Procedural 3D urban content generation in simulation and games

As virtual urban environment generation becomes a widespread research topic, the need to create enriched urban worlds, which group both the geometric and semantic properties has become a necessity, the purpose being to obtain interactive, adaptive and consistent world entities. This paper suggests a representational model of urban environment generation based on both geometric and semantic knowledge, the future work being to create a modelling tool of a 3D urban environment, which stores the semantic information and allows the final non expert user to acquire information about the environment before and after its creation and to explore this information in an interactive way

On Improving Urban Environment Representations

Computer Graphics has evolved into a mature and powerful field that offers many opportunities to enhance different disciplines, adapting to the specific needs of each. One of these important fields is the design and analysis of Urban Environments. In this article we try to offer a perspective of one of the sectors identified in Urban Environment studies: Urbanization. More precisely we focus on geometric and appearance modeling, rendering and simulation tools to help stakeholders in key decision stages of the process

WUDAPT: an urban weather, climate and environmental modeling infrastructure for the Anthropocene

WUDAPT is an international community-based initiative to acquire and disseminate climate relevant data on the physical geographies of cities for modeling and analyses purposes. The current lacuna of globally consistent information on cities is a major impediment to urban climate science towards informing and developing climate mitigation and adaptation strategies at urban scales. WUDAPT consists of a database and a portal system; its database is structured into a hierarchy representing different levels of detail and the data are acquired using innovative protocols that utilize crowdsourcing approaches, Geowiki tools, freely accessible data, and building typology archetypes. The base level of information (L0) consists of Local Climate Zones (LCZ) maps of cities; each LCZ category is associated with range of values for model relevant surface descriptors (e.g. roughness, impervious surface cover, roof area, building heights, etc.). Levels 1 (L1) and 2 (L2) will provide specific intraurban values for other relevant descriptors at greater precision, such as data morphological forms, material composition data and energy usage. This article describes the status of the WUDAPT project and demonstrates its potential value using observations and models. As a community-based project, other researchers are encouraged to participate to help create a global urban database of value to urban climate scientists

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

ShapeCoder: Discovering Abstractions for Visual Programs from Unstructured Primitives

We introduce ShapeCoder, the first system capable of taking a dataset of shapes, represented with unstructured primitives, and jointly discovering (i) useful abstraction functions and (ii) programs that use these abstractions to explain the input shapes. The discovered abstractions capture common patterns (both structural and parametric) across a dataset, so that programs rewritten with these abstractions are more compact, and suppress spurious degrees of freedom. ShapeCoder improves upon previous abstraction discovery methods, finding better abstractions, for more complex inputs, under less stringent input assumptions. This is principally made possible by two methodological advancements: (a) a shape-to-program recognition network that learns to solve sub-problems and (b) the use of e-graphs, augmented with a conditional rewrite scheme, to determine when abstractions with complex parametric expressions can be applied, in a tractable manner. We evaluate ShapeCoder on multiple datasets of 3D shapes, where primitive decompositions are either parsed from manual annotations or produced by an unsupervised cuboid abstraction method. In all domains, ShapeCoder discovers a library of abstractions that captures high-level relationships, removes extraneous degrees of freedom, and achieves better dataset compression compared with alternative approaches. Finally, we investigate how programs rewritten to use discovered abstractions prove useful for downstream tasks

Linking design to finance : enabling a co-operative developer platform through automated design and valuation

Thesis: S.M., Massachusetts Institute of Technology, Department of Architecture, 2017.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 136-141).Significant shifts in technology and finance are altering the practice and position of urban design and development. These shifts - the torrent of micro-spatialized data, the amplification of designer instrumentality through computation, and the financialization of built capital into abstract securities - are forming a new relational infrastructure propelling the production of the built environment. Currently, coupling these shifts together remains the specialty of well-capitalized and sophisticated institutions, but the march of technological progress forecasts the widespread democratization of urban development skills and knowledge. This thesis explores the potential outcomes from mass accessibility to urban data, design computation, and digitized financing. I present two patent propositions outlining design methods that culminate in a project deploying network effects through collectively-financed, mass-distributed developments. The project is situated in three neighborhoods of New York City, on three-dozen sites for one-thousand inhabitants, and the methodology consists of three design computation processes. The first is a method for the automated re-massing of urban typologies using procedural scripting and a geometry constraint engine, in order to achieve open-space and density targets. The second is the automated valuation of a real estate development project using projected cash flows and construction cost estimations. Lastly, an optimization method matches suites of sites, project-massings, and financing arrangements; demonstrating the ability for the inhabitants' spatial needs to be met within financial constraints. Assuming that these technologies will be in widespread use evokes a vision for clusters of households to collectively originate, fund, and construct networks of mutually co-dependent developments. With the ability to operationalize a co-ownership model of distributed live-work spaces, self-organizing groups will have a dramatically expanded capability to influence the design and use of urban fabric - in practice, a Lefebvrian 'right to the city'.by Daniel Fink.S.M