Depave Bridgeport

This map shows where Bridgeport carries the most non-essential pavement, and which neighborhoods stand to benefit most from removing it. It is a screening tool for turning heat-trapping, runoff-generating asphalt back into living ground.

Data tier 3 of 4 — Pre-classified land cover Bridgeport uses NOAA C-CAP 1-meter pre-classified impervious cover, OSM-only road widths (no surveyed widths), and a lidar topographic stormwater proxy without soil. Neighborhood-screening reliability, with thinner ancillary data than Tier 2. Tiers reflect input-data availability, not effort. Scores are relative within each city, so the tiers and the numbers are not comparable across cities, and reliability decreases from Tier 1 to Tier 4.

Why depaving matters

Pavement raises summertime temperatures and concentrates stormwater runoff. It also displaces the tree canopy that would otherwise cool streets and soak up rain. Some pavement is essential. Roads and sidewalks carry the movement a city depends on. Plenty of it is surplus, like parking aprons, oversized driveways, and the unused back lot behind a strip mall. The work begins by finding where that surplus sits and which neighborhoods carry the greatest environmental burden.

How we identify pavement

Bridgeport does not classify raw aerial imagery. It starts from a land-cover product that NOAA has already classified: the NOAA C-CAP High-Resolution Land Cover for coastal Connecticut, 1-meter resolution, 2016 vintage. We select the pixels NOAA labels class 2, Impervious Surface. That class covers hard surfaces in general, so it includes both pavement and roofs.

To isolate pavement, we subtract building footprints. The Microsoft US Building Footprints layer (2022) is differenced out of the impervious pixels, removing rooftops and leaving the ground-level hard surface. We then polygonize, clean the geometry, simplify, and drop slivers below 100 square feet. Everything outside the Bridgeport municipal boundary is clipped away. There is no machine-learning classifier in this pipeline; the impervious class comes pre-labeled from NOAA, which is the main difference from the Fort Lauderdale viewer.

To separate optional from essential pavement, we compare each piece against a "core" mask built from road centerlines and sidewalks. Highways are buffered to estimated lane widths, using the OpenStreetMap lanes tag where present and a class-based fallback otherwise. Sidewalks are buffered into the core mask. Service roads, driveways, and paths stay out of it. Anything inside the core mask is core pavement, and anything outside it is non-core, the pool of depave candidates. Unlike Fort Lauderdale, Bridgeport has no surveyed road-width dataset, so all widths are OSM estimates.

How we identify priority areas

For each of the city's 38 census tracts we compute four need scores, each normalized to a 0–1 scale:

Heat: mean land-surface temperature from a Landsat 9 thermal composite, averaged within each tract.
Stormwater flood risk: a proxy derived from lidar terrain. Where does water pond, and where do flow paths concentrate it?
Canopy deficit: one minus the fraction of the tract covered by tree canopy, from the ESA WorldCover tree class.
Pavement burden: non-core pavement area divided by tract area.

We average the four scores into a single composite and flag the top quartile (tracts at or above the 75th percentile) as priority tracts. Overlapping the priority tracts with the federal Climate and Economic Justice Screening Tool (CEJST) disadvantaged-community designation highlights the equity hotspots, the places where environmental need and historical disinvestment coincide.

Headline findings (approximate, latest pipeline run)

Approximately 4,468 acres of pavement citywide, of which about 2,886 acres (65%) are non-core and therefore candidates for depaving.
About 1,581 acres (35%) are core pavement: travel lanes, sidewalks, and similar essential surfaces.
10 of 38 tracts (about 26%) flagged as priority on the composite needs score.
33 tracts are CEJST-designated disadvantaged communities, and 10 of those also fall in the priority set, where equity and need overlap.

Key caveats

Pre-screening only. This tool scopes where to look first. Choosing specific parcels is a separate step, and site-level decisions require ground-truthing, utility checks, ownership review, and community input.
The pavement source is coarse and dated. NOAA C-CAP is 1-meter, pre-classified, 2016 vintage. Its impervious class lumps pavement and roofs together, so building subtraction is the only roof removal, and construction after 2016 may leak in or out. The data cannot tell asphalt from concrete.
The stormwater layer is a topographic proxy. It combines surface depressions and flow paths from lidar to rank where rainfall is most likely to pond, relative to the rest of the city. It uses no soil data, no drainage pipes, and no tide model, and it has not been validated against observed flooding. Coastal and tidal flooding is not captured. Read it as a screen for where to look first, not a flood forecast.
Road widths are estimates. Bridgeport has no surveyed road-width dataset, so the core mask relies entirely on OpenStreetMap lane counts and class-based widths. Mapping gaps and width errors propagate into the core/non-core split.
Small sample. With 38 tracts, min-max normalization and percentile tiers are sensitive to outliers. Read the scores as relative rankings within Bridgeport.

For the full technical methodology, including data sources, algorithms, and known limitations, see the detailed methodology.