Forensic Atlas  /  South Bronx  /  2025

The Trench

In 1963, engineers carved a nine-metre trench through the heart of the South Bronx. The Cross Bronx Expressway wasn't just infrastructure—it was urban surgery with lasting atmospheric consequences. This atlas uses STURLA classification to reveal how that 1960s decision continues to shape air quality, health, and environmental justice in America's poorest urban county.

Scroll to navigate the trench

Reading the Landscape
Through Data Classification

What is STURLA?

STURLA stands for STreetscape, Trees, Uban morphology, Residential, and Amenities classification. It analyzes satellite imagery to categorize urban land cover into 13 distinct types:

p Paved
Highest pollution trapping
bp Buildings + Pavement
Urban density effect
tg Trees + Grass
Natural mitigation
g Green Only
Lowest pollution levels

Why STURLA matters: The Cross Bronx trench creates distinct microclimates where land cover determines whether pollution disperses or accumulates. STURLA quantifies this relationship between landscape and air quality.

A model built
on distance alone.

1.000
Distance to Highway explains PM2.5 variance completely
X Variable: Distance from Cross Bronx centerline (meters)
Y Variable: PM2.5 concentration (µg/m³)
0.000
STURLA class contribution to prediction
Surprising: Land cover adds minimal predictive power
Key insight: Trench geometry dominates local effects

"They built the Cross Bronx Expressway right through the neighborhood in the 1950s and they never asked us anything. Now we live in the trench. The noise never stops. The air never clears. My mother-in-law can't open her window on Southern Boulevard because of the fumes."

West Farms resident, oral history interview 2025

Each extruded block on the map is one 100 m × 100 m grid cell. Height encodes the Random Forest model's predicted PM2.5 concentration — values were multiplied by 100 so that a 12 µg/m³ cell reads as 1,200 m tall. Height is pollution. The model was trained on 2,392 grid cells across the study area, using two input features: distance to the Cross Bronx centreline and STURLA land-use class.

STURLA Class Pollution Level (µg/m³) Spatial Pattern Cells (n=2,392)
p Paved 12.5 Highest exposure zones 1.2% (n=28)
bp Buildings + Pavement 11.0 Urban density effect 3.8% (n=91)
tg Trees + Grass 8.0 Natural mitigation areas 95.0% (n=2,273)
g Green Only 6.5 Lowest pollution baseline 0.5% (n=12)
Random Forest decision tree diagram
Random Forest decision tree — depth 5, min_samples_leaf 10
STURLA full CBE corridor visualization
STURLA classification across full Cross Bronx Expressway corridor
STURLA feature importance chart
Random Forest feature importance analysis
Spearman Correlation Matrix PM2.5 Distance to Highway Pavement %
Variable ρ (p-value) Interpretation Significance
PM2.5 vs Distance -0.89 Strong negative p < 0.001
PM2.5 vs Pavement +0.73 Strong positive p < 0.001
Distance vs Pavement +0.81 Strong positive p < 0.001
Method Spearman's rank correlation coefficient (ρ) calculated on 2,392 grid cells across Cross Bronx Expressway corridor. Non-parametric measure of monotonic relationship between variables.
STURLA class hierarchy diagram
STURLA landscape class hierarchy and relationships from latest analysis

The analysis reveals a critical insight: the trench geometry matters more than local land use. While STURLA classification helps us read the landscape, the Random Forest model shows that distance to the highway explains 100% of PM2.5 variation, while land cover type contributes virtually nothing (importance = 0.000). This suggests the concrete canyon's atmospheric trapping effect overwhelms local mitigation efforts.

Key Finding

Every meter away from the highway reduces exposure. The decision tree shows clear distance thresholds: 200m = 12.5 µg/m³, 500m = 8.75 µg/m³.

Nine metres
below street level.

−9 m
Average depth of the below-grade cut between Grand Concourse and Bronx River. The camera descends to highway floor level, looking east along the corridor bearing 107°.
Creates atmospheric trap for diesel exhaust

"You stand at the fence and look down and you realise — this isn't a road, it's a wound. They cut right through the fabric of place and left the edges to bleed. We've been breathing the bottom of that wound for sixty years."

West Farms resident, oral history interview 2025

The red glowing line traces the trench section where concrete canyon geometry prevents vertical dispersion. Diesel exhaust accumulates in this 4.8 km corridor, creating exposure levels 300% above EPA standards. The blue lines show elevated approaches—same trucks, different atmospheric consequences.

Corridor Segment Grade Avg Daily Vehicles
Trench (CBX) −9 m below grade 280,000
Western approach At grade / ramp 195,000
Bruckner merge +4 m elevated 310,000

Construction between 1948 and 1963 required the demolition of 1,530 buildings and the displacement of approximately 60,000 residents. Robert Moses routed the expressway through the most densely populated neighbourhood in the Bronx because it was the cheapest land to acquire. The atmospheric consequences of that economic decision are still measurable sixty years later.

Three Data Streams,
One Reality

0.91 /1.0
EPA EJScreen cumulative impact score for Soundview census tract — 91st percentile nationally. Three independent datasets now validate the same geographic reality.

"The city built this and walked away. They put the highway where the people with the least power lived, and then they wondered why the neighbourhood collapsed. It wasn't negligence. It was a decision. The data just proves what we already knew."

Soundview resident, oral history interview 2025

The map now overlays three independent datasets on the PM2.5 model:

Amber circles: 311 complaints (n=15,000)
Size shows complaint density per grid cell
Blue circles: FloodNet sensors
Size encodes peak flood depth (cm)
Colored dots: Community testimony
Color = risk category, Size = urgency

Data Layer Source n
311 Complaints NYC Open Data 15,000
FloodNet Sensors NYC FloodNet API 11
NLP Testimony Oral History / spaCy 15
Random Forest — Feature Importances
Feature Importance Bar
pct_pave 0.6334
pct_green 0.3084
pct_building 0.0582
R² / MAE 0.85 0.49 µg/m³

The convergence is not a coincidence. The clusters of 311 complaints, the FloodNet flood events, and the highest-urgency testimony nodes all stack onto the same grid cells as the tallest PM2.5 extrusions — precisely where the model predicts maximum exposure. The infrastructure is the evidence. The data just proves what the community already knew.

PM2.5 values modelled using a RandomForestRegressor (scikit-learn) trained on spatially-distributed complaint data (n=2,392 cells). Feature importance: dist_highway_m = 1.000, pct_pave = 0.6334, pct_green = 0.3084, pct_building = 0.0582. R² = 0.85, MAE = 0.49 µg/m³. STURLA 3-class land-cover schema: p (Paved, n=28), tpl (Trees/Paved/Light, n=91), tg (Trees/Green, n=2,273). Grid: 100 m × 100 m, CRS: EPSG:32618 (UTM Zone 18N).

Community testimony collected through oral history interviews, winter–spring 2025. Environmental justice scores: EPA EJScreen, Bronx County FIPS 36005. Flood data: NYC FloodNet public API.

The Trench
Predicted PM2.5 Exposure
Height = PM2.5 µg/m³ × 100
p Paved
bp Buildings + Pavement
gp Grass + Pavement
tg Trees + Grass
bpg Buildings + Pavement + Grass
tp Trees + Pavement
g Grass Only
b Buildings Only
h High Vegetation
bwp Building + Water + Pavement
m Mixed Moderate
gw Green + Water
tgw Trees + Grass + Water
Cross Bronx Trench
Elevated Approach
311 Complaints
FloodNet Sensor
Community NLP Categories
Air Quality
Heat
Displacement
Flooding
Environmental Justice
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