# Tree Canopy Observations — Numeric Interval Filter + IQR Outlier Flags

> Tree Canopy Observations — Numeric Interval Filter + IQR Outlier Flags 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).

Filters tree canopy observation records by a numeric interval and flags IQR-based outliers across up to 200 rows, returning two analytical reports for canopy_m2 or plot_m2 fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-17-130?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-25
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/tree-canopy-observations-numeric-interval-filter-iqr-outlier-flags-f9062395
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_k2eCgwtIAuZYf-6lKhKOY

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-interval-filter-iqr-outlier-flags-f9062395 -d '<json body>'
```

Example prompt: I have 150 tree canopy observation records with canopy_m2 and plot_m2 values — can you filter the canopy_m2 field to only keep rows between 0 and 500, and also flag any IQR outliers in those records? Here's the data: [rows array].

## When to prefer this

Choose this endpoint when you have tree canopy observation records (with canopy_m2 and plot_m2 fields) and need both range-based filtering and IQR outlier detection in a single call, without needing live data lookup, predictions, or external enrichment. Ideal for pre-analysis data cleaning, QA pipelines, and audit preparation on small-to-medium datasets (up to 200 rows).

## Known failure modes

- More than 200 rows submitted — request rejected or truncated
- Invalid date format (not YYYY-MM-DD) causes row validation failure
- Missing required fields (row_id, canopy_m2, plot_m2) causes schema rejection
- Minimum value greater than maximum value produces empty interval filter results
- All-null numeric field values may produce undefined IQR statistics
- Payment of 0.01 USDC not completed — endpoint returns 402 Payment Required

## How this service works

Tree canopy observations — Numeric interval filter + IQR outlier flags: Numeric interval filter + IQR outlier flags 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 interval filter report listing which records fall within the specified minimum/maximum range for the selected field (canopy_m2 or plot_m2), and (2) an IQR outlier detection report flagging records that fall outside the interquartile range. No external data is fetched; all analysis is performed on the submitted 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"
  },
  "maximum": {
   "type": "number",
   "default": 100,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  },
  "minimum": {
   "type": "number",
   "default": 0,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/tree-canopy-observations-numeric-interval-filter-iqr-outlier-flags-f9062395/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)