Green Atlas MACT. Computational Design II
Developing simulations tools to understand green and urban spaces in Barcelona.
Alejandro Quinto · Byron Cadena · Elijah Munn · Aryo Dhaneswara
Data Sources
How can these help to take better decisions and have a better understanding of the space?
How can these help to take better decisions and have a better understanding of the space?
Methodology
Existing condition: Trees path
Existing condition: Trees vs cars
RATING CRITERIA: Existing conditions ()
RATING CRITERIA: Generative design (Building density)
RATING CRITERIA: Generative design (green space density)
RATING CRITERIA: Generative design (garden rooftop)
RATING CRITERIA: Trees on path.
RATING CRITERIA: Trees on path (race)
RATING CRITERIA: Trees on path (eval)
Generative design
Generative Scenario Evaluating the visual impact of the different generative designs by keeping a constant parameters such as density and existing roads as input.
Outputs Number of buildings Volume of building Roof area Square meter of green area Road length
Sidewalk area Green area Building area Road area
Analysis grid (occlusivity)
Analysis grid (combined)
Rating Criterias Occlusivity (Openness)
Trees in sight (360ยบ)
Trees density
CO2 performance
Existing iterations
Generative iterations
Gotic: generative design
Limitations
Isovist Area Distance Weighted Area Perimeter Compactness Circularity Convex DeďŹ ciency Occlusivity Min Radial Max Radial Mean Radial
Max Radial Mean Radial Standard Deviation Variance Skewness Dispersion Elongation Drift Magnitude Drift Angle
We are aware of the limitations but, considering this, how do we take this further?
Next?