Justin Cai ’24


Civil and Environmental Engineering

Project Title

Finer-scale Agricultural Burning Mapping in Punjab, India

Presentation Link

View Justin's Presentation

I studied the burning of agricultural land by farmers in northern India, which is driven by labor shortages and the timing of growing seasons. Agricultural burning is a significant concern due to its greenhouse gas emissions and air pollution. The goal of my project was to map this burning using fine-scale satellite imagery since little information currently exists on where and when this burning occurs. I started by manually classifying burned land to provide training and validation data for a supervised image classification algorithm, which would ideally classify burned agricultural land. Then, I cleaned the satellite imagery to remove potentially defective images and interpolated the resulting missing values to prepare it for classification. I am continuing to research other optimizations and noise-reduction techniques, as well as develop a robust classification workflow and evaluate its accuracy. I gained substantial experience working through a professional data science workflow, giving me a better sense of how geographic analysis is conducted in a rigorous scientific context. This internship sparked my interest in the applications of machine learning in environmental science, and I intend to continue studying civil and environmental engineering and statistics and machine learning, possibly working in these fields in the future.

Internship Year


Project Category

Urban Systems and Planning for a Sustainable Future


Sustainable Urban Systems Lab, Department of Civil and Environmental Engineering, Princeton University


Anu Ramaswami, Sanjay Swani ’87 Professor of India Studies, Professor of Civil and Environmental Engineering and the High Meadows Environmental Institute