# USDA Cropland Data Layer Farmland & Land-Cover Screener (`malonestar/usda-cdl-farmland-siting-screener`) Actor Farmland & land-cover API: batch coordinates to USDA Cropland Data Layer class (Corn, Soybeans, Developed, Forest, Water), an active-cropland flag, and a prime-farmland proxy. For solar-siting, land-use diligence, and farmland-protection screening. Keyless, MCP-ready. Prime-farmland is a proxy. - **URL**: https://apify.com/malonestar/usda-cdl-farmland-siting-screener.md - **Developed by:** [Kyle Maloney](https://apify.com/malonestar) (community) - **Categories:** Real estate, Developer tools, Agents - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $3.85 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## USDA Cropland Data Layer Farmland & Siting Screener Classifies a batch of coordinates against the USDA Cropland Data Layer (CDL) and returns, per site, the land-cover class, an active-cropland flag, and a prime-farmland proxy. Aimed at solar and wind site developers, land-use diligence teams, and ag lenders who need to know whether a candidate parcel is in active crop production before they act on it. ### How it works For each site you supply (`lat`/`lon`, WGS84), the actor projects the point into the CDL's native CONUS Albers Equal Area projection (EPSG:5070) and samples it through USDA's public CropScape `GetCDLValue` point service (`nassgeodata.gmu.edu`). No API key, no login, no scraping. The CDL is a ~30 m annual satellite crop-classification raster; the sampled pixel gives you the class code (1 = Corn, 5 = Soybeans, 176 = Grassland/Pasture, 121–124 = Developed, 141–143 = Forest, 111 = Open Water, 0 = No Data outside CONUS). Coverage is the Contiguous US. A point in the ocean or outside CONUS returns a valid `No Data` row, not an error, and a single bad coordinate produces an ERROR row without failing the run. Years 2008–2025 are available; default is 2024. ### Example input ```json { "assets": [ { "lat": 42.45, "lon": -93.55, "label": "Iowa cornfield" }, { "lat": 42.30, "lon": -94.20, "label": "Iowa soybean field" }, { "lat": 40.75, "lon": -73.98, "label": "Manhattan, NY (developed)" } ], "year": 2024 } ```` ### Key output fields (one row per site) - `cdl_code` — raw USDA CDL class code (0–255) at the point. - `land_cover_class` — the human-readable name for that code (Corn, Soybeans, Developed/Medium Intensity, Deciduous Forest, and so on). - `category` — coarse bucket: cropland, pasture, forest, developed, water, or other. - `is_active_cropland` — true when the pixel is a cultivated crop (field/row crops, orchards, specialty and double crops; grassland/pasture, forest, developed, and water are excluded). - `prime_farmland_flag` — a proxy that equals `is_active_cropland`; see the caveat below. - `prime_farmland_basis` — how that flag was derived, in plain language. - `cdl_color` — the official CDL legend hex color for map rendering. - `albers_x`, `albers_y` — the EPSG:5070 coordinate actually sampled. - `cdl_year`, `source_url`, `citation`, `checked_at`, `error`, `disclaimer`. ### About the prime-farmland flag The CDL does not carry the legal "prime farmland" soil classification — that lives in NRCS SSURGO as the `farmlndcl` attribute. So `prime_farmland_flag` is a transparent proxy: true when the point is in active crop production, which strongly indicates farmland but is not a substitute for an SSURGO determination. For an authoritative answer (for example, a Farmland Protection Policy Act / AD-1006 review), use NRCS Web Soil Survey / SSURGO. ### Who uses it - Solar and renewable-energy developers screening candidate parcels for active cropland or farmland-conversion sensitivity before acquisition. - Land-use and environmental diligence teams (Phase I / ESA-adjacent) needing a fast land-cover read at many coordinates. - Ag lenders, appraisers, and CRE analysts checking whether collateral is productive cropland. - Farmland-protection and conservation planners flagging active-cropland parcels. - AI agents needing a coordinate-to-land-cover lookup. ### Use as an MCP tool This is a Pay-Per-Result API with field-level output descriptions, so AI agents (Claude, Cursor, and others) can call it over mcp.apify.com as a coordinate-to-land-cover tool. Empty input costs nothing beyond the actor start. ### FAQ **Is this the legal prime-farmland determination?** No. It is a CDL active-cropland proxy; use NRCS SSURGO for the authoritative soil class. **Does it need an API key?** No. The CropScape service is public and keyless. **What happens for an ocean or non-US point?** You get a valid `No Data` (code 0, category `other`) row, not an error. **How is billing calculated?** One dataset row per site. # Actor input Schema ## `assets` (type: `array`): List of coordinates to classify against the USDA Cropland Data Layer. Each item is an object: {"lat": \, "lon": \, "label": ""}. Coverage is the Contiguous United States (CONUS); points outside CONUS return a valid 'No Data' row. Each site produces exactly one billable dataset row. Invalid points produce an ERROR row and the run continues. ## `year` (type: `integer`): USDA Cropland Data Layer vintage year to sample (national CDL is published annually). Values are clamped to 2008-2025; the most recent fully published year is recommended. Default 2024. ## `maxAssets` (type: `integer`): Safety cap on the number of sites classified per run. Sites beyond this cap are skipped with a warning. ## Actor input object example ```json { "assets": [ { "lat": 42.45, "lon": -93.55, "label": "Iowa cornfield (active cropland)" }, { "lat": 42.3, "lon": -94.2, "label": "Iowa soybean field" }, { "lat": 40.75, "lon": -73.98, "label": "Manhattan, NY (developed)" } ], "year": 2024, "maxAssets": 500 } ``` # Actor output Schema ## `results` (type: `string`): The default dataset with one CDL land-cover row per site. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "assets": [ { "lat": 42.45, "lon": -93.55, "label": "Iowa cornfield (active cropland)" }, { "lat": 42.3, "lon": -94.2, "label": "Iowa soybean field" }, { "lat": 40.75, "lon": -73.98, "label": "Manhattan, NY (developed)" } ], "year": 2024 }; // Run the Actor and wait for it to finish const run = await client.actor("malonestar/usda-cdl-farmland-siting-screener").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "assets": [ { "lat": 42.45, "lon": -93.55, "label": "Iowa cornfield (active cropland)", }, { "lat": 42.3, "lon": -94.2, "label": "Iowa soybean field", }, { "lat": 40.75, "lon": -73.98, "label": "Manhattan, NY (developed)", }, ], "year": 2024, } # Run the Actor and wait for it to finish run = client.actor("malonestar/usda-cdl-farmland-siting-screener").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "assets": [ { "lat": 42.45, "lon": -93.55, "label": "Iowa cornfield (active cropland)" }, { "lat": 42.3, "lon": -94.2, "label": "Iowa soybean field" }, { "lat": 40.75, "lon": -73.98, "label": "Manhattan, NY (developed)" } ], "year": 2024 }' | apify call malonestar/usda-cdl-farmland-siting-screener --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=malonestar/usda-cdl-farmland-siting-screener", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "USDA Cropland Data Layer Farmland & Land-Cover Screener", "description": "Farmland & land-cover API: batch coordinates to USDA Cropland Data Layer class (Corn, Soybeans, Developed, Forest, Water), an active-cropland flag, and a prime-farmland proxy. For solar-siting, land-use diligence, and farmland-protection screening. Keyless, MCP-ready. Prime-farmland is a proxy.", "version": "1.0", "x-build-id": "03PYpiJvRKzNjoscX" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/malonestar~usda-cdl-farmland-siting-screener/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-malonestar-usda-cdl-farmland-siting-screener", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/malonestar~usda-cdl-farmland-siting-screener/runs": { "post": { "operationId": "runs-sync-malonestar-usda-cdl-farmland-siting-screener", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/malonestar~usda-cdl-farmland-siting-screener/run-sync": { "post": { "operationId": "run-sync-malonestar-usda-cdl-farmland-siting-screener", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "assets": { "title": "Sites to screen", "type": "array", "description": "List of coordinates to classify against the USDA Cropland Data Layer. Each item is an object: {\"lat\": , \"lon\": , \"label\": \"\"}. Coverage is the Contiguous United States (CONUS); points outside CONUS return a valid 'No Data' row. Each site produces exactly one billable dataset row. Invalid points produce an ERROR row and the run continues." }, "year": { "title": "CDL year", "minimum": 2008, "maximum": 2025, "type": "integer", "description": "USDA Cropland Data Layer vintage year to sample (national CDL is published annually). Values are clamped to 2008-2025; the most recent fully published year is recommended. Default 2024.", "default": 2024 }, "maxAssets": { "title": "Max site lookups", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Safety cap on the number of sites classified per run. Sites beyond this cap are skipped with a warning.", "default": 500 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```