Cityengine future manual#
Cityengine future software#

Computer programs can follow rules to create and manipulate virtual polygonal mesh models superhumanly quickly and accurately. It is here that we see another advantage of working with virtual, rather than physical, 3D models. Such modeling systems offer tools to procedurally generate 3D meshes from systems of rules-they are able to create models with millions of vertices in seconds. In particular, we will diveВ deeply into a particular modeling system: EsriвЂ™s CityEngine. In this chapter, we introduce one way to instruct them: rule-based modeling. Luckily, computers are rather good at these repetitive tasks-if we can find a way to explain to them what to do. What we would rather do is to create a rule which encodes вЂњattach a sphere to every front doorвЂќ. For our use cases, we might imagine our long-suffering artist being employed to position a spherical doorknob on every rectangular front door, of every building, in the urban area we are modeling.

Cityengine future manual#

Even though these manual tools have become incredibly sophisticated and general, they still require users to spend a lot of time positioning and editing triangles and primitives. Such manual tools include Autodesk Maya ( 2019), Trimble SketchUp ( 2019), or Blender ( 2019). Traditional manual 3D modeling tools offer a way to create multiple triangles at a time by creating more complex primitives (spheres, cubes, curves, surfaces, extrusions, etc.). There are many tools available for creating these polygonal meshes. We may even choose to apply colors or texture to each triangle. By creating many thousands of such triangles, we can build representations of complex 3D environments. This is a set of corners (vertices) placed in 3D space, between which we create triangles.

The de facto 3D representation is the mesh. 3D tools such as physical simulation (solar potential, window modeling) and viewpoint rendering help engineers design empirically better environments because we are able to explore our design spaces more quickly, we understand them faster, produce better designs, and better comprehend any issues.

Technologies such as immersive virtual and augmented realities (VR, AR, often summarized as XR) allow anyone from children to city planners to understand complex designs by exploring them at real-world scales. While it has always been possible to create physicalВ scale models of our environments, these are expensive, difficult to transport or share, and bulky to store. As various technologies such as commodity 3D CAD and photogrammetric reconstruction have matured, we are able to accurately construct virtual 3D models of our 3D world.ДЄt the same time as making our data more accurate, 3D models make our data more accessible. Collecting and sharing this 3D information has been, until recently, difficult and prohibitively expensive. Technology now enables us to efficiently record, model, and plot in 3D. This is because there is more information in the 3D world than 2D plans contain. The 3D data must be encoded using various tricks and conventions, such as contourВ lines, elevation diagrams, symbols, and shading.

Reading 2D plans and maps is often challenging because they are oneВ dimension short of the 3D world we live in. Revolutions are, however, rarely easy there are numerous issues and challenges around this transition from 2D to 3D toolchains.

We introduce the principal workflows and the flexibility they afford, sketch the procedural programming language used, and discuss the export pathways available.ДЈD technologies are revolutionizing the way we plan, understand, communicate, and document our urban environments. Such advantages must be carefully balanced against the increased time to create and parameterize the rules and the sometimes stylistic or approximate models created coming from more traditional workflows, CityEngineвЂ™s pipeline can be initially overwhelming. Additionally, this rule-based approach means that large design spaces can be explored quickly, interactively, and analytically compared. The rule-based core of EsriвЂ™s CityEngine has some unique advantages: Huge cities can be created as easily as small ones, while the quality of the models is consistent throughout. Typical applications include processing 2D urban cartographic geographic information system (GIS) data to create a detailed 3D city model, creating a detailed visualization of a proposed development, or exploring the design space of a potential project. It offers a flexible pipeline to transform 2D data into 3D urban models.

Cityengine future software#

CityEngine is a rule-based urban modeling software package.