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Land Parcel Observations — String Normalisation + Two-Measure Correlation
x402
Land Parcel Observations — String Normalisation + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Normalises string fields and computes a two-measure correlation analysis (area_m2 vs perimeter_m) for up to 200 land parcel observation records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Land parcel observations — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied land parcel observations records (area_m2, perimeter_m). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Two analytical reports: (1) a string normalisation report cleaning the station_group and other string fields across the submitted rows, and (2) a two-measure correlation report quantifying the statistical relationship between area_m2 and perimeter_m across up to 200 rows. No external lookups or predictions are included.
Example use cases
Parcel survey data quality check
“I've got a batch of land parcel survey records with area in square metres, perimeter in metres, and site group names that need cleaning — can you normalise the group strings and tell me how strongly area and perimeter correlate across the 150 rows?”
Agricultural plot measurement analysis
“Here are 80 agricultural plot observations with area_m2, perimeter_m, and farm group labels across several dates — run string normalisation on the group names and give me a correlation report between the two numeric measures.”
Urban planning parcel dataset cleanup
“I'm preparing a land-use dataset with parcel area and perimeter readings from multiple station groups — can you clean up the station group strings and compute the correlation between area_m2 and perimeter_m for these 200 rows?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-14-033?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have land parcel observation records (with area_m2 and perimeter_m) that need both string field normalisation and a statistical correlation between the two numeric measures in a single cheap call. It is ideal for batch pre-processing of survey or cadastral data before downstream modelling. It is not suitable for real-time lookups, external data enrichment, geospatial operations, or datasets exceeding 200 rows.
Side effects
- More than 200 rows submitted — request rejected with validation error
- Missing required fields (row_id, date, area_m2, perimeter_m, station_group) cause row-level errors
- Malformed date strings not matching YYYY-MM-DD pattern rejected
- All-null numeric columns may prevent meaningful correlation computation
- Payment failure returns 402 before processing begins
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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