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q57·intermediate

Who and what is exposed in this hazard zone?

citieshazards Datasets: 4 15–35 min
◇ Real events · NASA Disasters / VEDA

Analysis-ready products for actual events that this question maps to — open each in the catalog, or browse them on the NASA Disasters Portal.

Texas Flood Zone: 100-Year Flood Risk Areas (2025)
tx-flood-100-yr-recurrence · VEDA
Texas Flood Zone: 10-Year Flood Risk Areas (2025)
tx-flood-10-yr-recurrence · VEDA
Texas Flood Zone: 500-Year Flood Risk Areas (2025)
tx-flood-500-yr-recurrence · VEDA
▶ Find the data for your area

Draw a rectangle to pick your area of interest, then see what NASA data covers it (live, here in your browser) or download a ready-to-run notebook with your AOI pre-filled. The notebook runs in any Python environment — it needs a free Earthdata Login to fetch the data.

Current AOI: -95.8, 29.5 → -95, 30.1 (Greater Houston, Texas)

Before a disaster strikes, the question is *who is in harm's way.* You overlay the hazard footprint onto where people live and what's built — turning a hazard map into an **exposure** map that drives preparedness.

Before a disaster strikes, the question is who is in harm’s way. You overlay the hazard footprint onto where people live and what’s built — turning a hazard map into an exposure map that drives preparedness.

What you can answer

  • How many people are exposed. Intersect a hazard zone (e.g. a 100-year flood layer) with WorldPop population and count the people inside.
  • What’s built there — EO-derived building footprints and exposure layers add the physical assets at risk.
  • Which neighbourhoods to prioritise — rank by exposed population × hazard likelihood for mitigation and evacuation planning.

What you can NOT answer (be careful)

  • Vulnerability ≠ exposure. This counts who’s in the zone, not who’s most vulnerable (age, income, mobility) — pair with social-vulnerability data (e.g. SEDAC/CDC SVI).
  • Exact asset values — building exposure is a proxy, not an appraisal.
  • Future population — these are present-day snapshots; growth changes exposure.

How you’d approach it

Load a hazard layer for your AOI, overlay WorldPop and building footprints, and sum exposed population and structures by zone. This is the Prepare / Build-Resilience workhorse — see the free companion data (WorldPop, geoBoundaries) the atlas already lists. Supports the NASA Disasters program.

⚲ How a scientist answers this
Parameters
Hazard footprint as a binary/return-period layer (e.g. 100-year flood extent, or 10/100/500-year recurrence); exposed population from WorldPop gridded counts (~100 m); built assets from EO-derived building footprints/exposure layers; SEDAC GPW/settlement layers as a cross-check. Output units: persons and structures inside the zone.
Method
Reproject all layers to a common equal-area grid, intersect (mask) the hazard footprint with WorldPop and building footprints, and area-weight/sum population and structure counts inside the zone; rank sub-areas by exposed population × hazard likelihood for prioritisation.
Validation
Cross-check WorldPop totals against SEDAC GPW and national census, state the return-period and disaggregation baseline, and flag that exposure (who is in the zone) is not vulnerability — pair with social-vulnerability indices (SEDAC/CDC SVI) and note present-day snapshot limits.
In plain EnglishLay the hazard zone over a population grid and building map, then count how many people and structures fall inside it, ranking neighbourhoods by risk.

Make it yours → Swap in your AOI and chosen return-period hazard layer, and set the ranking weights in the notebook.

⌨ Run the core method · no login

The detection / counting above a threshold at the heart of this question — runnable on synthetic data, right here. The full earthaccess code template further down does it on real NASA data (needs an Earthdata login).

editable · runs in your browser