# Truck Traffic Monitoring with Satellite Images

## TL;DR

This paper demonstrates a method to estimate truck traffic in developing countries using satellite images and object detection, addressing data scarcity in freight monitoring.

## Contribution

It introduces a complete model for counting trucks in satellite images and predicting annual traffic, including uncertainty analysis and transferability to low-resource settings.

## Key findings

- Successful truck counting in satellite images
- Estimated annual truck traffic with quantified uncertainty
- Potential application in developing countries' freight monitoring

## Abstract

The road freight sector is responsible for a large and growing share of greenhouse gas emissions, but reliable data on the amount of freight that is moved on roads in many parts of the world are scarce. Many low- and middle-income countries have limited ground-based traffic monitoring and freight surveying activities. In this proof of concept, we show that we can use an object detection network to count trucks in satellite images and predict average annual daily truck traffic from those counts. We describe a complete model, test the uncertainty of the estimation, and discuss the transfer to developing countries.