# Tree Canopy Observations — Record Quality Audit + Adjacent Row Changes

> Tree Canopy Observations — Record Quality Audit + Adjacent Row Changes 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).

Runs a record quality audit and adjacent row change report on up to 200 tree canopy observation records (canopy_m2, plot_m2) using local analytical engines — no external lookups or predictions.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-17-011?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-24
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/tree-canopy-observations-record-quality-audit-adjacent-row-changes-501db23f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_6ApON_0UJuQxVEXDHW6KH

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-record-quality-audit-adjacent-row-changes-501db23f -d '<json body>'
```

Example prompt: Can you run a record quality audit and adjacent row change report on my tree canopy observation data? I have 4 rows with station groups 'group-a' and 'group-b', dates from 2026-10-01 to 2026-10-04, and I want to audit the canopy_m2 field.

## When to prefer this

Choose this endpoint when you need simultaneous record quality auditing AND adjacent row change detection on tree canopy observation data (canopy_m2, plot_m2) in a single low-cost call. It is ideal for pre-analysis validation of environmental monitoring datasets up to 200 rows where no external lookup, live data, or professional assessment is needed. Prefer it over generic data validation tools when your data specifically involves canopy area and plot area measurements with station group and date dimensions.

## Known failure modes

- More than 200 rows submitted — request rejected with validation error
- Missing required fields (row_id, date, canopy_m2, plot_m2) — row-level validation failure
- Invalid date format not matching YYYY-MM-DD pattern — schema rejection
- Invalid field selector value not in enum [canopy_m2, plot_m2] — schema error
- Empty rows array — minItems constraint violation
- Payment not included or insufficient — x402 payment required response

## How this service works

Tree canopy observations — Record quality audit + Adjacent row changes: Record quality audit + Adjacent row changes 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 reports for the submitted rows: (1) a record quality audit identifying missing values, invalid entries, or format issues in the canopy_m2 or plot_m2 fields; and (2) an adjacent row change report showing value differences between consecutive rows for the selected field, grouped by station and date. All analysis is performed locally with no external data 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-record-quality-audit-adjacent-row-changes-501db23f/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)