Global Agricultural Analytics Visualization

A comprehensive data visualization project that explores global agricultural production, sustainability metrics, and regional trends from 1961 to 2007.

Link：https://com-480-data-visualization.github.io/Yakety/

A process book showcases the progression of the design workflow: process book

The screencast of what you can do with this viz: video demo

Project Overview

This project provides an interactive visualization platform for analyzing global agricultural data, focusing on:

• Global grain production patterns
• Regional production dynamics
• Sustainable resource utilization
• Agricultural intensification indicators

Technical Setup

Prerequisites

• Modern web browser (Chrome, Firefox, Safari, or Edge)
• Local web server (for development)

Dependencies

The project uses the following main libraries:

• D3.js (v7.8.5) - For data visualization and mapping
• TopoJSON (v3.0.2) - For geographic data processing
• Chart.js - For radar charts and other statistical visualizations

Project Structure

├── assets/           # Media assets (images, videos)
├── data/            # Data files
├── fonts/           # Custom fonts
├── img/             # Image resources
├── js/
│   └── charts/      # JavaScript visualization modules
│       ├── main.js          # Main visualization logic
│       ├── constants.js     # Shared constants and configurations
│       ├── land-map.js      # Land utilization map visualization
│       ├── radar.js         # Radar charts implementation
│       └── dynamic.js       # Dynamic chart updates
├── styles.css       # Main stylesheet
└── index.html       # Main application file

Features

1. Interactive World Map

• Visualizes global agricultural production data
• Supports multiple crop type selections
• Interactive tooltips with detailed information

2. Production Analysis

• Regional production trends over time
• Comparative analysis between continents
• Dynamic bar charts showing production rankings

3. Sustainability Metrics

• Land utilization patterns
• Fertilizer usage analysis
• Water resource utilization
• Regional sustainability indicators

4. Radar Charts

• Multi-dimensional analysis of agricultural sustainability
• Region-specific sustainability profiles
• Interactive data exploration

Usage

1. Clone the repository
2. Set up a local web server
3. Run 'python -m http.server 8000' in local terminal
4. Open http://[::]:8000/ in your web browser

Data Sources

The project uses agricultural data from various sources, including:

• FAO (Food and Agriculture Organization)
• World Bank
• Regional agricultural databases

License

This project is part of the COM-480 Data Visualization course at EPFL.

Team Members

• Yuan Xiao (404006)
• Jingyi Guo (377173)
• Wenyu Liu (383193)