Houston Floodplain & Repetitive Loss
Floodplain designations and repetitive-loss properties to understand flood risk.
Data Detective
TipScan the map for red dots and check the chart for spikes. Big jumps or drops are usually where the interesting questions live.
Source: The numbers above come straight from Houston Open Data.
π Data quality breakdown
How healthy is this dataset across five dimensions?
πΊοΈ Where the data lives
Up to 300 geolocated records. Red markers are flagged values.
π Activity over time
Record volume by month, or by status when no dates exist.
π© Open red flags
Suspicious values our scanner caught β see if you agree.
This record is dated in the future.
Next step: Check for a typo or a time-zone/format bug at the source.
This record is dated in the future.
Next step: Check for a typo or a time-zone/format bug at the source.
This record is dated in the future.
Next step: Check for a typo or a time-zone/format bug at the source.
A count or amount is negative where that should be impossible.
Next step: Confirm whether negatives represent refunds/corrections or are simply errors.
A count or amount is negative where that should be impossible.
Next step: Confirm whether negatives represent refunds/corrections or are simply errors.
A count or amount is negative where that should be impossible.
Next step: Confirm whether negatives represent refunds/corrections or are simply errors.
The field "reported_by" is empty in 33% of records.
Next step: Ask the owning department why this field is so often blank.
Coordinates are missing, 0/0, or outside the Houston area.
Next step: Re-geocode the address or drop the broken point from maps.
β οΈ Known issues
- β’Updated infrequently
- β’Boundaries simplified
π‘ Public use cases
- β’Check flood risk by area
- β’Find repeat-loss clusters
- β’Plan resilience investments
π Geo fields
π Time fields
Records: 300
Update frequency: annual
Last imported: 23 hours ago