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Many incumbent \u2018tools of the trade\u2019 are proprietary and were developed to support growth in motor traffic, limiting their utility for transport planners who have been tasked with twenty-first century objectives such as enabling citizen participation, reducing pollution, and increasing levels of physical activity by getting more people walking and cycling. Geographic techniques\u2014such as route analysis, network editing, localised impact assessment and interactive map visualisation\u2014have great potential to support modern transport planning priorities. The aim of this paper is to explore emerging open source tools for geographic analysis in transport planning, with reference to the literature and a review of open source tools that are already being used. A key finding is that a growing number of options exist, challenging the current landscape of proprietary tools. These can be classified as command-line interface, graphical user interface or web-based user interface tools and by the framework in which they were implemented, with numerous tools released as R, Python and JavaScript packages, and QGIS plugins. The review found a diverse and rapidly evolving \u2018ecosystem\u2019 tools, with 25 tools that were designed for geographic analysis to support transport planning outlined in terms of their popularity and functionality based on online documentation. They ranged in size from single-purpose tools such as the QGIS plugin AwaP to sophisticated stand-alone multi-modal traffic simulation software such as MATSim, SUMO and Veins. Building on their ability to re-use the most effective components from other open source projects, developers of open source transport planning tools can avoid \u2018reinventing the wheel\u2019 and focus on innovation, the \u2018gamified\u2019 A\/B Street\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/dabreegster\/abstreet\/#abstreet\">https:\/\/github.com\/dabreegster\/abstreet\/#abstreet<\/jats:ext-link>\n                    simulation software, based on OpenStreetMap, a case in point. The paper, the source code of which can be found at\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/robinlovelace\/open-gat\">https:\/\/github.com\/robinlovelace\/open-gat<\/jats:ext-link>\n                    , concludes that, although many of the tools reviewed are still evolving and further research is needed to understand their relative strengths and barriers to uptake, open source tools for geographic analysis in transport planning already hold great potential to help generate the strategic visions of change and evidence that is needed by transport planners in the twenty-first century.\n                  <\/jats:p>","DOI":"10.1007\/s10109-020-00342-2","type":"journal-article","created":{"date-parts":[[2021,1,16]],"date-time":"2021-01-16T10:02:28Z","timestamp":1610791348000},"page":"547-578","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":57,"title":["Open source tools for geographic analysis in transport planning"],"prefix":"10.1007","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5679-6536","authenticated-orcid":false,"given":"Robin","family":"Lovelace","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,1,16]]},"reference":[{"key":"342_CR1","unstructured":"Abadi M, Agarwal A, Barham P, Brevdo E, Chen Z, Citro C, Corrado GS, et al (2016) TensorFlow: large-scale machine learning on heterogeneous distributed systems. arXiv:1603.04467 [cs]"},{"key":"342_CR2","unstructured":"Anderson LD (1991) Applying geographic information systems to transportation planning. 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