer was easily able to interpret the changes between present and planned state. The LFD technology is particularly useful for true-3D (auto-stereoscopic) viewing. Statistical evaluations of questionnaires concerning sociological and perception-scientific aspects revealed interesting details regarding the role of the new visualization method in the participatory city planning process. The result of the interviews revealed that all stakeholders were readily able to participate in the planning process and to contribute their ideas by sketch-map drawing and writing, using the LFD technology. Regarding the possibilities to stimulate the participation of different stakeholders in the planning process, the LFD was found to be more effective than the conventional approach using transparencies overlaid over orthophotos. Non-experts, in particular, preferred the LFD technology to the transparent overlays which were, however, the preferred approach for the professionals and experts familiar with Master Plan map-reading. One conclusion of the present study is that an efficient participatory urban-planning process should explicitly consider the level of map-reading skills of the stakeholders. Geo-data visualization products like the Multi-Flip-LFDs and other innovative approaches offer possibilities to improve stakeholder participation. The monograph closes by making concrete suggestions for further research into the development and optimization of LFDs.

Geo-data visualization has always been an important tool in the urban planning process. Recent trends in geo-information technology are, however, offering additional opportunities for the development of new visualization tools. In parallel, developments have also taken place in the field of urban planning, which has evolved from the rational planning model towards a more strategic planning process with a greater emphasis on collaboration and inclusiveness. This study investigates how an innovative geo-data visualisation tool can be used to develop more inclusive and participatory planning processes, and it tests this approach by means of a case study in Tripoli, Lebanon. The study compared two geo-data visualization techniques regarding their potential for an increased involvement of different types of stakeholders in the urban planning processes: The first technique employed coloured printed transparency maps of the present land-use and the 2000-2020 Master Plan, both geo-referenced to a mosaic of QuickBird satellite imagery used to assist the participant’s orientation. The second technique was the Lenticular Foil Display (LFD) using the so-called flip effect, also based on the geo-coding of the same three “layers”. By tilting this product the observer was easily able to interpret the changes between present and planned state. The LFD technology is particularly useful for true-3D (auto-stereoscopic) viewing. Statistical evaluations of questionnaires concerning sociological and perception-scientific aspects revealed interesting details regarding the role of the new visualization method in the participatory city planning process. The result of the interviews revealed that all stakeholders were readily able to participate in the planning process and to contribute their ideas by sketch-map drawing and writing, using the LFD technology. Regarding the possibilities to stimulate the participation of different stakeholders in the planning process, the LFD was found to be more effective than the conventional approach using transparencies overlaid over orthophotos. Non-experts, in particular, preferred the LFD technology to the transparent overlays which were, however, the preferred approach for the professionals and experts familiar with Master Plan map-reading. One conclusion of the present study is that an efficient participatory urban-planning process should explicitly consider the level of map-reading skills of the stakeholders. Geo-data visualization products like the Multi-Flip-LFDs and other innovative approaches offer possibilities to improve stakeholder participation. The monograph closes by making concrete suggestions for further research into the development and optimization of LFDs.

Ensemble simulation is a commonly used technique in operational forecasting of weather and floods. Multi-member ensemble output is usually large, multivariate, and challenging to interpret interactively. Forecast meteorologists and hydrologists are interested in understanding the uncertainties associated with the simulation; specifically variability between the ensemble members. The visualization of ensemble members is currently accomplished through spaghetti plots or hydrographs. To improve visualization techniques and tools for forecasters, we conducted a userstudy to evaluate the effectiveness of existing uncertainty visualization techniques on 1D and 2D synthetic datasets. We designed an uncertainty evaluation framework to enable easier design of such studies for scientific visualization. The techniques evaluated are errorbars, scaled size of glyphs, color-mapping on glyphs, and color-mapping of uncertainty on the data surface. Although we did not find a consistent order among the four techniques for all tasks, we found that the efficiency of techniques used highly depended on the tasks being performed. Errorbars consistently underperformed throughout the experiment. Scaling the size of glyphs and color-mapping of the surface performed reasonably well. With results from the user-study, we iteratively developed a tool named ‘Noodles’ to interactively explore the ensemble uncertainty in weather simulations. Uncertainty was quantified using standard deviation, inter-quartile range, width of the 95% confidence interval, and by bootstrapping the data. A coordinated view of ribbon and glyph-based uncertainty visualization, spaghetti plots, and data transect plots was provided to two meteorologists for expert evaluation. They found it useful in assessing uncertainty in the data, especially in finding outliers and avoiding the parametrizations leading to these outliers. Additionally, they could identify spatial regions with high uncertainty thereby determining poorly simulated storm environments and deriving physical interpretation of these model issues. We also describe uncertainty visualization capabilities developed for a tool named ‘FloodViz’ for visualization and analysis of flood simulation ensembles. Simple member and trend plots and composited inundation maps with uncertainty are described along with different types of glyph based uncertainty representations. We also provide feedback from a hydrologist using various features of the tool from an operational perspective.

Climate analysts use Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations to make sense of models performance in predicting extreme events such as heavy precipitation. Similarly, weather analysts use numerical weather prediction models (NWP) to simulate weather conditions either by perturbing initial conditions or by changing multiple input parameterization schemes, e.g., cumulus and microphysics schemes. These simulations are used in operational weather forecasting and for studying the role of parameterization schemes in synoptic weather events like storms. This work addresses the need for visualizing the differences in both CMIP5 and NWP model output. This work proposes three glyph designs used for communicating CMIP5 model error. It also describes Ensemble Visual eXplorer tool that provides multiple ways of visualizing NWP model output and the related input parameter space. The proposed interactive dendrogram provides an effective way to relate multiple input parameterization schemes with spatial characteristics of model uncertainty features. The glyphs that were designed to communicate CMIP5 model error are extended to encode both parameterization schemes and graduated uncertainty, to provide related insights at specific locations such as storm center and the areas surrounding it. The work analyzes different ways of using glyphs to represent parametric uncertainty using visual variables such as color and size, in conjunction with Gestalt visual properties. It demonstrates the use of visual analytics in resolving some of the issues such as visual scalability. As part of this dissertation, we evaluated three glyph designs using average precipitation rate predicted by CMIP5 simulations, and Ensemble Visual eXplorer tool using WRF 1999 March 4th, North American storm track dataset.

Landscape is a heterogeneous collection of visibly distinct features of various elements of land and its various forms on the earth surface. Its pattern is subjected to disturbances and undergo rapid alterations in its grain sizes. The evolving patterns of landscape define and decide various parameters for the planning and management of resources. These dynamic systems possess both spatial and temporal complexity. Exploitation of natural resources and drastic land cover changes have given rise to significant impacts on ecosystem structure and dynamics. The functional abilities (bio-geo chemical cycling, hydrological cycling, etc.) of the landscape are basically dependent on the structure and its complexity. This necessitates inventorying, mapping and modeling of landscape dynamics. Patterns and scale are central issues that are essential to understand complex interactions and driving forces. Large scale changes have been rapid and occurring since industrialization and urbanisation in the last century. The exponential growth of cities has been noticed since the industrial revolution and as transport sector changed the mobility of the masses drastically. Urbanisation interacts with the neighboring landscape structures in the form of commuter’s flow, pollution, obtaining food grain, which create dispersed growth or sprawl in between the metropolis and the semi urban area, and these areas are often devoid of basic amenities due to lack of prior information and necessitates predictions of such growth while planning, policy and decision-making. Planning determines appropriate future action through a sequence of choices that tend to occur. To understand uncertain conditions, planners and city managers need vital comprehensive information about the temporally evolving landscape and try to predict the future, for effective decisions. The quality of planning and its decision processes can be substantially improved when the required information is handled appropriately and efficiently. This explains that an effective planning requires descriptive, predictive, and prescriptive information inputs for sustainable resource management. Therefore, modeling future trends becomes a necessary part of planning. Urban growth models help in modelling future trends that can be an efficient and effective support tool. In recent years, the confluence of developments in Remote sensing, Geographic Information System and Image processing, Computational Urban Growth and Urban Land-use Modeling has made possible in timely provision of information inputs to planners. In the context of Indian cities, this research attempts to study the patterns of urban growth and the rate of change of that growth using various techniques such as Land use, land cover models, Gradient and zonal approach, spatial metrics and urban growth models. Indian cities are divided based on population into various categories. These categories were considered separately and dealt with sample number of cities. This works helps in understanding the change pattern of rapidly urbanising, moderately urbanising and rural landscape is accomplished using various metrics and gradients. The research, is mainly aimed at understanding the pattern of growth and device computational urban growth model using well known techniques and develop a suitable technique in order to understand the context of agents and their role in modelling future urban growth and estimate the rate of loss of other land use categories due to urban growth. Satellite images for different time series was used to study the pattern of urban growth in the study areas. Well know indicators were derived from the data. This was further used to model one of the rapidly urbanising cities based on scenario no agents/factor and with agents of growth using city development plans and in absence of it. This adaptation to Indian context will help in gaining better understanding of the urban growth system in various levels of cities classified, and thus help in providing inputs and specific information of future growth for urban planners and city managers to provide better basic amenities and for sustainable growth of cities. The objective of the proposed research is to understand and model the spatio temporal patterns of landscape dynamics. This involves i. Analysis of Landscape dynamics using multi-resolution (spatial, temporal and spectral) data. ii. Quantifying landscape dynamics using landscape metrics and associated landscape parameters. iii. Modeling and geo-visualisation of landscape dynamics in rapidly urbanizing, moderately urbanising and rural landscape using these parameters. iv. Model the landscape dynamics using soft computing techniques. The thesis consists of nine chapters. Chapter 1 introduces the basic concepts such as landscape, landscape dynamics, use of spatio-temporal data to monitor landscape dynamics, geo-visualisation of landscape dynamics, research gaps and motivation for taking up the research in this domain. Chapter 2 presents the study region, which are broadly grouped as (i) Rapidly urbanizing landscapes (corresponding to Tier I Cities in India), (ii) Moderately urbanizing landscapes (Tier II cities, chosen select Tier II cities in Karnataka), and (iii) Landscape experiencing minimal urbanisation (rural landscape). Chapter 3 discusses the material and method adopted for understanding landscape dynamics and geo-visualisation of landscape dynamics Chapter 4 presents the landscape dynamics in rapidly urbanizing landscape (Bangalore) in India. Spatial pattern analyses are done through metrics using zonal- gradient approach. Chapter 5 analyses the environmental sustainability aspects considering one case study of rapidly urbanizing landscape – Bangalore Chapter 6 discusses urbanisation process and patterns across macro cities in India. Similarly Chapter 7 discusses the urbanisation pattern in Tier II cities (in Karnataka) and Chapter 8 presents the rural landscape dynamics Geo-visualisation of a rapidly urbanizing landscape (Bangalore) through techniques such as Cellular Automata – Markov Chain, land change modeler (LCM), Geographical land use change modeler (GEOMOD), Markov Cellular automata based process of deriving agent’s behavior using Fuzziness in the dataset and Analytical Hierarchal process. Further research in progress in this domain focusses on integration of various agents and evaluation of proposed development plans and likely scenario of integrating land use with mobility. Keyword: landscape, landscape dynamics, urbanisation, urban growth, urban sprawl, urban footprint, modelling, geo-visualisation