Modelling Day and Night-Time Population using a 3D Urban Model

Dasymetric methods are commonly used to redistribute or disaggregate (census) population data, using either simple binary or multi-layer models. Most models show limitations in high density built-up areas as they commonly ignore the 3D dimension (meaning buildings height) of multi-story urban environments. For example, simple dasymetric models only allocate the population counts to built-up areas, without considering differences between areas of multi-story and single-story buildings. Furthermore, such models only allow the disaggregation of ‘night-time’ population data, while for many urban applications such as transport, health or hazard, the location of ‘day-time’ population is of interest. This research presents an initial approach to model day and night-time population using as case study an Indian city (Kalyan-Dombivli). For most Indian cities, census population data is only available for wards, while day-time population data is either not available or of very poor quality. Besides census data and ancillary spatial data, this research uses a 3D urban model, extracted from Cartosat stereo-images. First, the extracted height from the stereo-image is used in combination with building footprints to disaggregate census population data at wards to ‘night-time’ population per building. Second, a classification of economically active areas is constructed based on the 3D urban model in combination with other spatial layers (e.g. transport layers) to model the day-time population. The result shows different concentration of population during day and night-time across ward boundaries as well as it confirms the potential of 3D data to disaggregate population data

Pathway using WUDAPT's Digital Synthetic City tool towards generating urban canopy parameters for multi-scale urban atmospheric modeling

The WUDAPT (World Urban Database and Access Portal Tools project goal is to capture consistent information on urban form and function for cities worldwide that can support urban weather, climate, hydrology and air quality modeling. These data are provided as urban canopy parameters (UCPs) as used by weather, climate and air quality models to simulate the effects of urban surfaces on the overlying atmosphere. Information is stored with different levels of detail (LOD). With higher LOD greater spatial precision is provided. At the lowest LOD, Local Climate Zones(LCZ) with nominal UCP ranges is provided (order 100 m or more). To describe the spatial heterogeneity present in cities with great specificity at different urban scales we introduce the Digital Synthetic City (DSC) tool to generate UCPs at any desired scale meeting the fit-for-purpose goal of WUDAPT. 3D building and road elements of entire city landscapes are simulated based on readily available data. Comparisons with real-world urban data are very encouraging. It is customized (C-DSC) to incorporate each city's unique building morphologies based on unique types, variations and spatial distribution of building typologies, architecture features, construction materials and distribution of green and pervious surfaces. The C-DSC uses crowdsourcing methods and sampling within city Testbeds from around the world. UCP data can be computed from synthetic images at selected grid sizes and stored such that the coded string provides UCP values for individual grid cells

Prototyping Information Visualization in 3D City Models: a Model-based Approach

When creating 3D city models, selecting relevant visualization techniques is a particularly difficult user interface design task. A first obstacle is that current geodata-oriented tools, e.g. ArcGIS, have limited 3D capabilities and limited sets of visualization techniques. Another important obstacle is the lack of unified description of information visualization techniques for 3D city models. If many techniques have been devised for different types of data or information (wind flows, air quality fields, historic or legal texts, etc.) they are generally described in articles, and not really formalized. In this paper we address the problem of visualizing information in (rich) 3D city models by presenting a model-based approach for the rapid prototyping of visualization techniques. We propose to represent visualization techniques as the composition of graph transformations. We show that these transformations can be specified with SPARQL construction operations over RDF graphs. These specifications can then be used in a prototype generator to produce 3D scenes that contain the 3D city model augmented with data represented using the desired technique.Comment: Proc. of 3DGeoInfo 2014 Conference, Dubai, November 201

Transformable Space Based on Human Body Movement

Due to the increase in urban population and the rising cost of providing housing, the size and quality of dwelling space in the city has become an issue. Asian cities like Hong Kong and Tokyo have already shrunk the normal living space to accommodate more units in a development. Taipei, Singapore, and Shanghai are also evolving toward the same solution. This dissertation argues that there are alternative ways to design and reshape our dwelling space to create an efficient space based on human body movement and at the same time retain spatial quality . Dance can be seen as creating extreme body movements compared to our daily movement, so the hypothesis of this dissertation is that if a space can accommodate dance movement, then most likely it will be a comfortable space for daily movement. The study begins with a historical research of space, including the concept of space, human use of space, and body movement in the space. Rudolf Laban’s theory of dance movement is one of the main ideas investigated and reinterpreted for the research and design dissertation. To understand the human daily movement, data gathering is key to the thesis. The subjects of study are from both dance body movement and daily body movement. A videotaping process is used to record these movements. During the data collecting process, both two dimensional and four dimensional methods are used. The first phase records the body movements and translates these into two dimensional images. These images are simulated into three dimensional representations. In the design phase, computer models are made with Rhinoceros, Maya, 3D Studio Max, and MotionBuilder to simulate the new space prototype and body movements based on the analyzed information to create more efficient spaces that also provide a better quality living environment. 1 For the purpose of this study, spatial quality is defined as visual experience, lighting quality, and ventilation quality. 2Four dimensional is a combination of three dimension and the time factor, can also be called 3D animation

An overview of virtual city modelling : emerging organisational issues

This paper presents a recent overview of the increasing use of Virtual Reality (VR) technologies for the simulation of urban environments. It builds on previous research conducted on the identification of three-dimensional (3D) city models and offers an analysis of the development, utilization and construction of VR city models. Issues pertaining to advantages, barriers and ownership are identified. The paper describes a case study of the development of a VR model for the city of Newcastle upon Tyne in the UK and outlines the role that academic institutions can play in both the creation and utilization of urban models. The study offers a new approach for the creation, management and update of urban models and reflects on issues which are emerging. Areas for future research are discussed

Video Registration in Egocentric Vision under Day and Night Illumination Changes

With the spread of wearable devices and head mounted cameras, a wide range of application requiring precise user localization is now possible. In this paper we propose to treat the problem of obtaining the user position with respect to a known environment as a video registration problem. Video registration, i.e. the task of aligning an input video sequence to a pre-built 3D model, relies on a matching process of local keypoints extracted on the query sequence to a 3D point cloud. The overall registration performance is strictly tied to the actual quality of this 2D-3D matching, and can degrade if environmental conditions such as steep changes in lighting like the ones between day and night occur. To effectively register an egocentric video sequence under these conditions, we propose to tackle the source of the problem: the matching process. To overcome the shortcomings of standard matching techniques, we introduce a novel embedding space that allows us to obtain robust matches by jointly taking into account local descriptors, their spatial arrangement and their temporal robustness. The proposal is evaluated using unconstrained egocentric video sequences both in terms of matching quality and resulting registration performance using different 3D models of historical landmarks. The results show that the proposed method can outperform state of the art registration algorithms, in particular when dealing with the challenges of night and day sequences

From buildings to cities: techniques for the multi-scale analysis of urban form and function

The built environment is a significant factor in many urban processes, yet direct measures of built form are seldom used in geographical studies. Representation and analysis of urban form and function could provide new insights and improve the evidence base for research. So far progress has been slow due to limited data availability, computational demands, and a lack of methods to integrate built environment data with aggregate geographical analysis. Spatial data and computational improvements are overcoming some of these problems, but there remains a need for techniques to process and aggregate urban form data. Here we develop a Built Environment Model of urban function and dwelling type classifications for Greater London, based on detailed topographic and address-based data (sourced from Ordnance Survey MasterMap). The multi-scale approach allows the Built Environment Model to be viewed at fine-scales for local planning contexts, and at city-wide scales for aggregate geographical analysis, allowing an improved understanding of urban processes. This flexibility is illustrated in the two examples, that of urban function and residential type analysis, where both local-scale urban clustering and city-wide trends in density and agglomeration are shown. While we demonstrate the multi-scale Built Environment Model to be a viable approach, a number of accuracy issues are identified, including the limitations of 2D data, inaccuracies in commercial function data and problems with temporal attribution. These limitations currently restrict the more advanced applications of the Built Environment Model