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Tree Canopy Observations — Daily Sum Series & Date-by-Category Pivot
x402
Tree Canopy Observations — Daily Sum Series & Date-by-Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).
Computes two local analytical reports on supplied tree canopy observation rows: a daily sum time series and a date-by-category pivot table, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Tree canopy observations — Daily sum series + Date by category pivot: Daily sum series + Date by category pivot 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 for the supplied rows: (1) a daily sum series showing the total of the selected field (canopy_m2 or plot_m2) for each date, and (2) a date-by-category pivot table breaking down totals by station_group across dates. Reports are computed locally without external lookups.
Example use cases
Urban tree survey time series
“I've got four months of daily tree canopy measurements from three monitoring stations — give me a daily sum series for canopy_m2 so I can see how total canopy coverage is trending over time.”
Station-group canopy pivot report
“Can you take my 150 rows of tree canopy observations and produce a date-by-station-group pivot table for canopy_m2 so I can compare how each group performs on each date?”
Plot area daily aggregation
“I need a daily sum series for plot_m2 from my urban greening survey records — I have 90 rows with row_id, date, station_group, canopy_m2, and plot_m2 filled in.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-17-143?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of tree canopy observation records and need both a daily sum time series and a date-by-category pivot computed analytically without any external data lookups, live forecasting, or professional assessment. It is ideal for offline batch analytics on structured canopy monitoring datasets where you want two complementary reports in a single low-cost call.
Side effects
- Exceeding 200 rows returns an error or truncates input
- Missing required fields (row_id, station_group, date, canopy_m2, plot_m2) cause validation failure
- Malformed date strings not matching YYYY-MM-DD pattern are rejected
- Numeric values outside ±1,000,000,000,000 bounds are rejected
- Empty rows array returns an error
- Invalid field enum value (not canopy_m2 or plot_m2) is rejected
- Payment failure (insufficient USDC) blocks request processing
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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