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Tree Canopy Observations — Base-100 Series & Secondary-Measure Weighted Mean
x402
Tree Canopy Observations — Base-100 Series & Secondary-Measure Weighted Mean 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).
Computes a Base-100 index series and a plot_m2-weighted mean for supplied tree canopy observation records (canopy_m2, plot_m2) across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Tree canopy observations — Base-100 series + Secondary-measure weighted mean: Base-100 series + Secondary-measure weighted mean 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 Base-100 index series normalizing the chosen field (canopy_m2 or plot_m2) relative to the specified base_index row, showing relative change per row; and (2) a secondary-measure weighted mean where each row's value is weighted by the complementary field. Results cover all submitted rows (up to 200) and are computed locally without external lookups.
Example use cases
Urban canopy trend indexing for city planners
“I'm tracking tree canopy coverage across 8 urban monitoring plots over 6 months. Can you normalize the canopy_m2 values into a Base-100 index starting from row 1 (the January baseline) and also give me the plot-area-weighted mean? Here are the records by date and station group.”
Forestry restoration progress benchmarking
“We planted trees across 3 restoration zones and recorded canopy area and plot size every quarter. Can you index the canopy_m2 readings relative to the first quarter (base_index=0) and compute a plot_m2-weighted average canopy so we can see how much coverage has grown?”
Research dataset summary for ecological study
“I have canopy observation data for 50 sample plots split into two station groups — control and treatment. Can you produce a Base-100 series on canopy_m2 anchored at row 0 and a secondary weighted mean using plot_m2 as the weight, so I can include both reports in my ecological analysis?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-17-166?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have raw tree canopy observation records (canopy area and plot area in m²) and need both a time-series Base-100 normalization and a plot-area-weighted aggregate in a single call. It is particularly well-suited for ecological, forestry, or urban greening analyses where relative indexing and weighted summarization of canopy coverage data are needed without external data sources or predictions.
Side effects
- Rows exceeding 200 items will be rejected — keep input within maxItems limit
- Missing required fields (row_id, station_group, date, canopy_m2, plot_m2) will cause validation errors
- Invalid date format (must be YYYY-MM-DD) will fail schema validation
- base_index out of range (must be 0–199 and within submitted row count) will cause errors
- Null values for canopy_m2 or plot_m2 may affect weighted mean computation
- Payment failure or insufficient USDC balance will block the request
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
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