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How can the existing planning codes in climate migration receiving cities like Atlanta prepared to accommodate the anticipated population influx in terms of affordable housing and resilient infrastructure?

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Climate-Migration Readiness in Atlanta

Missing-Middle Housing + Resilient Infrastructure Simulations

(Revit + Autodesk Forma)

Independent Study – M.S. Urban Design
Author: Nitiksha Mota - LinkedIn

Institution: Georgia Institute of Technology
Advisors: Prof. Brian Stone, Prof. Patrick Kastner


1. Overview

This repository documents a replicable workflow for evaluating how missing-middle housing infill can support climate-migration readiness while balancing environmental resilience in Atlanta neighborhoods.

The study focuses on:

  • Translating zoning and overlay codes into buildable scenarios
  • Testing density increases through ADUs, townhomes, and small multifamily housing
  • Evaluating microclimate, energy, wind, and stormwater impacts using simulation tools

This repo is intended as a guide for future students who want to:

  • Run neighborhood-scale simulations
  • Compare multiple density scenarios
  • Produce policy-relevant, climate-informed urban design analysis

2. Research Question

How can existing zoning frameworks in climate-migration receiving cities like Atlanta be leveraged to increase housing supply while minimizing environmental and microclimatic impacts?


3. Case Study Neighborhoods

Neighborhood Role in Study Development Pattern
Reynoldstown Retrofit model Built-out historic neighborhood
Vine City Rebuild model Disinvested, vacant-parcel-rich TOD area
Midtown Reference model Dense, transit-connected urban core

4. Tools Used

Modeling & Simulation

  • Autodesk Revit – massing + context modeling
  • Autodesk Forma – climate and performance simulations
    • Sun hours
    • Heat stress
    • Wind comfort
    • Solar panel potential

Planning & Policy

  • Atlanta Zoning Ordinance (R-5, SPI-19, SPI-16)
  • BeltLine Overlay District regulations
  • MARTA proximity and TOD guidelines


5. Workflow Summary

Step 1 — Define Site Type

Each neighborhood is categorized by growth logic:

  • Retrofit (Reynoldstown): limited vacancy, backyard infill
  • Rebuild (Vine City): block-scale redevelopment
  • Reference (Midtown): contextual benchmark

Step 2 — Translate Zoning Into Design Rules

For each site:

  • Maximum units per lot
  • Height and setback limits
  • Parking requirements or reductions
  • ADU permissions
  • Overlay intent (TOD, walkability, affordability)

This step ensures proposals are code-aligned.


Step 3 — Create Density Scenarios

Each site includes:

  • Existing condition
  • Proposal 1 (moderate infill)
  • Proposal 2 (higher density infill)

Scenarios differ in:

  • Number of units
  • Roof area
  • Tree canopy loss
  • Ground permeability

6. Simulation Workflow (Core of the Study)

6.1 Revit Preparation

Goal: Comparable, clean massing models.

Best practices:

  • Use simple massing (avoid detailed components)
  • Keep ground plane constant across scenarios
  • Maintain consistent building heights
  • Represent trees as simplified canopy objects
  • One Revit file per scenario

6.2 Import to Autodesk Forma

  • Create a Forma site using real address
  • Import Revit massing
  • Verify:
    • Orientation
    • Scale
    • Terrain alignment

⚠️ Important: Do not change simulation settings between scenarios.


7. Simulations Performed

A. Sun Hours Analysis

image

Purpose: Measure daylight tradeoffs caused by density.

Run conditions:

  • Winter Solstice (Dec 21)
  • Summer Solstice (Jul 21)
  • Daytime window (e.g. 8:00–16:00)

Recorded outputs:

  • % ground with ≥ 3 hours sun
  • % facades with ≥ 3 hours sun
  • % roofs with ≥ 3 hours sun

Interpretation focus:

  • Backyard livability
  • Passive solar access
  • Roof usability for PV

B. Microclimate / Heat Stress

image

Purpose: Evaluate thermal comfort impacts of added density.

Run condition:

  • July 21, 2 PM (peak summer heat)

Metrics recorded:

  • % strong heat stress
  • % moderate heat stress
  • Spatial concentration of heat

Key insight:

Heat stress changes were driven more by tree canopy loss than by density alone.


C. Wind Comfort Analysis

image

Purpose: Understand pedestrian-level comfort and ventilation.

Run condition:

  • Prevailing east wind

Outputs:

  • Comfort categories (sitting → uncomfortable)
  • Wind stagnation vs channeling
  • Block interior ventilation

Key tradeoff:

  • Trees improve comfort but can reduce cooling airflow

D. Solar Panel Potential

image

Purpose: Evaluate energy resilience benefits of added density.

Metrics recorded:

  • Total roof surface area
  • Panel placement area
  • Estimated annual energy output (kWh)

Finding:

Higher density increases total solar capacity, even if per-square-foot performance remains similar.


E. Stormwater + Runoff (Interpretive Analysis)

While Forma does not directly model runoff volume, geometry-based conclusions were drawn:

Observed impacts:

  • Increased roof area → increased runoff volume
  • Reduced parking helps lower impervious surface per unit
  • Tree loss reduces interception and evapotranspiration

Mitigation strategies proposed:

  • Mandatory rainwater harvesting
  • Cool / reflective roofs
  • Green roofs
  • Bioswales + green streets
  • Permeable paving
  • Tree replacement ratios

8. Writing Findings (Reusable Template)

For every analysis slide:

Findings

  • Quantitative results (% or area)
  • Spatial patterns

Interpretation

  • Comfort impacts
  • Environmental tradeoffs
  • Policy relevance
  • Equity implications

9. Key Results Summary

Reynoldstown (Retrofit Model)

  • ~230 new units via ADUs + small MF
  • Minimal heat increase with canopy preservation
  • Stormwater manageable with lot-scale mitigation
  • Low displacement risk

Vine City (Rebuild + TOD Model)

  • 196–263 new units across scenarios
  • Heat stress remains similar across densities
  • Significant solar + housing gains
  • Stormwater impacts require district-scale solutions

10. Resilience Toolkit (Recommended Requirements)

For missing-middle infill:

  • Rainwater harvesting on all new roofs
  • Cool or green roofs
  • Bioswales + curbside green infrastructure
  • Permeable paving
  • Tree replacement (1–2 new trees per removal)

11. Future Extensions

  • Quantitative stormwater modeling (SWMM / SCS-CN)
  • Canopy sensitivity testing
  • Neighborhood-to-neighborhood comparison toolkit
  • Policy scenario testing (density bonuses tied to resilience)

12. Citation

This repository is based on the Independent Study submission: “Climate-Migration Readiness in Atlanta: Housing + Resilient Infrastructure”
Georgia Institute of Technology, 2025


13. For Future Students

If you are continuing this work:

  • Keep simulation settings constant
  • Always compare Existing vs Proposal
  • Pair density increases with required mitigation
  • Use simulations to support policy arguments, not just visuals

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How can the existing planning codes in climate migration receiving cities like Atlanta prepared to accommodate the anticipated population influx in terms of affordable housing and resilient infrastructure?

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