Parks map
Coverage across 30+ U.S. National Parks.
WebAppIn development
Forecast My Park
Web app using machine learning to predict visitor crowds at 30+ U.S. National Parks. Combines real-time weather, historical visitor patterns, and forecasting models for up to 365-day predictions with interactive visualizations and crowd-level indicators.
Gallery
365-day view
Long-horizon crowd predictions by park.
Crowd levels
At-a-glance indicators for planning trips.
Product
Forecast My Park helps travelers and planners anticipate crowds across 30+ U.S. National Parks—weather, history, and ML forecasts up to a year out, with clear crowd-level visuals.
Problem
Park visits are hard to plan when crowding and weather shift by season and day.
Solution
ML forecasts fused with weather and historical patterns, presented in an interactive web UI.
Highlights
- Crowd predictions for 30+ U.S. National Parks
- Up to 365-day forecasts
- Interactive visualizations with crowd-level indicators
Specs
- Coverage
- 30+ National Parks
- Horizon
- Up to 365 days
- Inputs
- Weather + visitor history
- Stack
- Python, ML, forecasting
- UX
- Interactive visualizations
How it works
- 1Choose a park from the interactive map or list.
- 2Set a date range within the 365-day forecast window.
- 3Review crowd-level indicators alongside weather context.
- 4Compare parks or dates to pick a quieter visit window.
Achievements
- Forecasts for 30+ U.S. National Parks
- Up to year-ahead crowd predictions
- Designed for clear trip-planning decisions
Stack
PythonMachine LearningForecasting
Core StackFrontendData & Machine LearningDesign & DX