Data Science, Data Visualization, and Digital Twins

Real-time, web-based, and interactive visualisations are proven to be outstanding methodologies and tools in numerous fields when knowledge in sophisticated data science and visualisation techniques is available. The rationale for this is because modern data science analytical approaches like machine/deep learning or artificial intelligence, as well as digital twinning, promise to give data insights, enable informed decision-making, and facilitate rich interactions among stakeholders.The benefits of data visualisation, data science, and digital twinning technologies motivate this book, which exhibits and presents numerous developed and advanced data science and visualisation approaches. Chapters cover such topics as deep learning techniques, web and dashboard-based visualisations during the COVID pandemic, 3D modelling of trees for mobile communications, digital twinning in the mining industry, data science libraries, and potential areas of future data science development

Distributed runoff simulation of extreme monsoon rainstorms in Malaysia using TREX

2013 Summer.Includes bibliographical references.Malaysia has a monsoon climate and most areas receive more than 2,500 mm of rainfall every year. For the past five years, the frequency and magnitude of floods in Malaysia have been relatively high. Floods have become the most significant type of natural disaster for Malaysia in terms of the population affected, financial losses and adverse socio-economic impact. This study uses the distributed two-dimensional TREX model to simulate infiltration, overland runoff and channel flow during extreme rainfall events. The main objective is to calibrate the distributed hydrological model to simulate monsoon floods. The second objective is to determine the affected flooding area under different rainfall events (i.e., large and extreme rainfall events). Large rainfall events cover return periods ranging from two to one hundred years. Extreme rainfall events include both the PMP and the world's largest rainfall events. The third objective is to examine the effect of rainfall duration on the magnitude of peak flood discharge as a function of watershed size. Finally, determine and produce graphs for the relationships between peak specific-discharge and watershed sizes. Three different sizes of watersheds are considered: Lui (small - 68 km2), Semenyih (medium - 236 km2) and Kota Tinggi (large - 1,635 km2). Generally, the topography of these watersheds is steep, except for the large watershed. The TREX model calibration and validation have been done using field measurements during several storm events. The performance of the model to find peak discharge, time to peak, and volume has been tested using three metrics: Relative Percentage Difference (RPD), Percentage Bias (PBIAS) and Nash-Sutcliffe Efficiency Coefficient (NSEC)) comparison. On average, the model performance was good for small (RPD - 7%, PBIAS - 14% and NSEC - 0.4) and medium watersheds (RPD - 14%, PBIAS - 28% and NSEC - 0.7). The RPD (4%), PBIAS (2%) and NSEC (0.8) for the large watershed shows that the model performance was very good. The spatial and temporal runoff distribution for overland and channel flows were successfully visualized in 3D. Both small and medium watersheds were not flooded by large events, except in the main channel. The flow depth reached 1.72 m in the valley of the small watershed only during extreme events. It was estimated that about 24% (±10%) and 83% (±5%) of the valley area exceed a flow depth of 1.72 m during PMP and world's largest events, respectively. For the medium watershed, the valley area was covered with water in excess of 4.49 m under the world's largest events. The visualization tool shows that the valley areas are prone to severe flooding (in excess of 4.49 m of flow depth) under this event (±5%). For the large watershed, the low land areas (i.e., along the tributaries and channels) are more likely to be flooded during large and extreme events. The water depths covered more than 2.8 m in these areas. The maximum estimated discharges (MED) for large rainfall events were highest for rainfall durations of 3 to 5 hours on small watersheds. However, the MED values for medium watersheds were obtained for rainfall durations between 5 and 12 hours. The MED values for extreme rainfall events were highest for rainfall durations between 10 and 13 hours on both watersheds. For the large watershed, the MED values of large and extreme events were obtained for a rainfall duration of 168 hour. The main conclusions of this study are: (1) rainfall intensity (i.e., hourly data) is one of the main factors that contribute to the magnitude of flooding on small and medium watersheds (watershed size less than 1,000 km2). The flooding events on large watersheds (watershed size more than 1,000 km2) result from longer rainfall durations (i.e., multi-day rainstorms), (2) for all size watersheds, the average magnitude of peak discharge for the PMP and the world's largest events are approximately 5 and 12 times larger than a 100-year rainfall event, (3) the peak specific-discharge (cms/km2) decreased as the watershed size (km2) increased, and (4) the runoff coefficient C increased significantly (i.e., a factor of three) from the 100-year rainfall event to the PMP and the world's largest events for all watersheds (CPMP,CWGR > 0.7)

How does your viewing perspective matter for decision-making with flood risk maps?*

The globally increasing frequency of flood events highlights the importance of effective flood risk communication. The influence of the viewing perspective of mapped flood events on human risk perception has not yet been a research focus of the geovisualization community. This empirical study aims to fill this gap by investigating how the viewing perspective of flood risk maps, that is, 2D orthographic vs. 2.5D oblique views, influence human flood risk perception and decision-making. Results on how viewing perspective might influence measured risk perception are in line with prior inconclusive research on the utility and usability of adding a third viewing dimension on static maps. Unlike prior research would have suggested, we find that the individual risk attitude of our participants had no direct influence on their risk ratings in the context of this study. With additional empirical evidence on how static 2D and oblique 2.5D hazard maps might influence the public’s risk perception and decision-making, we hope to further inform policy and decision makers on the critical importance of well-designed cartographic displays for effective and efficient hazard and risk communication. We also provide an open-source code repository for making reproducible experiments with our static maps

3D simulation in flooding Providence

This thesis use 3d data visualization to provide the scenarios of how global climate changes will influence people’s life if we don’t take actions as soon as possible, which provide non-professional people an easy way to understand the urban issues and engage them into the environmental protection. My proposal is to visualize the flooding issues in Providence by using kinds of simulation tools, including 3d model, augmented reality(AR), animation in order arise the awareness of climate change and the significance of human’s actions to protect the living environments. These simulations also provide the support for the designers and policy-makers to adjust management strategies when they are thinking about the long-term urban planning

Visualization of uncertainty in natural hazards assessments using an interactive cartographic information system

Natural hazard assessments are always subject to uncertainties due to missing knowledge about the complexity of hazardous processes as well as their natural variability. Decision-makers in the field of natural hazard management need to understand the concept, components, sources, and implications of existing uncertainties in order to reach informed and transparent decisions. Until now, however, only few hazard maps include uncertainty visualizations which would be much needed for an enhanced communication among experts and decision-makers in order to make informed decisions possible. In this paper, an analysis of how uncertainty is currently treated and communicated by Swiss natural hazards experts is presented. The conducted expert survey confirmed that the communication of uncertainty has to be enhanced, possibly with the help of uncertainty visualizations. However, in order to visualize the spatial characteristics of uncertainty, existing uncertainties need to be quantified. This challenge is addressed by the exemplary simulation of a snow avalanche event using a deterministic model and quantified uncertainties with a sensitivity analysis. Suitable visualization methods for the resulting spatial variability of the uncertainties are suggested, and the advantages and disadvantages of their implementation in an interactive cartographic information system are discusse

Virtual geographic environments in socio-environmental modeling: a fancy distraction or a key to communication?

Modeling and simulation are recognized as effective tools for management and decision support across various disciplines; however, poor communication of results to the end users is a major obstacle for properly using and understanding model output. Visualizations can play an essential role in making modeling results accessible for management and decision-making. Virtual reality (VR) and virtual geographic environments (VGEs) are popular and potentially very rewarding ways to visualize socio-environmental models. However, there is a fundamental conflict between abstraction and realism: models are goal-driven, and created to simplify reality and to focus on certain crucial aspects of the system; VR, in the meanwhile, by definition, attempts to replicate reality as closely as possible. This elevated realism may add to the complexity curse in modeling, and the message might be diluted by too many (background) details. This is also connected to information overload and cognitive load. Moreover, modeling is always associated with the treatment of uncertainty–something difficult to present in VR. In this paper, we examine the use of VR and, specifically, VGEs in socio-environmental modeling, and discuss how VGEs and simulation modeling can be married in a mutually beneficial way that makes VGEs more effective for users, while enhancing simulation models

Climate adaptation for coastal zones : benefits and tradeoffs in a southern Swedish case

Climate change in coastal areas implies sea level rise and more frequent extreme weather events causing floods. Floods cause property damage and risk to people as the coastal zones many times are built and developed environments. Besides from this, the coastal zones have high ecological values connected to the coastal dynamics. ‘Coastal squeeze ‘ occurs when ecological values are obstructed to migrate inland by built environments, currently a common situation. In Bunkeflostrand and Klagshamn in southern Sweden, coastal squeeze is a fact, and as sea levels rise, much of the ecological values could be lost by year 2100. Conventional and traditional methods to control water are being questioned, the integration of natural features is gaining attention and innovation is advocated in the aspiration to a sustainable development for our common future. Following reading will take you through the outlook of coastal planning and management, and display international approaches to address climate adaptation for coastal zones. Thereafter, some examples will be applied to the Bunkeflostrand and Klagshamn context with the ambition to identify benefits and tradeoffs from the sustainability aspect. The results show that conventional methods may not always be the worst solution, and that natural features may not be the better - the combination of various structures and methods may constitute a sequential line of defense. Other results show that ecological benefits many times imply socio-economic tradeoffs, and vice versa. Sometimes an ecological long-term benefit even implies ecological tradeoffs. The results also show that sustainability may conflict with the Sustainable Development Goals, depending on the focus. To assess the best possible solutions, climate adaptation for coastal zones require multidisciplinary collaboration and investigations between agencies, the state, municipalities, planners and designers

The integration of storm water flooding and thermal stress potential in Tainan (Taiwan) and Groningen (Netherlands)

Stormwater flooding and thermal stresses of citizens are two important phenomena for most of the dense urban area. Due to the climate change, these two phenomena will occur more frequently and cause serious problems. Therefore, the sectors for public health and disaster management should be able to assess the vulnerability to stormwater flooding and thermal stress. To achieve this goal, two cities in different climate regions and with different urban context have been selected as the pilot areas, i.eY., Tainan, Taiwan and Groningen, Netherlands. Stormwater flooding and thermal stress maps will be produced for both cities for further comparison. The flooding map indicates vulnerable low lying areas, where the thermal stress map indicates high Physiological Equivalent Temperature (PET) values (thermal comfort) in open areas without shading. The combined map indicates the problem areas of flooding and thermal stress and can be used by urban planners and other stakeholders to improve the living environment

Design of a System for Multiple Route Selection in the Presence of Flooding

Safe navigation during flooding is integral in minimizing loss of life. Navigation has throughout literature been treated as a search problem with the aim of optimizing certain impedance. The earliest study of path finding started in the late 1800s forming the basis of depth-first search techniques. This was followed by the introduction of a lot of popular algorithms including Dijkstra’s, A*and Bellman-Ford. Recently, the study of path planning – for road networks based on heuristics for dynamic or partially known environments has gained a lot of attention. In this thesis, we present a unique approach to finding multiple competitive paths between two locations on a street network that also considers road flooding. The key idea is to find a cost optimal solution for two locations using Dijkstra’s algorithm. We then penalize the found solution by increasing the traversal cost of one segment or the whole path, forcing the search algorithm to find alternative solutions. This framework is developed for the street network the City of Houston leveraging the capabilities of ArcGIS Desktop and Python scripting. The proposed algorithm is evaluated for quality and safety of resultant routes. This is done by comparing route lengths, elevations, widths, percentage of duplicate road segments, maximum speed limits of the obtained paths. We also conducted an experimental evaluation that shows an elevated sensitivity towards these factors as compared to the standard shortest path algorithms.Computer Science, Department o