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Tree Canopy Record Quality Audit and Two-Measure Correlation
x402
Tree Canopy Record Quality Audit and 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 2026-10-25).
Audits quality of tree canopy observation records and computes correlation between canopy_m2 and plot_m2 measurements for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Tree canopy observations — Record quality audit + Two-measure correlation: Record quality audit + Two-measure correlation for supplied tree canopy observations records (canopy_m2, plot_m2). 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
Returns two analytical reports: (1) a record quality audit identifying missing values, outliers, or format issues across the supplied canopy observation rows, and (2) a statistical correlation analysis between the canopy_m2 and plot_m2 fields. No external data is fetched; all analysis is performed locally on the supplied rows.
Example use cases
Pre-analysis data quality check
“Before I run any models, can you do a quality audit on my tree canopy dataset and tell me if any of the canopy_m2 or plot_m2 values look suspicious? I have 50 rows from station groups north-1 and north-2 collected in October 2026.”
Correlation check for field survey
“I collected canopy area and plot area measurements across 120 field sites — can you compute the correlation between canopy_m2 and plot_m2 and also flag any records that have data quality issues? The rows span station groups A through D and dates from 2026-09-01 to 2026-09-30.”
Vegetation monitoring data validation
“We just finished a vegetation monitoring survey and I want to run a record quality audit plus a canopy-to-plot correlation report on all 200 observation rows before handing the dataset off to the research team.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-17-015?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tree canopy observation records with canopy_m2 and plot_m2 columns and need both a data quality audit and a two-measure correlation in a single low-cost call. It is best suited for offline, batch-style analytical checks on up to 200 rows of supplied data where no live data lookup, prediction, or external enrichment is needed.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, canopy_m2, plot_m2) cause validation errors
- Invalid date format (not YYYY-MM-DD) triggers schema rejection
- Null values in both canopy_m2 and plot_m2 across all rows may prevent correlation computation
- Payment of 0.01 USDC not provided or rejected via x402 protocol
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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