Truck traffic monitoring with satellite images
- 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.
Document Type: | Part of a Book |
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Language: | German |
Author(s): | Lynn KaackORCiD, George Chen, M Granger Morgan |
Parent Title (German): | Proceedings of the 2nd ACM SIGCAS Conference on Computing and Sustainable Societies |
Publisher: | Association for Computing Machinery |
Place of Publisher: | New York |
Publication year: | 2019 |
Publishing Institution: | Hertie School |
First Page: | 155 |
Last Page: | 164 |
DOI: | https://doi.org/10.1145/3314344 |
Release Date: | 2021/10/07 |
Licence of document (German): | Metadaten / metadata |