NATURAL DISASTER
Data Sonification · Data Visualization · Climate Change
Topic:
Climate Change
Goal:
Public Engagement
Date:
Nov. 2023 - Dec. 2023
Tool:
Python · Garage Band
Faced with the challenge of conveying the chaotic impact of natural disasters, I transformed relevant data into a multisensory experience.
This project born from my firsthand experiences with natural disasters, driven by a desire to express the overwhelming feelings of suddenness and helplessness they evoke. Focusing on three disasters - lightning, floods, and heavy snow - I employed data sonification technique to transform their characteristics into MIDI sound files using Python. Visually, these phenomena were creatively rendered into artworks.
Frames to Sound
STRIKE
The lightning strike was captured by the building's CCTV footage. A total of 19 lightning strikes occurred within an hour. For each strike, the significant observation was the change in brightness and color throughout the frames. As a result, the data across these 19 strikes were extracted and compiled to form a continuous dataset.
Sound to Sound
RISE
The flood video, captured in August 2022 with my phone at night, exhibit a range of low-frequency rumbling, with varying intensities and pitches over time
Image to Sound
DRAG
The heavy snowfall, subtle in sound and steady across frames, showed its true intensity when illuminated. To showcase this, I used a image of snowfall video from 2022 to analyzed the variations in brightness and other data across the pixel columns from left to right.
Graphic Art
Data Visualization · Python · Blender · Photoshop · Illustrator
This collection features artworks inspired by "Natural Disaster" projects. Each piece transforms original data visualization into diverse artistic expressions through creative manipulation and reinterpretation.
