Mapping Historical Crop Yields across India

Data Visualization

Maps offer an intuitive means to represent the spatial distribution of data, helping users understand the geographic context and relationships between different locations. With human-induced climate change a reality, understanding evolutionary patterns in nationwide crop yields is essential to ensure food sustainability. India is the world’s second-largest producer of rice, wheat, sugarcane, groundnut, and cotton. Using Python, I built an interactive dashboard to visualize district-level yield distributions of these crops across India between 1990 – 2017. This dashboard (presently offline) was hosted on the Amazon Web Services EC2 server.

Author

Akshay Suresh

Published

May 1, 2023

Note

Github repo: agriyield_viz
2-minutes video presentation: YouTube link
Presentation slides: PDF
Programming language: Python (geopandas, plotly), Dash
App hosting platform: Amazon Web Services EC2

This project was completed as part of the Erdös Institute Data Visualization Mini-course, Spring 2023.

Application features

I included a live walkthrough of the dashboard in my 2-minutes project presentation video, showcasing the following interactive features.

User option to zoom in/out of the map
Cursor hover displaying values of the plotted quantity for the selected district.
Dropdown menu for selecting the quantity to visualize. Options include yield (kg/ha), harvested area (1000 ha), and production (1000 tonnes).
Dropdown menu for selecting a crop of interest. Here, the available menu options are Rice, Wheat, Sugarcane, Cotton, and Groundnut.
Slider to select a year between 1990 and 2017.

Dashboard screenshot

Screenshot of interactive dashboard

Project Workflow

Application workflow