# Tree Canopy Observations — Two-Measure Correlation + Date by Category Pivot

> Tree Canopy Observations — Two-Measure Correlation + 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 2026-10-26).

Runs two analytical reports on supplied tree canopy observation data: a correlation analysis between canopy_m2 and plot_m2 measures, and a date-by-station-group pivot table.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-17-182?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-26
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/tree-canopy-observations-two-measure-correlation-date-by-category-pivot-4bf9e866
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_EEaUa-g25bbbVs1xDSkPZ

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability tree-canopy-observations-two-measure-correlation-date-by-category-pivot-4bf9e866 -d '<json body>'
```

Example prompt: I have up to 200 rows of tree canopy survey records with canopy_m2 and plot_m2 measurements, dates, and station groups — can you run a correlation between canopy_m2 and plot_m2 AND give me a pivot of canopy_m2 values broken down by date and station group?

## When to prefer this

Choose this endpoint when you need both a pairwise correlation between canopy_m2 and plot_m2 AND a date-by-category pivot from the same batch of up to 200 tree canopy observation records in a single low-cost call ($0.01 USDC). It is ideal for environmental monitoring, urban forestry, or ecological research workflows where you supply your own data and want offline statistical summaries without any live data lookup or external prediction.

## Known failure modes

- Exceeds 200-row limit — request rejected with validation error
- Missing required fields (row_id, date, canopy_m2, plot_m2, station_group) in any row causes schema validation failure
- Malformed date strings not matching YYYY-MM-DD pattern rejected
- Null values in both numeric fields for all rows may produce degenerate correlation result
- Payment of 0.01 USDC not completed results in 402 Payment Required response
- Empty rows array (minItems:1 violated) causes validation error

## How this service works

Tree canopy observations — Two-measure correlation + Date by category pivot: Two-measure correlation + 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 independent analytical reports: (1) a two-measure correlation result between canopy_m2 and plot_m2 (including correlation coefficient and supporting statistics), and (2) a date-by-station-group pivot table summarizing the selected field (canopy_m2 or plot_m2) across all supplied rows. Both reports are computed locally using shared analytical engines on the provided data, with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "station_group",
     "date",
     "canopy_m2",
     "plot_m2"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "plot_m2": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "canopy_m2": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "station_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "plot_m2": 1,
     "canopy_m2": 10,
     "station_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "plot_m2": 2,
     "canopy_m2": 20,
     "station_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "plot_m2": 3,
     "canopy_m2": 15,
     "station_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "plot_m2": 4,
     "canopy_m2": 30,
     "station_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "canopy_m2",
    "plot_m2"
   ],
   "type": "string",
   "default": "canopy_m2"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/tree-canopy-observations-two-measure-correlation-date-by-category-pivot-4bf9e866/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)