# Land Parcel Observations — Daily Sum Series + Two-Measure Correlation

> Land Parcel Observations — Daily Sum Series + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-30).

Computes daily sum time series and Pearson correlation between area_m2 and perimeter_m for up to 200 land parcel observation records.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-14-141?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-30
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/land-parcel-observations-daily-sum-series-two-measure-correlation-03f66ffd
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_-XlcnLHvo37yGCFz12ivL

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 land-parcel-observations-daily-sum-series-two-measure-correlation-03f66ffd -d '<json body>'
```

Example prompt: I have 4 land parcel observation records — row-1 on 2026-10-01 with area_m2=10 and perimeter_m=1 in group-a, row-2 on 2026-10-02 with area_m2=20 and perimeter_m=2 in group-b, row-3 on 2026-10-03 with area_m2=15 and perimeter_m=3 in group-a, and row-4 on 2026-10-04 with area_m2=30 and perimeter_m=4 in group-b — can you compute the daily sum series for area_m2 and also run the two-measure correlation between area_m2 and perimeter_m?

## When to prefer this

Choose this endpoint when you have raw land parcel observation data (area and perimeter measurements keyed by date and station group) and need both a daily aggregation time series and a statistical correlation between the two measures in a single low-cost call. It is ideal for offline/batch analytical pipelines where no live data lookup, external enrichment, or prediction is needed, and the dataset fits within 200 rows.

## Known failure modes

- More than 200 rows submitted — request rejected due to maxItems constraint
- Missing required fields (row_id, station_group, date, area_m2, perimeter_m) — validation error
- Malformed date strings not matching YYYY-MM-DD pattern — schema validation failure
- All null values for a measure — correlation computation may return null or NaN
- Empty rows array — minItems:1 constraint violation

## How this service works

Land parcel observations — Daily sum series + Two-measure correlation: Daily sum series + Two-measure correlation for supplied land parcel observations records (area_m2, perimeter_m). 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 reports: (1) a daily sum time series showing the summed value of the selected field (area_m2 or perimeter_m) grouped by date, and (2) a two-measure correlation coefficient between area_m2 and perimeter_m across all supplied rows. Both reports are computed locally from the submitted 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",
     "area_m2",
     "perimeter_m"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "area_m2": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "perimeter_m": {
      "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",
     "area_m2": 10,
     "perimeter_m": 1,
     "station_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "area_m2": 20,
     "perimeter_m": 2,
     "station_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "area_m2": 15,
     "perimeter_m": 3,
     "station_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "area_m2": 30,
     "perimeter_m": 4,
     "station_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "area_m2",
    "perimeter_m"
   ],
   "type": "string",
   "default": "area_m2"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/land-parcel-observations-daily-sum-series-two-measure-correlation-03f66ffd/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)