# Land Use Observations — String Normalisation + Exact Row Deduplication

> Land Use Observations — String Normalisation + Exact Row Deduplication is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).

Normalises strings and removes exact duplicate rows from land use observation records containing area_hectares and parcel_count fields, returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-economics-22-020?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/land-use-observations-string-normalisation-exact-row-deduplication-c8cf2f0d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_o2LO0l7LEufVnF9uY39gv

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-use-observations-string-normalisation-exact-row-deduplication-c8cf2f0d -d '<json body>'
```

Example prompt: I have a batch of up to 200 land use observation records with region names, dates, area_hectares, and parcel_count values — can you clean them up by normalising the strings and removing any exact duplicate rows, then give me two analytical reports on the results?

## When to prefer this

Choose this endpoint when you have land use observation data (area_hectares, parcel_count) up to 200 rows and need both string normalisation and exact row deduplication performed together in two analytical reports, with no need for live lookups, predictions, or external data enrichment. It is cost-effective at $0.01 USDC for two reports and suits batch data cleaning workflows before downstream analysis.

## Known failure modes

- Exceeding 200 row limit returns a validation error
- Missing required fields (row_id, region, date, area_hectares, parcel_count) causes rejection
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- Numeric values outside allowed range cause input rejection
- Empty rows array returns an error
- Payment not included or insufficient USDC triggers x402 payment required response

## How this service works

Land use observations — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication for supplied land use observations records (area_hectares, parcel_count). 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

Two independent analytical reports summarising the results of string normalisation and exact row deduplication applied to the submitted land use observation records (area_hectares, parcel_count) for up to 200 rows. Reports are generated locally with no external lookups or predictions.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/land-use-observations-string-normalisation-exact-row-deduplication-c8cf2f0d/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)