# Wild & Scenic River Proximity Screener - Section 7 Flag (`malonestar/wild-scenic-river-proximity-screener`) Actor Wild & Scenic River proximity API: per lat/lon site, nearest designated Wild & Scenic River corridor - name, classification (Wild/Scenic/Recreational), managing agency and distance - plus a WSR Act Section 7 free-flow flag. USFS open data. For hydro, dredge, NEPA and land due-diligence. - **URL**: https://apify.com/malonestar/wild-scenic-river-proximity-screener.md - **Developed by:** [Kyle Maloney](https://apify.com/malonestar) (community) - **Categories:** Agents, Developer tools, Real estate - **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 ## Wild & Scenic River Proximity Screener — Section 7 Flag Batch **coordinate screener** for proximity to designated **National Wild & Scenic Rivers (WSR)**. Give it a list of sites (lat/lon) and it returns, for each site, the **nearest designated Wild & Scenic River corridor** — river name, **segment classification** (Wild / Scenic / Recreational), managing/administering agency, and the **nearest-distance** — plus a **`wsr_section7_flag`** that fires when a designated river lies within your search radius. Under **Section 7 of the Wild & Scenic Rivers Act**, a federally assisted water-resources project — a dam, diversion, bank stabilization, **FERC hydro license**, bridge, or **dredge-and-fill** — that is *on or directly affecting* a designated river requires a **free-flow determination**. This actor is a fast first-pass screen for that exposure across a whole portfolio of sites. Data is the multi-agency **USFS Enterprise Data Warehouse** National Wild & Scenic River Segments service (USFS / NPS / BLM / FWS, public domain). There are 200+ designated rivers across 39 states and Puerto Rico. ### Who it's for - **Hydropower / energy / water-resources developers** — FERC licensing and dam/diversion siting where a WSR designation can bar or complicate a project. - **Dredge-and-fill / marine / infrastructure contractors** — Section 404 / Section 7 exposure screening. - **NEPA & environmental consultants** — batch pre-screen candidate sites for WSR conflicts before a full review. - **Land, recreation, real-estate & conservation** — flag parcels adjacent to a protected free-flowing river. - **AI agents & data pipelines** — a clean, chainable geospatial due-diligence tool. ### Example input ```json { "assets": [ { "lat": 42.65, "lon": -123.58, "label": "Rogue River, OR", "radius": 5000 }, { "lat": 39.7392, "lon": -104.9903, "label": "Denver, CO", "radius": 5000 } ], "radiusMeters": 5000, "maxResults": 500 } ```` Each asset is `{ lat, lon, label?, radius? }` (radius in **meters**, optional per-asset override). `"lat,lon"` strings and `[lat, lon]` arrays are also accepted. One dataset row (one billed result) is produced per asset. #### Verified sample run A real 6-site run (2026-07-21, 5000 m radius) returned 6 rows and 0 errors: | Asset | Nearest river | Class | Agency | Distance | Section 7 flag | |---|---|---|---|---|---| | Rogue River, OR | Rogue Wild and Scenic River | Wild | USFS + BLM | 0.2596 mi | true | | Salmon River, ID | Salmon Wild and Scenic River | Wild | USFS | 0.3321 mi | true | | Rio Grande, NM | Rio Grande Wild and Scenic River | Wild | USFS + BLM | 0.5811 mi | true | | Upper Delaware River, NY/PA | Delaware Wild and Scenic River | Scenic | Upper Delaware Scenic and Recreational River, NPS | 0.3477 mi | true | | Chattooga River, GA/SC | Chattooga Wild and Scenic River | Wild | USFS | 0.0981 mi | true | | Denver, CO (control) | no river within radius | — | — | — | false | The control point returned a clean, billed "no WSR conflict" row rather than an error. This exact run is published as the actor's example task, so you can open it and re-run it as-is. ### Output fields | Field | Description | |-------|-------------| | `asset_label`, `asset_lat`, `asset_lon` | The screened site. | | `search_radius_meters` | Radius used for this asset. | | `nearest_river_name` / `nearest_river_shortname` | Nearest designated Wild & Scenic River within the radius. | | `nearest_segment_classification` | Wild / Scenic / Recreational classification of the nearest segment. | | `nearest_segment_agency` | Administering agency code of the nearest segment (BLM, USFS, NPS, FWS). | | `administering_agencies` | Managing/administering agencies for the whole corridor. | | `nearest_distance_miles` / `nearest_distance_km` | Nearest-point-on-line distance to the corridor. | | `nearest_river_state` | State of the nearest segment. | | `nearest_river_orvs` | Outstandingly Remarkable Values (fish, scenery, recreation, etc.). | | `nearest_segment_begin` / `nearest_segment_end` | Reach endpoints of the nearest segment. | | `on_designated_river` | True when the site sits essentially on the corridor. | | `rivers_within_radius`, `segments_within_radius` | Counts within the radius. | | `classifications_within_radius` | Distinct classifications present (Wild > Scenic > Recreational). | | `wsr_section7_flag` | True when a designated river is within the radius (Section 7 screening flag). | | `error`, `checked_at`, `source_url` | Diagnostics + provenance. | ### Use as an MCP tool This actor is callable by AI agents (Claude, Cursor, etc.) via **mcp.apify.com**. The field-level output descriptions make it a clean, chainable **geospatial due-diligence tool**: feed it candidate coordinates and it returns a structured Wild & Scenic River proximity + Section 7 verdict per site. ### FAQ **Is this legal advice or a permit determination?** No. `wsr_section7_flag` is an advisory proximity screen. A formal Section 7(a) free-flow determination is made by the administering agency. **How is distance measured?** Nearest-point-on-line (point-to-segment) distance from your coordinate to the river corridor polyline, in miles and kilometers. **What counts as "within range"?** Any designated Wild & Scenic River corridor within your `radius` (meters). Default 5000 m (~3.1 miles); up to ~50 miles. **Which rivers are covered?** All congressionally / secretarially designated National Wild & Scenic Rivers in the USFS multi-agency dataset (USFS, NPS, BLM, FWS) — 200+ rivers across 39 states + Puerto Rico. **What if a site has no river nearby?** You still get a billed row with `wsr_section7_flag: false` and null river fields — a clean "no WSR conflict" record. ### Related screeners This actor is part of a family of single-coordinate federal due-diligence screeners that all take the same `assets[]{lat,lon,label}` input shape, so you can run several over the same site list and join the results per site. - [Site Due Diligence Bundle](https://apify.com/malonestar/site-due-diligence-bundle) — 15 federal overlays for one coordinate in a single call. - [EPA Impaired Waters 303(d) Screener](https://apify.com/malonestar/epa-impaired-waters-303d-screener) — Clean Water Act 303(d) impaired waters near the site. - [FWS Critical Habitat Screener](https://apify.com/malonestar/fws-critical-habitat-screener) — ESA Section 7 designated critical habitat. - [USACE Levee Flood Risk Screener](https://apify.com/malonestar/usace-levee-flood-risk-screener) — leveed-area flood risk from the National Levee Database. - [National Register of Historic Places Screener](https://apify.com/malonestar/nrhp-historic-place-screener) — listed historic properties and districts, NHPA Section 106 flag. - [Tribal Land Jurisdiction Screener](https://apify.com/malonestar/tribal-land-jurisdiction-screener) — reservation / trust land and THPO consultation flag. ### Pricing Pay-per-result: one billed row per screened asset. Empty/no-conflict sites still return a row. *Source: USFS EDW National Wild & Scenic River Segments MapServer (layers 0 corridor + 1 segments). Public-domain federal data. This tool is informational and not a substitute for an agency determination.* # Actor input Schema ## `assets` (type: `array`): Sites to screen for proximity to designated National Wild & Scenic Rivers. Each entry is an object { "lat": number, "lon": number, "label": "optional name", "radius": optional meters }. Also accepts "lat,lon" strings or \[lat, lon] arrays. The optional per-asset "radius" (meters) overrides the global search radius. One dataset row (one billed result) is produced per asset; a bad entry yields an ERROR row and the run continues. ## `radiusMeters` (type: `integer`): Default radius, in meters, around each asset to search for a designated Wild & Scenic River corridor (100-80467, i.e. up to ~50 miles). A river beyond this distance is ignored. Overridden by a per-asset "radius". Default 5000 (~3.1 miles). ## `maxResults` (type: `integer`): Maximum number of assets processed in one run (1-2000). One result row is emitted (and billed) per asset. Default 500. ## Actor input object example ```json { "assets": [ { "lat": 42.65, "lon": -123.58, "label": "Rogue River, OR", "radius": 5000 }, { "lat": 39.7392, "lon": -104.9903, "label": "Denver, CO (no designated river)", "radius": 5000 } ], "radiusMeters": 5000, "maxResults": 500 } ``` # Actor output Schema ## `results` (type: `string`): The default dataset (one row per asset). # 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": 42.65, "lon": -123.58, "label": "Rogue River, OR", "radius": 5000 }, { "lat": 39.7392, "lon": -104.9903, "label": "Denver, CO (no designated river)", "radius": 5000 } ], "radiusMeters": 5000 }; // Run the Actor and wait for it to finish const run = await client.actor("malonestar/wild-scenic-river-proximity-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": 42.65, "lon": -123.58, "label": "Rogue River, OR", "radius": 5000, }, { "lat": 39.7392, "lon": -104.9903, "label": "Denver, CO (no designated river)", "radius": 5000, }, ], "radiusMeters": 5000, } # Run the Actor and wait for it to finish run = client.actor("malonestar/wild-scenic-river-proximity-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": 42.65, "lon": -123.58, "label": "Rogue River, OR", "radius": 5000 }, { "lat": 39.7392, "lon": -104.9903, "label": "Denver, CO (no designated river)", "radius": 5000 } ], "radiusMeters": 5000 }' | apify call malonestar/wild-scenic-river-proximity-screener --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=malonestar/wild-scenic-river-proximity-screener", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Wild & Scenic River Proximity Screener - Section 7 Flag", "description": "Wild & Scenic River proximity API: per lat/lon site, nearest designated Wild & Scenic River corridor - name, classification (Wild/Scenic/Recreational), managing agency and distance - plus a WSR Act Section 7 free-flow flag. USFS open data. For hydro, dredge, NEPA and land due-diligence.", "version": "1.0", "x-build-id": "9ejXvoPeJFPsDGrLG" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/malonestar~wild-scenic-river-proximity-screener/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-malonestar-wild-scenic-river-proximity-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~wild-scenic-river-proximity-screener/runs": { "post": { "operationId": "runs-sync-malonestar-wild-scenic-river-proximity-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~wild-scenic-river-proximity-screener/run-sync": { "post": { "operationId": "run-sync-malonestar-wild-scenic-river-proximity-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 (sites / coordinates to screen)", "type": "array", "description": "Sites to screen for proximity to designated National Wild & Scenic Rivers. Each entry is an object { \"lat\": number, \"lon\": number, \"label\": \"optional name\", \"radius\": optional meters }. Also accepts \"lat,lon\" strings or [lat, lon] arrays. The optional per-asset \"radius\" (meters) overrides the global search radius. One dataset row (one billed result) is produced per asset; a bad entry yields an ERROR row and the run continues." }, "radiusMeters": { "title": "Search radius (meters)", "minimum": 100, "maximum": 80467, "type": "integer", "description": "Default radius, in meters, around each asset to search for a designated Wild & Scenic River corridor (100-80467, i.e. up to ~50 miles). A river beyond this distance is ignored. Overridden by a per-asset \"radius\". Default 5000 (~3.1 miles).", "default": 5000 }, "maxResults": { "title": "Max assets to screen", "minimum": 1, "maximum": 2000, "type": "integer", "description": "Maximum number of assets processed in one run (1-2000). One result row is emitted (and billed) per asset. Default 500.", "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 } } } } } } } } } } ```