Crowd-Sourced Road Quality Mapping in the Developing World

• URL: http://arxiv.org/abs/2012.00179v1
• Date: Tue, 1 Dec 2020 00:10:36 GMT
• Title: Crowd-Sourced Road Quality Mapping in the Developing World
• Authors: Benjamin Choi, John Kamalu
• Abstract summary: Road networks are among the most essential components of a country's infrastructure. Up-to-date mapping of the the geographical distribution of roads and their quality is essential in high-impact applications ranging from land use planning to wilderness conservation. We present a new crowd-sourced approach capable of assessing road quality and identify key challenges and opportunities in the transferability of deep learning based methods across domains.
• Score: 0.42173327609427325
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Road networks are among the most essential components of a country's infrastructure. By facilitating the movement and exchange of goods, people, and ideas, they support economic and cultural activity both within and across borders. Up-to-date mapping of the the geographical distribution of roads and their quality is essential in high-impact applications ranging from land use planning to wilderness conservation. Mapping presents a particularly pressing challenge in developing countries, where documentation is poor and disproportionate amounts of road construction are expected to occur in the coming decades. We present a new crowd-sourced approach capable of assessing road quality and identify key challenges and opportunities in the transferability of deep learning based methods across domains.

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