Computing Urbanism

Computing Urbanism for an Eco Downtown,Pittsburgh Finding order in disorder through a computational urbanism approach

Abhinavv Singh Master of Urban Design 2020 Carnegie Mellon University

Downtown,Pittsburgh

Abstract The aim of this course was to develop our own procedural methods for reordering the urban fabric, analyzing the performance of design decisions. Using Downtown Pittsburgh as the site, the focus was on augmenting existing networks, reconfiguring urban morphology, and expanding the public realm. while learning the fundamentals of using urban data, multi-dimensional scripting, and specialized analysis tools.

The project aims to introduce a green component in the highly saturated and dense configuration of Downtown Pittsburgh.

Green infrastructure broadly covers the major component of the project including tree cover, topography, flood basin, drainage system each when pieced together can give a holistic insight at dealing with the problem. The urban domain plays a big role in shaping the morphology of the city. Building footprints, street network transport infrastructure including car, bus, cycle all need to work in tandem and need to be informed by concepts of green design The most important and often overlooked aspect of mega scale projects is the human cost that they inflict. Demographics of existing communities, population density, racial breakdown, economic capacity, social amenities, social infrastructure such as schools, religious institutions that may need relocation or rebuilding. These projects often destroy the existing social fabric. The aim of the project is to make a sensitive intervention in the public realm with the intention of scalability with least physical and environmental negative impact

Layout1 | Context Model Downtown Pittsburgh is chosen as the site of the project. Downtown’s context is extremely interesting as it is located at the intersection of the Alleghany and Monongahela rivers. A major part of the site falls within the flood zone of the two rivers. The topography within Downtown though not very steep, the site is surrounded by some difficult terrain and is usually the point where the water from the hilly regions drains off. The extreme built morphology of the site is also an interesting factor to analyze since there are very few vacant lots and the built mass indicates that there are less pervious surfaces. The above factors make Downtown an interesting site to study water flow.

Studying the built and natural morphology of Downtown helps establish the relationship between the two exisitng condtions on site.

The Built mass far outweighs the unbuilt typology and hence it is not surprising that Downtown suffers from regular flooding. The surrounding neighborhoods, their topography and infrastructure also impact Downtown in several ways.

It is also important to analyze the sewer and storm water layout to check if any patterns emerge that can inform future design solutions.

Parks Flood lines Contours

Natural systems

Buildings

Built Infrastructure

Layout3 | Analysis

Downtown has a much lower vacancy rate as compared to other parts of the city. These vacant parcels though few and far between form a network that can be utilized to include green measures that can help mitigate flooding. Clustering the vacant parcels near existing tre clusters can increase the impact of the existing greens and act as a starting point for economically feasible design interventions

One of the major aspects of flood resilient design is the presecnce of trees. The roots of trees are known to absorb water and absorb surface run off reducing the possibility of flooding on streets. Based on the Pittsburgh tree data, the points of interest are chosen in areas with seemingly less trees. A 500 feet buffer around these trees is used to identify the parcels where interventions can be made to increase tree cover. Similarly, due to the low plot vacancy rate in downtown, the buffer is run to check buildings that can be targetted to inculcate vertical gren facades in an atempt to increase green cover.

The purpose of this heat map is to identify tree clusters and check the density. The points of interest were identified as roughly in the center of any cluster of greater than 10 trees.

As we move away, we can map out the areas in need of more trees.

The areas in light green and yellow are finalized as regions where tree plantation can take place

Built Morphology

Cluster Mapping

Heat Map

Height field

Flow Simulation

The flow simulation when overlayed with the contour lines explains the direction of the flow of water and its lessening intensity in the relatively flat terrain of central downtown.. The streets in central downtown would be less prone to flooding. However, the previous network analysis had hinted at central downtown streets being better connected and hence a better spot for the design intervention. Overlaying the two analyses would give us a holistic idea for the location of the module

Betweenness Centrality

Closeness Centrality

Tree cluster network

Walkshed from tree cluster

Using the street centerlines to calculate the between centrality and closeness centrality gives a good idea about the street network. Downtown’s dense urban fabric inspired the design of an urban canopy component which would utilize the streetscape and adapt to it based on various factors such as connectivity and use. The more connected streets computed here would be a great starting point to introduce the component in the scenario stage. This also responds to the design metrics of replicability of the module Instead of bus stops, the script was utilized to calculate the network for tree clusters. The points for tree clusters with more than 10 trees have been previously identified. The walkshed helps visualize the location of the intervention within a walking radius. The walkabiloty score for downtown being relatively high due to its flat terrain allows for a greater radius and hence greater connectivity and impact of the module

SCENARIO 1: THE URBAN CANOPY The first iteration of the component pod is intended to act as an urban tree canopy along the street edge in lieu with the low vacancy rates for plots in Downtown, The urban canopy can act as a bus shelter, meeting point, food stalls, kids play area and several other activities while absorbing the CO2 generated through the algae The idea

The view

SCENARIO 2: THE VERTICAL GARDEN The second iteration is inspired by the design of Bosco Verticale in replicating a vertical garden in the dense highrise environment of Downtown. The higher levels will give the opportunity to the module to collect greater quantities of CO2 while acting as rain water harvesting module.

The idea

The view

parcel lines

parcel boundary

tree locations

large tree clusters

tree cluster boundary

parcels within tree cluster boundary

system overlay

populating parcels

Scenario Planning The final step required developing a logic that would govern the placing of the component. The two parameters chosen were the tree clusters that have inspired the design of the component.

Tree clusters were grouped and combined with plots in their vicinity to create a domain within which the component cpuld be populated. The plots closest to the tree cluster would be analyzed by site and the number of components would be decided.

Tree cluster

Group by size of cluster

Create boundary for parcels

Create outline for cluster to determine closeness to parcels Cull parcels to find those within tree cluster outline

Set a parameter of 500 sq feet. For every 500 square feet, populate a parcel with a component.

Designing in the urban realm can take a whole new dimension by merging the qualitiative and quantitative aspects of space. By computing large scale data, we can get a holistic picture and use it to determine parameters that add layers of complexity and sophistiation to design. In the urban realm, where multiple actors and forces are at play, design cannot be one dimensional and using multiple parameters helps provide a solution that is more flexible, optimal and robust.

Abhinavv Singh Master of Urban Design 2020 Carnegie Mellon University