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Tree Canopy Observations — Record Quality Audit + Daily Sum Series
x402
Tree Canopy Observations — Record Quality Audit + Daily Sum Series 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).
Runs two analytical reports on supplied tree canopy observation data: a record quality audit and a daily sum series, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Tree canopy observations — Record quality audit + Daily sum series: Record quality audit + Daily sum series 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 independent analytical reports: (1) a record quality audit identifying issues such as missing values, out-of-range entries, or malformed records across the supplied rows; and (2) a daily sum series aggregating the selected field (canopy_m2 or plot_m2) by date across all supplied records. Both reports are computed locally without external lookups.
Example use cases
Urban forestry data quality check
“I've collected tree canopy survey data from two station groups over the past month — can you audit the record quality and also give me a daily sum series for canopy_m2? I have about 80 rows with date, row_id, station_group, canopy_m2, and plot_m2 values.”
Daily canopy coverage aggregation
“I need a daily sum series for plot_m2 across all my canopy observation records — here are 150 rows from our monitoring stations covering Q3 2025. Can you also flag any quality issues in the records at the same time?”
Canopy monitoring pipeline validation
“Before I publish my tree canopy dataset, can you run both a record quality audit and a daily sum series on these 200 rows? The data has station_group, date, canopy_m2, and plot_m2 fields and I want the aggregation focused on canopy_m2.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-17-009?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a data quality audit and a daily sum series on tree canopy or plot area observation data in a single low-cost call. It is ideal for environmental data pipelines where you want to validate record integrity and produce daily aggregates simultaneously, without requiring any external data sources or live lookups. Best suited for batch sizes up to 200 rows per call.
Side effects
- Fewer than 1 or more than 200 rows supplied — input rejected
- Missing required fields (row_id, station_group, date, canopy_m2, plot_m2) on any row — validation error
- Invalid date format (not YYYY-MM-DD) — pattern mismatch error
- Payment not provided or insufficient — 402 payment required
- Numeric values outside allowed range (-1e12 to 1e12) — schema validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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