# Tree Canopy Observations — Numeric Distribution & Missing-Value Fill

> Tree Canopy Observations — Numeric Distribution & Missing-Value Fill 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).

Computes a numeric distribution summary and fills missing values for tree canopy observation records (canopy_m2, plot_m2) using local analytical engines.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-17-085?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-numeric-distribution-missing-value-fill-fc08aa9d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_KzFknmU0fj8rpkdyX0Ho_

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-numeric-distribution-missing-value-fill-fc08aa9d -d '<json body>'
```

Example prompt: I have up to 200 rows of tree canopy observation records with canopy_m2 and plot_m2 fields — can you run a numeric distribution report and fill any missing canopy_m2 values using the median method across my station groups?

## When to prefer this

Choose this endpoint when you have up to 200 rows of tree canopy or plot area observation records and need both a statistical distribution report and missing-value imputation in a single low-cost call. It is ideal for data cleaning and QA pipelines for environmental or urban forestry datasets where you already have the data in hand and do not need external lookups or real-time sensor data.

## Known failure modes

- Empty rows array or more than 200 rows causes a validation error
- Invalid date format (not YYYY-MM-DD) triggers a schema rejection
- Unrecognized field enum value (anything other than canopy_m2 or plot_m2) causes failure
- Unrecognized method enum value (anything other than zero, mean, median) causes failure
- Missing required fields (row_id, station_group, date) on any row causes rejection
- Payment of 0.01 USDC not provided or x402 auth failure blocks the request

## How this service works

Tree canopy observations — Numeric distribution + Explicit missing-value fill: Numeric distribution + Explicit missing-value fill 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 up to 200 supplied rows: (1) a numeric distribution summary (e.g. min, max, mean, percentiles, histogram-style breakdown) for the selected field (canopy_m2 or plot_m2), and (2) a missing-value-filled version of the dataset using the chosen method (zero, mean, or median). No external data is fetched; all analysis runs on the supplied rows.

## 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"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/tree-canopy-observations-numeric-distribution-missing-value-fill-fc08aa9d/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)