Thai
Flood
Risk

Methodology & sources

How we calculate a flood risk score, and where the underlying data comes from.

What this score is (and isn't)

Every report is a free, automated estimate built entirely from public data. It's designed to give you a starting point before you buy or rent — not a professional flood survey, an insurance assessment, or legal advice. Always confirm anything decision-critical with a licensed surveyor or local authority.

Three factors, weighted

The overall score (0–100, lower is safer) combines three factors: elevation (40%), flood history (35%), and distance to the nearest canal or river (25%). These weights are expert-assigned starting points — not yet calibrated against confirmed flood zones — and we're upfront about that rather than presenting them as scientifically proven.

Elevation (weight 40%): ground height relative to sea level, from 30m-resolution SRTM data (OpenTopoData). Bangkok's average elevation is about 1.5m, so the bands are calibrated to that context — at or below sea level scores the highest risk (100), above 10m scores the lowest (5).

Flood history (weight 35%): number of years with a recorded flood event at that location, from GISTDA's public flood-recurrence data. Zero recorded years scores 10 (low), 3+ years scores 90 (high).

Distance to nearest canal/river (weight 25%): closer waterways score higher risk — under 100m scores 80, over 1km scores 15. Search radius is 3km; nothing found within that radius is treated as low risk for this factor specifically, not as missing data.

When data is missing

Two of our data sources (GISTDA and OpenStreetMap/Overpass) are free public APIs without guaranteed uptime. When a factor's data is unavailable for a given point, we never fabricate a value — we exclude that factor entirely and redistribute its weight across the remaining factors, so the score always stays on a consistent 0–100 scale. Every report lists exactly which factors were excluded and why.

Not included yet: drainage area

Local drainage capacity and pumping-station coverage meaningfully affect real flood risk — a well-maintained canal with active pumps can offset what its proximity alone would suggest. We don't yet have a validated public data source for this, so it's listed as an excluded factor on every report rather than guessed at.

Data sources

GISTDA historical flood recurrence data (Open Data Common license)

OpenTopoData / SRTM 30m ground elevation

OpenStreetMap canals, rivers, and other waterways, via the Overpass API

OpenGISData-Thailand administrative boundaries (tambon/district/province)

Limitations

This is a young, actively developed tool. The fixed weights above are a reasonable starting point, not a scientifically calibrated model — we plan to refine them against known flood-prone and flood-safe reference addresses over time. Programmatic pages (Bangkok districts, tourist destinations) use a single representative coordinate for that area, not every address within it — for a specific building or plot, always search its exact address.

Flood history relies on satellite-detected flooding (GISTDA) — reliable for large, sustained flooding, but it can miss brief, localized events, like a road flooded for a few hours after heavy rain, that don't leave a water body large or lasting enough to be visible from space. A location with zero recorded years means no satellite-detected flooding was registered there — not a guarantee the area has never flooded.