The Viability of the Procedural Modeling Technique in ...

4th Annual International Conference on Architecture and Civil Engineering (ACE 2016)

The Viability of the Procedural Modeling Technique in Scenario Analyses of the Residential Site Plans The Optimization Case of the Korean DIF Zoning Requirements

Nae-Young Choei Dept. of Urban Design & Planning Hongik University Seoul, Korea

The paper reviews the procedural modeling in Ch. II. The chapter also introduces the Korean DIF zoning provision with which the study cases are simulated. The study data and the specific case area is observed in Ch. III. Scenario analyses are proceeded with full presentation of the 3D models together with the financial calculation for each version of scenarios in Ch. IV. Ch. V and VI discusses and concludes the findings. II. PROCEDURAL MODELING AND DIF ZONING

Abstract—This paper delves into experimenting the so-called procedural modeling in an effort to try: the generation of the 3D residential site models based on alternate 2D site plan scenarios; and to evaluate and compare them via its interoperability with the GIS geodatabases. The scenarios are implemented on a Korean Development Impact Fee (DIF) zone located at a specific site in Pyeongtaek City. It has been demonstrated that the procedural modeling could be a very viable and cost efficient tool to reach the optimality of the design consequences in terms of both physical design quality and financial feasibility, if the relevant CGA rules and proper framework of multi-criteria evaluation are available. Keywords-procedural modeling; interoperability; analysis; development impact fee; residential site plan

I.

A. Procedural Modeling Technique Procedural modeling is a technique in computer graphics to create 3D models and textures from the preset CG Architecture rules. The origins of CGA go back to the introduction of shape grammars in the seminal work by Stiny and Gips [10-12], and their adaptation to computer graphics applications is presented by Wonka et al. [13]. Now commercially available under the name of CityEngine from ESRI, it now readily allows one to compare and analyze building proposals from various angles and to see how they fit into the overall urban settings (either contemporary or ancient).

scenario

INTRODUCTION

Geographical information systems (GIS) have traditionally operated in the 2D domain but are now rapidly moving towards real 3D. The processes of creating the 3D models range from completely manual content creation to semi-automatic techniques using the generative modelling techniques [1]. As the scale and quality requirements for generation of urban 3D environments is increasing, manual creation becomes very time-consuming. Therefore, computer-assisted, semiautomatic, or even fully automatic methods seem to be moving more and more to the center of focus these days [6].

The capability of the CGA modeling could be demonstrated in the case of archaeological restoration of the ancient temples illustrated in Fig. 1 (see, for more detail, [6] and [7]). While Panels a) and b) show the actual Parthenon temple in Athens, Greece, Panels c) and d) are the restored version of the temple located in Nashville, Tennessee, in the US. The pictures of Nashville version have been taken by the authors in mid-November, 2014, during their survey tour to the US.

The purpose of this paper is to experiment the socalled “procedural modeling” as one of the available 3D urban modeling techniques in an effort to try: first, the generation of the 3D perspectives from the alternate 2D site plan scenarios; and second to evaluate and compare each different version of enhancing scenarios. The cases are implemented on a Korean DIF zone currently of disorderly layout of the residential parcels and infrastructures that are to be rehabilitated. The viability of adopting the procedural modeling technique will be tested with the three different scenario versions on this test-bed and the consequences are then to be discussed.

Probably, the second alternative other than expensive physical restoration could be the virtual restoration achievable by the procedural modeling. Panel e), for instance, shows the pane of CityEngine that encodes the CGA rule for the temple. Once proper and complete rules are encoded, diverse type of ancient temples in 3D could be created as in Panel f) [6]. Further, the similar rules could be used to restore even the entire ancient cities such as Pompeii (Fig. 2) [7]. The same approach, of

4th Annual International Conference on Architecture and Civil Engineering (ACE 2016) Copyright © GSTF 2016 ISSN 2301-394X doi: 10.5176/2301-394X_ACE16.123

© 2016 GSTF

136

4th Annual International Conference on Architecture and Civil Engineering (ACE 2016)

By making the virtual 3D visualization as real as possible in the design phase, costly mistakes in the building phase could also be avoided.

a) Athens Parthenon façade

c) Nashville Parthenon façade

B. DIF Zoning in Korea Development impact fees (DIF) are used for the provision of public infrastructure services such as roads, schools, parks, water and sewer that are necessary to adequately serve new developments. In the US, for example, impact fees are an increasingly common tool that municipalities use to finance public amenities, and roughly a quarter of local governments in the US now use them (see [2], [3], and [4]).

b) Athens Parthenon corner view

In Korea, many localities around the Capital Region have frequently suffered from sporadic incidences of uncontrolled developments during the periods of its rapid economic development in the last few decades. In order to counteract, the Ministry of Land, Infrastructure, and Transportation (MOLIT) provided the DIF zoning Act in 2008. Like its US counterpart, the Act requires localities to set up separate districts called the ‘DIF zone’ based on the population growth rate, and to prepare an adequate master plans to rehabilitate the area once the zone is designated [5].

d) Nashville Parthenon corner view

(Nashville photographs taken in November, 2014)

III.

A. Data The parcel based cadastral information from the Korea Land Information System (KLIS) and building register information from the electronic Architectural Information System (eAIS) are used in this paper. While the KLIS provides accurate spatial information including the shapes and sizes of every land parcel, the eAIS offers physical information of the building structures on each parcel. By joining the two Korean National Geographic Information System (NGIS) databases on the GIS platform, complete spatial data for the study site have been successfully constructed.

e) Encoding in shape grammar to build CGA rule set for the temple

f) Archaeological restoration of the Greco-Roman temples Figure 1.

DATA AND CASE AREA

Sample procedural modeling of Greco-Roman temples

In addition, the aerial orthophotograph made by the National Geographic Information Institute (NGII) have also been used to

course, could be exploited for the contemporary buildings and urban environments.

One critical aspect of the technique is that it could generate as many scenarios as needed so that time and costs are significantly saved in preparing the various design alternatives.

Figure 3. Location of the study site in Pyeongtaek City of South Korea

Figure 2. Sample user-interface in Greco-Roman archaeological application

© 2016 GSTF

137

4th Annual International Conference on Architecture and Civil Engineering (ACE 2016)

increasing more than 20% in the last consecutive years, meeting the DIF zone criterion. IV.

SCENARIO ANALYSIS OF THE PLANS

A. Consideration of DIF Requirements The land owners in the DIF zones are subject to fee payment (private sector charge), matching the locality’s budget expenditure (public sector subsidy), to finance the infrastructure installation cost when rehabilitation takes place in the zone. Generally, 6:4 contribution ratio is adopted between the private and public sector so that the scenario analyses in this paper practices the same financial schedule. Since the objective of the DIF zoning is to totally rehabilitate the disorderly parcel layouts and deficient infrastructure in the zone to the ones with high quality amenity, the entirely new subdivision of parcels within the zonal area take place in accordance with the new site plan. Figure 4. Disorderly study site compared to other well-planned sectors

render the background 3D terrain and existing structure images in the vicinity of the study site. B. Case Area Pyeongtaek City is located at the southernmost part of Gyeonggi Province, the core of the Capital Region of Korea (see Fig. 3). Ranging from 126°46ʹW to 127°09ʹE and 36°54ʹS to 37°08ʹN, it accommodates 434,305 residents as of 2013, and the number is ever increasing. The City has Pyeongtaek Harbor along the western seashore, having become the second largest transshipment points next to Incheon in Yellow Sea. The statistics indicate that it now is one of the fastest growing cities in the Capital Region. The site area has been selected by the MOLIT as a one candidate area to setup a DIF zone [5]. As can be seen in Fig. 4, the area has extremely irregular and disorderly layouts within its border as contrasted to the newly rehabilitated blocks outside of it. Despite its deficient infrastructure, the population is

As the DIF is composed of land cost as well as infrastructure construction cost (as formally formulated in the next section), current land price information should be extracted from the MOLIT’s ALPA (Automatic Land Price Appraisal) System, a part of KLIS database. The land prices of existing parcels should then be totally rearranged into newly divided parcels as well as newly installed roads, parks, and, green areas drawn in the site plan, the cost estimation and redistribution processes becomes enormously complicated. B. Development Impact Fee Formula The total infrastructure installation costs should be obtained as dictated in the current DIF regulation. First, it comprises two major components: 1) facility construction cost; and 2) the land acquisition cost for each of the k sorts of infrastructure [5]. ) 𝐿𝐿𝐿𝐿𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝐿𝐿𝐿𝐿𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑖𝑖𝑖𝑖 (1) 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 = ∑𝑖𝑖𝑖𝑖𝑘𝑘𝑘𝑘𝑖𝑖𝑖𝑖(𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖𝑖𝑖 ∙ 𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑈𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑖𝑖𝑖𝑖 +

The unit construction costs (UnitCosti) for each kind of infrastructure are based on the empirical data from the Korean Land and Housing Corporation (LH), whereas land costs are from the ALPA database. The average cost, then, is obtained by dividing the total cost by the weighted building floor area (WtdFL). (2)

𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝑇 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 ⁄𝐴𝐴𝐴𝐴𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝐴𝐴𝐴𝐴𝐿𝐿𝐿𝐿

The WtdFL in eq. (2) is obtained as follows: the largest allowable building area on each parcel (MaxFLli) are multiplied by Wlj. Here, Wlj is the weight factor (e.g., 1.0 for residential (j=1), 2.6 for commercial (j=2), 1.9 for industrial (j=3), and 2.1 for other land-uses (j=4)). Additionally, the law permits that any building with floor area less than 200m2 is exempted from the fee payment. The formula, thus, could be expressed as: 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝑇

𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇

∑𝑛𝑛𝑛𝑛𝑙𝑙𝑙𝑙𝑖𝑖𝑖𝑖[(𝑀𝑀𝑀𝑀𝑇𝑇𝑇𝑇𝑀𝑀𝑀𝑀𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙

− 200) ∙ 𝐴𝐴𝐴𝐴𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 ]

for 𝑗𝑗𝑗𝑗 𝑗𝑗 (1, ⋯ ,4)

(3)

Finally, every individual parcel owner, possessing the structure of floor area FLl is subject to pay their respective fees (DIFl) according to the following calculation:

Figure 5. The fiscal structure of the levy of Development Impact Fee (DIF)

© 2016 GSTF

138

4th Annual International Conference on Architecture and Civil Engineering (ACE 2016)

a) Major steps of DIF estimation based for each site plan scenario

b) Corresponding Model Builder flows

c) Script codes for Model Builder flows

Figure 6. Model Builder encoding for DIF fee calculation and design quality estimation

𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝑙𝑙𝑙𝑙 = 𝐷𝐷𝐷𝐷𝐹𝐹𝐹𝐹𝑙𝑙𝑙𝑙 ∙ 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 ∙ 𝐴𝐴𝐴𝐴𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙

(4)

for 𝑙𝑙𝑙𝑙 𝑙𝑙 (1, ⋯ , 𝑛𝑛𝑛𝑛); 𝑗𝑗𝑗𝑗 𝑙𝑙 (1, ⋯ ,4)

C. Encoding of DIF Calculation via Model Builder of GIS Despite the fee estimation process requires significant amount of time and efforts due to its spatial complexity, it can be performed considerably with ease by using the ‘Model Builder’ tool available in the ArcGIS platform. Fig. 6 illustrates the process: Column a) shows the three basic steps to complete the estimation cycle; Column b) exhibits the captured images as displayed in the GIS platform. If one drags a necessary function into the Model Builder pane, the logical process for the task appears in the form of visually intuitive work flowcharts; and, finally, Column c) depicts the corresponding programming codes for that workflow. Internally, they are automatically encoded in Python script, the basic programming language of the ArcGIS. D. The Site Plan Scenarios 1) Scenarios 1 & 2: Fig. 7 shows the scenarios 1 and drawn 2 in the form of typical 2D land-use map with conventional zoning colors: the yellow-colored areas represent the residential parcels; the grey-colored, roads; and, the green and light-green areas are buffer green areas and parks, respectively.

Scenario 1 is of plain grid road system (with relatively few green areas) to minimize the infrastructure installation costs, hence of less-than-adequate amenity: Scenario 2 has more abundant community parks at the core of each residential block, hence, comes with much enhanced openspace amenity than its preceding version. To visualize the virtual 3D models of these two plans, the CG Architecture rules should be cast onto them. Also, in the CGA rule, street details should be embedded to check the adequacy of the road system as well as sufficient accessibility to the parcels. In this study, the Philadelphia CGA rule set was applied as illustrated in Fig. 8. Panel a) shows the Philadelphia CGA rule for housing and street modeling. The left-hand side is the outcomes when applied to Pyeongtaek study site, the right-hand side shows the outputs as it appears when the rule is applied onto real Logan Square of Philadelphia. On the other hand, the upper row of Penal a) exhibits the uploading step the rules: the lower row shows the virtual view of the modeling consequences. Panel b) of Fig. 8 shows the photographs of Logan Square taken by the authors at the time of survey visit to Philadelphia in November, 2014. Fig. 9 is the virtual 3D bird’s eye view of both scenarios 1 & 2 generated by the procedural modeling using the 2D landuse maps of Fig. 7. The backgrounds are the NGII’s orthophotograph images. As can be seen, the housing units,

© 2016 GSTF

139

4th Annual International Conference on Architecture and Civil Engineering (ACE 2016)

a) Land-use map of the site plan scenario 1

b) Land-use map of the site plan scenario 2

Figure 7. Land-use map of the site plan scenarios 1 & 2

streets, parks, and the green areas are quite realistically rendered in accordance with the Philadelphia CGA rules.

2) Scenarios 3: The main focus in the final scenario is, for its optimal prototype, to adopt the cul-de-sac street system originated from Radburn, New Jersey, in the US, As is well known in the field of site planning, the Radburn design had been the revolutionary plan, completely separating the pedestrian and vehicular circulations to guarantee the traffic safety by the cul-de-sac streets as well as its high level of amenity with its spacious community green at the core of each residential block in a neighborhood. Fig. 10 shows: a) the original drawing of the Radburn’s cul-de-sac by Stein (see, for original copy, [9]); b) its satellite image; and c) the survey photograph (viewed from the cul-de-sac road toward its dead-end side of the street) taken by the authors at Radburn, New Jersey, in November, 2014. The outcomes of scenario 3, adopting the cul-de-sac street system, is shown in Fig. 11. It displays: a) the 2D landuse map; and b) the 3D bird’s eye view of the site generated by procedural modeling. With its existing elementary school at the right-hand side of the block, wide community green areas (prepared as parks in the site plan) are reserved, which collects the car-free pedestrian foot ways originating from each housing unit to the large community green open-space, and connects the pedestrian circulation to the elementary school, just like the Radburn neighborhood block.

a) Application of the Philadelphia CGA rules to Pyeongtaek study site

b) Philadelphia Logan Square

The image in Fig. 12 shows the close-up look at one culde-sac street of the scenario 3 site plan, and it can be seen that the lot subdivision, housing type, and road system are quite close to those of the Radburn design shown in Fig. 10 earlier. E. Fiscal Estimation of the DIF Costs The three scenario plans presented thus far should have, of course, different cost structures according to their differentials in lot subdivision and areal sizes and capacities of different sorts of infrastructure (such as roads, parks, and green areas). In the DIF zoning, the financial and fiscal consequences are as important criteria as the physical quality of the design.

c) Outward view from the Logan Square

(Photographs taken in November, 2014) Figure 8. Application of the Philadelphia CGA rule for the study scenarios

© 2016 GSTF

140

4th Annual International Conference on Architecture and Civil Engineering (ACE 2016)

a) 3D bird’s eye view of the site plan scenario 1

b) 3D bird’s eye view of the site plan scenario 2

Figure 9. 3D-perstpective of the site plan scenarios 1 & 2

and performs complicated land cost calculations for changed lot configurations as well as newly provided infrastructures.

Fig. 13 is the captured image of the fee calculation sheets as appears in the attribute table within the GIS platform. This means that the GIS imports the values of the design variables directly from the procedural modeling platform (CityEngine),

The entire process is directed automatically by the preprogrammed Python script commands written by the Model Builder tool of GIS as illustrated in Fig. 8 earlier, and constructs the complete and formatted output attribute tables as shown in Fig. 13. It, therefore, is not necessary to export the intermediate GIS data to other spreadsheet or database management packages to perform any additional calculation, sorting, and/or formatting of the outputs. As can be seen in Fig. 13, the sum of land cost (column (3))

(Photograph taken in November, 2014)

Figure 12. Procedural modeling output of the cul-de-sac street and housing layout by site plan scenario 3

Figure 10. Radburn cul-de-sac block and its survey photograph for reference

© 2016 GSTF

141

4th Annual International Conference on Architecture and Civil Engineering (ACE 2016)

a) Land-use map of the site plan scenario 3

b) 3D-perstpective of the site plan scenario 3

Figure 11. Land-use map and procedural modeling output of the site plan scenario 3

construction costs (column (7)) shows a similar pattern, though the increase rate is much less than its counterpart (the land cost).

decreases from scenario 1 to 2, but significantly increases in the case of scenario 3. With far more plentiful green areas and parks, such a result seems quite conceivable. The infrastructure

Figure 13. Captured images of the attribute table of GIS that show the DIF fee calculation outputs for each of the three site plan scenarios

© 2016 GSTF

142

4th Annual International Conference on Architecture and Civil Engineering (ACE 2016)

Figure 14. Captured images of the attribute table of GIS comparing the physical and quatitative aspects for each of the three site plan scenarios

the procedural modeling platform. The housing and/or other building structure drawings are also automatically generated as far as one has the complete CGA rules beforehand. In this way, the time and efforts to draw the physical objects at the stage of schematic design is incomparably more efficient and faster.

Fig. 14, in like manner, shows the summary sheet of major design variables such as the proportion of the lands occupied by each new infrastructure in the site. These kind of indexes could effectively serve as the quantitative evaluation criteria to check the optimality of the design when interpreted by the professional site planners. Here, the red digits indicate the decreases whereas blue digits means the opposite. As can be expected, amenity-related infrastructures (parks, green areas, and parcel sizes) greatly increases while proportion of roads is most significantly decreases in the cul-de-sac type site plan of scenario 3. V.

Most important, unlike the conventional drawing tools, it keeps the design variables in the internal database interoperable with attribute table databases in the GIS platform. This implies significant implication with respect to controlling the physical facets of the planning (such as housing density, building heights, and areal proportions of each different land-uses). In this regard, it could enable the public sector to control and maintain the adequate amenity level from the policy perspective.

DISCUSSION

In the procedural modeling, much of the drawing details are predefined in the CGA rule so that it is much more efficient than relying on other conventional simple 2D drawing packages like CAD or 3D rendering tools like SketchUp. For instance, as one moves only the road’s center line, all other details like street width, lanes, crossings at the crossroad, pedestrian sidewalks, and street furniture are automatically and instantly redrawn in

Fig. 15 graphically compares the time and cost measures between using the procedural modeling technique and the conventional methods to derive alternative site plan scenarios. While the former requires relatively higher burden and time to prepare full sets of CGA rule at the initial stage, it’s repetitive design and evaluative efficiency gradually overrides the latter as the number of new alternative scenarios increases, and, once complete rule sets are ready, it converge to the level of no additional marginal costs while its counterpart yet keeps the straightforward increase rate. VI.

COLNCLUSION

The procedural modeling technique and its interoperability with the GIS platform has been exercised in this paper. In the course, it has been demonstrated that the procedural modeling could be a very efficient tool to approach the optimality of the design consequences in terms of both physical quality and financial feasibility if the planning scenarios are evaluated within the proper framework of multi-criteria standards. In reality, it has been true that the time-consuming and burdensome character of the conventional design methods have been the predominant causes that the planners compromise at an intermediate stage of less-than-optimal design outputs. If much of the designing, data processing, and evaluating processes could be automated, it is expected that the path finding to the design optimality can be reached very cost-efficiently. For this, of course, perfect CGA rule sets should precede in the procedural modeling platform. In the part of GIS, complete

Figure 15. Comparison of the design update costs between the conventional method and the procedural modeling technique

© 2016 GSTF

143

4th Annual International Conference on Architecture and Civil Engineering (ACE 2016)

Python programs for specific purposes should also be made available.

[7] [8]

REFERENCES [1] [2] [3] [4] [5] [6]

S. M. Arisona, C. Zhong, X. Huang, and R. Qin, “Increasing detail of 3D models through combined photogrammetric and procedural modelling,” Geo-spatial Information Science, vol. 16, no. 1, 2013, pp. 45-53. B. M. Baden and D. L. Coursey, An Examination of the Effects of Impact Fees on Chicago’s Suburbs. A Discussion Paper for the Workshop in Econ. Pol. and Pub. Fin., Univ. of Chicago Dept. of Econ., 1998. G. Burge and K. Ihlanfeldt, “Impact fees and single-family home construction,” J. of Urb. Econ., vol. 60, 2006, pp. 284-306. W. Clarke and J. Evans, “Development impact fees and the acquisition of infrastructure,” J. of Urb. Affairs, vol. 21, no. 3, 1999, pp. 281-288. Mininstry of Land, Infrastructure, and Transport (MOLIT), The Study on Vitalization of the DIF Zoning Provision in Korea. Gov’t Rep. no. 11-1613000-000404-01 (in Korean), 2013. P. Mueller, P. Wonka, S. Haegler, A. Ulmer, and L. V. Gool, “Procedural modeling of buildings,” ACM Transactions on Graphics, vol. 23, no. 3, July 2006, pp. 614-623.

[9] [10] [11] [12] [13]

P. Mueller, “Applied Procedural Modeling,” in ACM Siggraph 2007 Courses. Zurich: Assoc. of Comput. Mach. Inc., 2007, pp. 112-147. J. Schaller and C. Mattos, “ArcGIS ModelBuilder application for landscape development planning in the region of Munich, Bavaria,” in Digital Landscape Architecture, Buhmann, Pietsch, and Kretzler ed., Berlin: Verlag, 2010, pp. 42-52. C. S. Stein, Toward New Towns for America, 2nd ed. Cambridge, MA: MIT Press, 1957. G. Stiny, “Introduction to shape and shape grammars,” Environment and Planning B, vol. 7, pp. 343-351, 1980. G. Stiny, “Computing with form and meaning in architecture,” J. of Arch. Edu., vol. 39, no. 1, Autumn 1985, pp. 7-19. G. Stiny and J. Gips, “Shape grammars and the generative specification of painting and sculpture,” in Information Processing, C. V. Freiman, ed., Cambridge, MA: North-Holland, 1971, pp. 125-135. P. Wonka, M. Wimmer, F. Sillion, and W. Ribarsky, “Instant architecture,” ACM Trans. Graphics (Proc. Siggraph), vol. 22, no. 3, 2003, pp. 669-677.

© 2016 GSTF

144