Photorealistic visualisation of urban greening in a low-cost high- density housing settlement.

Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2005.Apartheid housing policies of the pre-1994 South African government, and the low-cost highdensity housing programmes of the post-1994 government, has given rise to numerous urban environmental problems, some of which could be addressed in a cost-effective and sustainable manner through urban greening, while simultaneously promoting biodiversity. Public participation in the planning of urban greening has been identified as being of vital importance, without which urban greening projects run a high, and expensive, risk of failure. Previous studies indicate that the greening priorities of residents in low-cost high-density housing settlements may differ considerably from those of managers and experts tasked with the protection and extension of the natural environment resource base. A system of participatory decision support is therefore required to reconcile the greening requirements of the community, and the ecological benefits of biodiversity. If language, literacy, map literacy and numeracy difficulties are to be avoided, and a sense of place or belonging is to be invoked, such a participatory decision support system should, ideally, be visually based, and capable of generating realistic eye-level depictions of the urban landscape. New computer-based landscape visualisation applications, which can directly utilise GIS, CAD and DEM data to produce detailed photo-realistic viewsheds, were deemed better suited to the task of visualising urban greening than existing GIS based mapping systems, CAD and traditional landscape visualisation methods. This dissertation examines the process of constructing a 3D computer model of the Mount Royal low-cost high-density housing settlement, situated in the eThekwini Municipality, KwaZulu-Natal, South Africa. Visualisations including terrain, natural features, indigenous vegetation, houses and roads were produced and submitted, with a questionnaire, to experts from different disciplines, Mount Royal residents and neighbors. Results from the expert survey indicate moderate support for visualisation in professional decision-making. However, both experts and residents expressed strong support for the accuracy and credibility ofthe visualisations, as well as for their potential in a participatory decision support system

Seeing the invisible: from imagined to virtual urban landscapes

Urban ecosystems consist of infrastructure features working together to provide services for inhabitants. Infrastructure functions akin to an ecosystem, having dynamic relationships and interdependencies. However, with age, urban infrastructure can deteriorate and stop functioning. Additional pressures on infrastructure include urbanizing populations and a changing climate that exposes vulnerabilities. To manage the urban infrastructure ecosystem in a modernizing world, urban planners need to integrate a coordinated management plan for these co-located and dependent infrastructure features. To implement such a management practice, an improved method for communicating how these infrastructure features interact is needed. This study aims to define urban infrastructure as a system, identify the systematic barriers preventing implementation of a more coordinated management model, and develop a virtual reality tool to provide visualization of the spatial system dynamics of urban infrastructure. Data was collected from a stakeholder workshop that highlighted a lack of appreciation for the system dynamics of urban infrastructure. An urban ecology VR model was created to highlight the interconnectedness of infrastructure features. VR proved to be useful for communicating spatial information to urban stakeholders about the complexities of infrastructure ecology and the interactions between infrastructure features.https://doi.org/10.1016/j.cities.2019.102559Published versio

Implementation of a virtual environment system based on geographical information system and environmental models

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.Includes bibliographical references (p. 162-165).by Chen-Hsiang Yeang.M.S

Modeling and Simulation in Engineering

This book provides an open platform to establish and share knowledge developed by scholars, scientists, and engineers from all over the world, about various applications of the modeling and simulation in the design process of products, in various engineering fields. The book consists of 12 chapters arranged in two sections (3D Modeling and Virtual Prototyping), reflecting the multidimensionality of applications related to modeling and simulation. Some of the most recent modeling and simulation techniques, as well as some of the most accurate and sophisticated software in treating complex systems, are applied. All the original contributions in this book are jointed by the basic principle of a successful modeling and simulation process: as complex as necessary, and as simple as possible. The idea is to manipulate the simplifying assumptions in a way that reduces the complexity of the model (in order to make a real-time simulation), but without altering the precision of the results

Establishing a LAN Network for Designing and Analyzing of Manufacturing Products

A thesis presented to the faculty of the College of Science & Technology at Morehead State University in partial fulfillment of the requirements for the Degree of Master of Science by Yuqiu You in Spring of 2002

Development of a Harvester Machine Simulator in Virtual Reality

Computer-aided design (CAD) software is used in the product design and development to design complex and detailed prototypes. It provides good assistance and solid data generation to designers and engineers. In order to remain competitive, industry is always seeking for higher process efficiency and product quality enhancement in the shortest period of time. Continuous research keeps going to make it possible. Virtual reality has been one of the research focus in the recent years. It is studied and applied to be used as an assistant tool in the product lifecyle management, particularly in facilitating the development phase. However, the implementation process from CAD to virtual reality remains a challenge due to time consumption and technology complexibility. In this work a real-time virtual reality harvester simulator was developed. The start point was a 3D harvester CAD model. It was used the CAD simulator AGX Momentum, a game engine Unity and the physics engine AGX Dynamics to create dynamics simulation, to design a virtual forest environment and to enable physical controllers interact with the model. With the capabilities of AGX Momentum, it was added dynamics motion directly in the CAD software, creating fast CAD simulations. A virtual scene was designed with Unity to simulate an environment and the immersion of the user on it with Oculus Rift device. The harvester model was imported to the Unity scene with AGX Dynamics. In the end it was obtained a real size virtual prototype, with the possibility of interacting and control it using physical controllers. The user can visualise the scene in real-time through a head mounted display, providing him the experience of a real machine operator. Driving the harvester in a simulated forest, allowed to test the model in a hypothetical real scenario. The process of implementing the CAD model in virtual reality used in this work, revealed to be efficient and intuitive. However, because it is a complex and large model, it was necessary to remove certain bodies (without dynamics effect) and reduce the number of contact points between components in order to balance the speed and performance of the simulator. Following the same method used in this work, Other CAD models can be imported to virtual reality and be dynamically simulated

Constructing a GIS-based 3D urban model using LiDAR and aerial photographs

Due to the increasing availability of high-resolution remotely sensed imagery and detailed terrain surface elevation models, urban planners and municipal managers can now model and visualize the urban space in three dimensions. The traditional approach to the representation of urban space is 2D planimetric maps with building footprints, facilities and road networks. Recently, a number of methods have been developed to represent true 3D urban models. Those include panoramic imaging, Virtual Reality Modeling Language (VRML), and Computer-aided Design (CAD). These methods focus on aesthetic representation, but they do not have sufficient spatial query and analytical capabilities. This research evaluates the conventional approaches to 3D urban models, and identifies their advantages and limitations; GIS functionalities have been combined with 3D urban visualization techniques to develop a GIS-based urban modeling method; The algorithms and techniques have been explored to derive urban objects and their attributes from airborne LiDAR and high-resolution imagery for constructing and visualizing 3D urban models; and 3D urban models for the Texas A&M University (TAMU) campus and downtown Houston have been implemented using the algorithms and techniques developed in this research. By adding close-range camera images and highresolution aerial photographs as the texture of urban objects, effect of photorealism visualization has been achieved for walk-through and fly-through animations. The Texas A&M University campus model and the downtown Houston model have been implemented to offer proof-of-concept, namely, to demonstrate the advantages of the GIS-based approach. These two prototype applications show that the GIS-based 3D urban modeling method, by coupling ArcGIS and MultiGen-Paradigm Site Builder 3D software, can realize the desired functionalities in georeferencing, geographical measurements, spatial query, spatial analysis, and numerical modeling in 3D visual environment

Autonomous 3D Urban and Complex Terrain Geometry Generation and Micro-Climate Modelling Using CFD and Deep Learning

Sustainable building design requires a clear understanding and realistic modelling of the complex interaction between climate and built environment to create safe and comfortable outdoor and indoor spaces. This necessitates unprecedented urban climate modelling at high temporal and spatial resolution. The interaction between complex urban geometries and the microclimate is characterized by complex transport mechanisms. The challenge to generate geometric and physics boundary conditions in an automated manner is hindering the progress of computational methods in urban design. Thus, the challenge of modelling realistic and pragmatic numerical urban micro-climate for wind engineering, environmental, and building energy simulation applications should address the complexity of the geometry and the variability of surface types involved in urban exposures. The original contribution to knowledge in this research is the proposed an end-to-end workflow that employs a cutting-edge deep learning model for image segmentation to generate building footprint polygons autonomously and combining those polygons with LiDAR data to generate level of detail three (LOD3) 3D building models to tackle the geometry modelling issue in climate modelling and solar power potential assessment. Urban and topography geometric modelling is a challenging task when undertaking climate model assessment. This paper describes a deep learning technique that is based on U-Net architecture to automate 3D building model generation by combining satellite imagery with LiDAR data. The deep learning model used registered a mean squared error of 0.02. The extracted building polygons were extruded using height information from corresponding LiDAR data. The building roof structures were also modelled from the same point cloud data. The method used has the potential to automate the task of generating urban scale 3D building models and can be used for city-wide applications. The advantage of applying a deep learning model in an image processing task is that it can be applied to a new set of input image data to extract building footprint polygons for autonomous application once it has been trained. In addition, the model can be improved over time with minimum adjustments when an improved quality dataset is available, and the trained parameters can be improved further building on previously learned features. Application examples for pedestrian level wind and solar energy availability assessment as well as modeling wind flow over complex terrain are presented

Achieving efficient real-time virtual reality architectural visualisation

Master'sMASTER OF ARTS (ARCHITECTURE