# Sage-Grouse Habitat Siting Screener — BLM/USFS PHMA/GHMA (`malonestar/blm-sage-grouse-siting-screener`) Actor Point-in-polygon screen of coordinates against seven federal Greater Sage-Grouse Habitat Management Area sources (BLM/USFS: WY, UT, NV/CA, CO, ID/MT, OR) for western wind, solar, oil and gas, and transmission siting. Returns habitat tier, managing agency, and permitting stipulation flags. - **URL**: https://apify.com/malonestar/blm-sage-grouse-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, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.40 / 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 ## Sage-Grouse Habitat Siting Screener — BLM/USFS PHMA/GHMA API Point-in-polygon screening of coordinates against **seven federal Greater Sage-Grouse (GRSG) Habitat Management Area sources** — BLM and USFS Records of Decision covering Wyoming, Utah, Nevada/California, Colorado, Idaho/SW Montana, and Oregon. Built for western wind, solar, oil & gas, transmission, and BESS developers who need to know, before they spend money on a NEPA package, whether a proposed site sits inside sage-grouse Priority or General Habitat. Greater Sage-Grouse habitat stipulations are one of the biggest schedule and scope risks in western federal-land energy siting: Priority Habitat Management Areas (PHMA) commonly carry seasonal timing limitations, surface-disturbance density caps, noise thresholds near leks, and net-conservation-gain / mitigation requirements under the governing BLM/USFS Resource Management Plan. Finding this out during due diligence — not during permitting — is the whole point of this actor. ### Who this is for - **Wind, solar, and BESS developers** siting projects on BLM/USFS land in the 11-state sage-grouse range. - **Oil & gas and mining operators** evaluating lease parcels or well pads for seasonal-timing and disturbance-cap exposure. - **Transmission and pipeline right-of-way applicants** routing corridors through federal sage-grouse country. - **NEPA / environmental consultants** doing early constraints screening before a formal Biological Assessment. - **AI agents / MCP tool chains** doing automated site-due-diligence rollups alongside critical-habitat, wetlands, and grid-proximity checks. ### Why this actor (and not a raw GIS layer) There is **no single national BLM sage-grouse layer** — coverage is a federated set of per-sub-region Records of Decision, each with its own ArcGIS service and, maddeningly, its own attribute field name for the same PHMA/GHMA/IHMA vocabulary (`Habitat_Ty`, `Habitat_ID`, `GRSG_Categ`, `FinalHabit`, `Habitat_Management_Area`, `HMA`). This actor queries all seven verified services server-side per asset, normalizes the field-name drift into one fixed code set, resolves overlapping designations to the single most restrictive tier, and attaches a plain-English stipulation summary — so you get one clean answer per coordinate instead of seven different GIS exports to reconcile by hand. ### What it does For each input coordinate, the actor: 1. Runs a server-side point-in-polygon query against all 7 GRSG sources. 2. Collects every intersecting designation (a point can legitimately fall in more than one overlapping polygon). 3. Picks the **most restrictive** designation as primary (PHMA > IHMA > RHMA > LCHMA > OHMA > GHMA > UDH > Anthro Mtn). 4. Attaches a stipulation-level flag and a plain-English developability note. 5. If the exact point is clear and you set `radiusMiles`, optionally checks for nearby habitat within that radius as siting context. ### Example input ```json { "assets": [ { "lat": 42.985, "lon": -109.865, "label": "Upper Green River Basin, WY" }, { "lat": 39.7392, "lon": -104.9903, "label": "Downtown Denver, CO" } ], "radiusMiles": 10, "maxAssets": 25 } ```` ### Output fields | Field | Description | |---|---| | `asset_label`, `asset_lat`, `asset_lon` | The screened point. | | `in_habitat` | True if the point falls inside any queried designation. | | `habitat_type` / `habitat_type_label` | Code (PHMA/GHMA/IHMA/RHMA/LCHMA/OHMA/UDH/"Anthro Mtn") and plain-English label of the most restrictive overlapping designation. | | `stipulation_level` | Editorial restrictiveness tier: `high`, `high-moderate`, `moderate`, `low-moderate`, `low`, `special`, or `unknown`. | | `developability_note` | Plain-English summary of the typical permitting stipulations for that tier. | | `managing_source` / `managing_agency` | Which of the 7 federal sources and agency produced the primary hit. | | `overlapping_designation_count` / `overlapping_designations` | Full list when a point falls in more than one designation. | | `nearby_habitat_checked` / `nearby_habitat_found` / `nearby_habitat_types` / `radius_miles_used` | Nearby-habitat context when the exact point is clear and `radiusMiles` > 0. | | `checked_sources` / `source_errors` | Transparency on which of the 7 sources were queried and any that failed. | | `disclaimer`, `checked_at` | Informational-use disclaimer and UTC run timestamp. | ### Coverage and honest limits Verified live sources: BLM/USFS Wyoming 9-Plan, Utah, Nevada/California, Northwest Colorado, and Idaho/SW Montana GRSG Records of Decision, plus BLM statewide Colorado and Oregon services. A **CLEAR** result means no queried source intersects the point — it does **not** rule out habitat in a sub-region outside this coverage set (e.g. Montana outside the ID/SW-MT EIS area, Washington, North/South Dakota). This is an informational screen, not an official agency determination — confirm any siting or permitting decision with the relevant BLM Field Office or USFS Ranger District. ### Use as an MCP tool This actor is Pay-Per-Event priced and discoverable to AI agents (Claude, Cursor, etc.) via mcp.apify.com. Field-level output descriptions make it a clean, chainable grounding tool for automated site-due-diligence workflows — pair it with critical-habitat, wetlands, karst, or grid-proximity screeners for a full federal-land siting constraints rollup. ### FAQ **Does this cover all 11 sage-grouse states?** No — it covers the 7 verified federal sub-region services (WY, UT, NV/CA, CO, ID/MT, OR), which represent the large majority of BLM/USFS-managed sage-grouse habitat and energy-development activity. Montana areas outside the ID/SW-MT EIS, Washington, and the Dakotas are not yet covered. **What's the difference between PHMA, GHMA, and IHMA?** PHMA (Priority Habitat Management Area) is the most restrictive tier — highest-value breeding, nesting, and winter habitat. GHMA (General Habitat Management Area) is the least restrictive designated tier. IHMA (Important Habitat Management Area), specific to the Idaho/SW Montana sub-region, sits between the two. **Is this a substitute for a Biological Assessment or formal NEPA consultation?** No. It's a fast, informational pre-screen to catch sage-grouse exposure before you commit engineering and legal spend — always confirm with the managing BLM Field Office or USFS Ranger District before final siting. **Does a CLEAR result guarantee no sage-grouse issue?** No — see Coverage and honest limits above. Use `radiusMiles` to also flag nearby habitat as a siting-margin warning. # Actor input Schema ## `assets` (type: `array`): List of points to screen against 7 federal Greater Sage-Grouse Habitat Management Area sources (BLM/USFS: Wyoming, Utah, Nevada/California, Colorado, Idaho/SW Montana, Oregon). Each item is an object with numeric lat and lon (WGS84 decimal degrees) and an optional label. One billable result row is returned per asset. Example: \[{"lat":42.985,"lon":-109.865,"label":"Upper Green River Basin, WY"}]. ## `radiusMiles` (type: `integer`): When a point is clear at the exact coordinate, also search this many miles around it and report any nearby Greater Sage-Grouse habitat as context (no precise distance is computed -- this is a proximity flag, not a nearest-edge measurement). Set to 0 to skip the nearby search and only screen the exact point. ## `maxAssets` (type: `integer`): Maximum number of assets to screen from the assets list (safety cap). Extra assets beyond this are ignored. ## Actor input object example ```json { "assets": [ { "lat": 42.985, "lon": -109.865, "label": "Upper Green River Basin, WY (Pinedale gas field -- Priority Habitat)" }, { "lat": 39.7392, "lon": -104.9903, "label": "Downtown Denver, CO (clear -- urban Front Range)" } ], "radiusMiles": 10, "maxAssets": 25 } ``` # Actor output Schema ## `results` (type: `string`): The default dataset. # 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": 42.985, "lon": -109.865, "label": "Upper Green River Basin, WY (Pinedale gas field -- Priority Habitat)" }, { "lat": 39.7392, "lon": -104.9903, "label": "Downtown Denver, CO (clear -- urban Front Range)" } ], "radiusMiles": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("malonestar/blm-sage-grouse-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": 42.985, "lon": -109.865, "label": "Upper Green River Basin, WY (Pinedale gas field -- Priority Habitat)", }, { "lat": 39.7392, "lon": -104.9903, "label": "Downtown Denver, CO (clear -- urban Front Range)", }, ], "radiusMiles": 10, } # Run the Actor and wait for it to finish run = client.actor("malonestar/blm-sage-grouse-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": 42.985, "lon": -109.865, "label": "Upper Green River Basin, WY (Pinedale gas field -- Priority Habitat)" }, { "lat": 39.7392, "lon": -104.9903, "label": "Downtown Denver, CO (clear -- urban Front Range)" } ], "radiusMiles": 10 }' | apify call malonestar/blm-sage-grouse-siting-screener --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=malonestar/blm-sage-grouse-siting-screener", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Sage-Grouse Habitat Siting Screener — BLM/USFS PHMA/GHMA", "description": "Point-in-polygon screen of coordinates against seven federal Greater Sage-Grouse Habitat Management Area sources (BLM/USFS: WY, UT, NV/CA, CO, ID/MT, OR) for western wind, solar, oil and gas, and transmission siting. Returns habitat tier, managing agency, and permitting stipulation flags.", "version": "1.0", "x-build-id": "ylLOPToJF00ft0p20" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/malonestar~blm-sage-grouse-siting-screener/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-malonestar-blm-sage-grouse-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~blm-sage-grouse-siting-screener/runs": { "post": { "operationId": "runs-sync-malonestar-blm-sage-grouse-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~blm-sage-grouse-siting-screener/run-sync": { "post": { "operationId": "run-sync-malonestar-blm-sage-grouse-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": "Assets (coordinates to screen)", "type": "array", "description": "List of points to screen against 7 federal Greater Sage-Grouse Habitat Management Area sources (BLM/USFS: Wyoming, Utah, Nevada/California, Colorado, Idaho/SW Montana, Oregon). Each item is an object with numeric lat and lon (WGS84 decimal degrees) and an optional label. One billable result row is returned per asset. Example: [{\"lat\":42.985,\"lon\":-109.865,\"label\":\"Upper Green River Basin, WY\"}]." }, "radiusMiles": { "title": "Nearby-habitat search radius (miles)", "minimum": 0, "maximum": 50, "type": "integer", "description": "When a point is clear at the exact coordinate, also search this many miles around it and report any nearby Greater Sage-Grouse habitat as context (no precise distance is computed -- this is a proximity flag, not a nearest-edge measurement). Set to 0 to skip the nearby search and only screen the exact point.", "default": 10 }, "maxAssets": { "title": "Max assets", "minimum": 1, "maximum": 200, "type": "integer", "description": "Maximum number of assets to screen from the assets list (safety cap). Extra assets beyond this are ignored.", "default": 25 } } }, "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 } } } } } } } } } } ```