Visualizing Weather Forecasts Through Landscape Imagery
The "Weather as Landscape" project visualizes weather forecasts using landscape imagery, encoding weather data and time markers. It is implemented in Python for an E-Ink display and requires an ESP32 board.
Read original articleThe "Weather as Landscape" GitHub repository presents a novel approach to visualizing weather forecasts through landscape imagery, aiming to make weather information more intuitive and calming compared to traditional numerical displays. The project encodes weather data within a landscape image, where the horizontal axis represents a 24-hour timeline, and various landscape elements symbolize different weather conditions. Key features include time markers for sunrise, sunset, and other significant times, as well as detailed weather forecasts such as wind direction, temperature, cloud cover, and precipitation. The implementation is done in Python using the Pillow library, with data sourced from OpenWeather, and is tailored for a 296x128 E-Ink display. Users can run the code on both Linux and Windows, with instructions provided for setup, including the need to update the OpenWeather API key. The project requires an ESP32 development board and a 2.9-inch E-Ink display module. Example outputs showcase various landscape images that depict different weather scenarios, including sunny and rainy conditions.
- The project visualizes weather forecasts using landscape imagery.
- It encodes various weather details and time markers within the landscape.
- Implementation is done in Python, utilizing the Pillow library and OpenWeather data.
- The project is designed for a specific E-Ink display and requires an ESP32 board.
- Example outputs illustrate different weather conditions through visual representation.
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- Many users express admiration for the project's creative approach to visualizing weather data.
- Several commenters share their own similar projects or ideas, indicating a growing interest in weather visualization.
- Feedback includes suggestions for enhancing user experience, such as clearer iconography and more intuitive representations of weather conditions.
- Some users find the current visualizations confusing without proper explanations of the symbols used.
- There is a desire for broader applications, such as mobile apps or offline functionality.
put it on 'manual filter' and try setting some of the filters, you can see the tagged images it comes up with. I wasn't really interested in this being an accurate weather report, I was thinking more of using it in a photoframe or as a desktop background for mood.
the image tags are all in here https://github.com/bazzargh/bazzargh.github.io/blob/master/w...
and were largely done manually, I started by picking paintings I liked, then looking for gaps in the tags and trying to find paintings to cover those.
This is what it's showing right now: https://ibb.co/8K5jZ3B
I have the screen set up on my desk, and the image evolves throughout the day. Watching these changes is surprisingly enjoyable. For example, rain might appear from the right side and disappear after a few hours, or trees might start to grow. Meanwhile, the sun and moon steadily move forward, marking the transition between day and night.
Another fun aspect is how the setup resembles a binary clock. People often suspect it represents something meaningful but don’t always know how to interpret it. Still, the simplicity of the design invites them to try and figure it out.
1. Make the bending trees signify wind direction. Have to get creative with north and south, but a tree bent down vs out can do, and the bend or size and clustering of trees should signify magnitude of the wind.
2. Put sunrise and sunset as literally sun over the horizon, not the sun and moon.
3. Make the night sky shaded differently than day
4. Don't start at "current time" but rather a fixed point, either morning or midnight, and specify the "now" via the location of the house
I love the idea of artwork that actually conveys useful information.
[1]: https://play.google.com/store/apps/details?id=kaka.wallpaper...
However, you only get to see one moment at a time, requiring you to scroll horizontally through the day, and the temperature is only shown as a number.
https://apps.apple.com/no/app/yr/id490989206?l=nb
https://play.google.com/store/apps/details?id=no.nrk.yr&pcam...
Ex: I am almost never interested in "30% chance of shower at 08:00pm" type of forecast. I am more interested in the trend in which the clouds/rains are moving. This helps me figure out which direction I can drive to get the best sunshine or whatever else.
Is there anyone else who is doing it the way windy.com is doing? I really love them, and so far their experience is great (almost no dark UX patterns), that said I would love to see some more competition in this space.
If you have to learn counterintuitive things like "the appearance of the sun anywhere in the sky indicates sunrise", and "nighttime is indicated by, well, idk what exactly, but it's not darkness", it kind of fails at it's main purpose, I think.
EDIT: I'll add that many weather apps have a left-to-right timeline of some sort, and indicate sunrise and sunset with intuitive iconography.
EDIT2: The Windy.com timeline view shows sky condition, day/night, moon phase, temperature, precipitation, and wind speed and direction in a nice compact left-to-right timeline. (click the summary in the upper left)
I am throwing in my Plotly.js-based weather display, based on OpenWeatherMap and hand-drawn graphics: https://github.com/quimoniz/ophelia?tab=readme-ov-file#-ophe...
(by default it also displays the Hacker News newsfeed)
> Traditional weather stations often display sensor readings as raw numerical data. Navigating these dashboards can be overwhelming and stressful, as it requires significant effort to locate, interpret, and visualize specific parameters effectively.
Simply fascinating. The reverse holds true for me. Numbers provide easily identifiable and recognizable references, while sample images look incomprehensible to me. Without accompanying descriptions, I'd never guess what the author is getting at (except in the broadest of strokes). To each their own, of course.
It's a master class in information density while also being intuitive and readable.
Mostly, the weather around where I live is described as 'Mostly shite'.
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