We extract route coordinates, elevation profiles, difficulty ratings, user reviews, and trailhead metadata from AllTrails. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Trail Metadata objects from alltrails.com. All fields typed and schema-versioned.
"trail_id": "10293847", "name": "Yosemite Falls Trail", "difficulty": "hard", "length_km": 11.6, "elevation_gain_m": 998, "avg_rating": 4.8, "review_count": 14205
| # | trail_id | name | difficulty | length_km | elevation_gain_m | route_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Route Data objects from alltrails.com. All fields typed and schema-versioned.
"trail_id": "10293847", "latitude": 37.7564, "longitude": -119.5968, "elevation_m": 1219, "distance_marker": 0.0, "point_index": 1, "waypoint_name": "Lower Falls Trailhead"
| # | trail_id | latitude | longitude | elevation_m | distance_marker | waypoint_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews objects from alltrails.com. All fields typed and schema-versioned.
"review_id": "R9827364", "trail_id": "10293847", "rating": 5, "review_text": "Steep climb but incredible views of Half Dome at the top.", "date_posted": "2026-05-14", "activity_type": "hiking", "trail_conditions": "muddy, bugs"
| # | review_id | trail_id | user_id | rating | review_text | date_posted |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Park Data objects from alltrails.com. All fields typed and schema-versioned.
"park_id": "P83746", "park_name": "Yosemite National Park", "country": "USA", "state": "California", "total_trails": 243, "acreage": 759620, "contact_phone": "+1-209-372-0200"
| # | park_id | park_name | country | state | total_trails | acreage |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Trailhead Logistics objects from alltrails.com. All fields typed and schema-versioned.
"trail_id": "10293847", "parking_lat": 37.7423, "parking_lng": -119.6012, "fee_required": true, "fee_amount": 35.0, "dog_rules": "no dogs allowed", "facilities": "['restrooms', 'visitor center']", "wheelchair_accessible": false
| # | trail_id | parking_lat | parking_lng | fee_required | fee_amount | dog_rules |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our AllTrails scraper navigates map interfaces, parses GeoJSON payloads, and extracts historical reviews across thousands of global parks.
Extract raw coordinate arrays for trail routes, including latitude, longitude, and elevation data points.
Capture total elevation gain, highest point, lowest point, and gradient shifts across the entire route.
Extract user reviews, star ratings, trail conditions, activity types, and date posted across all paginated views.
Capture parking coordinates, facility availability, fee structures, and accessibility rules for every trail.
Map individual trails to parent parks, capturing total trail counts, park descriptions, and contact information.
Extract and normalise descriptive tags like dog friendly, kid friendly, paved, waterfall, and wildlife.
Scrape trails across North America, Europe, and Asia, maintaining consistent schemas despite regional interface variations.
Extract URLs, timestamps, and user attribution for trail photos uploaded by the community.
Monitor recent reviews for real-time trail conditions like snow, mud, or closures.
Brief in. Clean data out.
Provide target regions, park names, or specific trail URLs. We design the extraction schema together.
We configure Scrapy crawlers, coordinate extraction logic, proxy rotation, and session management.
Schema validation, coordinate boundary checks, and sample reviews before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
AllTrails relies heavily on interactive maps and dynamic API calls. Here is how we extract clean data from complex interfaces.
Trail coordinates are often loaded via background API calls rather than static HTML. We intercept these network requests during Playwright sessions to extract raw GeoJSON payloads directly, ensuring high precision for route mapping.
AllTrails limits high-volume requests from datacenter IPs. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing to maintain continuous access without rate limits.
Popular trails have tens of thousands of reviews loaded dynamically. We manage stateful pagination sessions to extract the entire historical corpus, not just the recent visible items.
AllTrails displays distances and elevations in imperial or metric units depending on the region and user settings. We normalise all extracted measurements to a consistent metric baseline during the extraction phase.
When AllTrails updates their frontend components or API structures, our monitoring stack detects null-rate spikes immediately. We adjust selectors and API endpoints before your downstream applications fail.
Integrate comprehensive trail networks and elevation profiles into custom mapping software and navigation tools.
Analyse trail popularity, user ratings, and visitor feedback to optimise park management and marketing strategies.
Correlate trail difficulty and terrain types with regional demand for specific outdoor gear and footwear.
Study environmental impact, trail erosion patterns, and human activity levels using historical review data and condition reports.
Enrich property listings and hotel descriptions with proximity metrics to highly rated hiking and biking trails.
Seed new fitness applications with accurate route data, elevation gains, and difficulty classifications for users.
"AllTrails holds the definitive global dataset for outdoor recreation, but extracting structured geospatial routing and elevation profiles requires heavy lifting."
Most teams underestimate the investment required: reliable AllTrails scraping requires residential proxies, full JavaScript rendering for map tiles, GeoJSON parsing, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on spatial analysis, not infrastructure.
Everything supported by our alltrails.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and deduplication. Playwright handles JavaScript rendering and network interception for map data. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About alltrails.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available trail descriptions, reviews, and coordinate data is generally permissible. DataFlirt targets only public, non-authenticated data. We do not extract private user tracks or circumvent paywalls for AllTrails+ features.
We use Playwright to render the trail pages and intercept the underlying network requests that fetch the GeoJSON payloads. This ensures we capture accurate latitude, longitude, and elevation arrays rather than estimating from static images.
Yes. We can target a specific park URL and iterate through all child trails, paginating through every historical review to build a complete dataset of user feedback and conditions.
AllTrails displays data in imperial or metric units based on location. Our pipeline detects the source unit and normalises all length and elevation fields to metric values (kilometres and metres) before delivery.
Yes. We can configure pipelines to run daily or weekly, scanning recent reviews for keywords related to trail conditions, closures, or weather impacts, and delivering only the new records.
Our smallest packages start at a defined list of parks or regions (typically 1,000 to 5,000 trails) with weekly delivery. For global catalogue extraction, we price based on compute volume.
Yes. We provide a sample run of up to 100 trails as part of the pre-engagement scoping process so you can validate coordinate arrays, review completeness, and schema fit before signing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off export of national park trails or a continuous feed of user reviews — we scope, build, and operate the pipeline. Tell us what you need.
